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Sample records for scalable flexible-order model

  1. Toward a scalable flexible-order model for 3D nonlinear water waves

    DEFF Research Database (Denmark)

    Engsig-Karup, Allan Peter; Ducrozet, Guillaume; Bingham, Harry B.

    For marine and coastal applications, current work are directed toward the development of a scalable numerical 3D model for fully nonlinear potential water waves over arbitrary depths. The model is high-order accurate, robust and efficient for large-scale problems, and support will be included...... for flexibility in the description of structures by the use of curvilinear boundary-fitted meshes. The mathematical equations for potential waves in the physical domain is transformed through $\\sigma$-mapping(s) to a time-invariant boundary-fitted domain which then becomes a basis for an efficient solution...... strategy on a time-invariant mesh. The 3D numerical model is based on a finite difference method as in the original works \\cite{LiFleming1997,BinghamZhang2007}. Full details and other aspects of an improved 3D solution can be found in \\cite{EBL08}. The new and improved approach for three...

  2. An efficient flexible-order model for 3D nonlinear water waves

    DEFF Research Database (Denmark)

    Engsig-Karup, Allan Peter; Bingham, Harry B.; Lindberg, Ole

    2009-01-01

    The flexible-order, finite difference based fully nonlinear potential flow model described in [H.B. Bingham, H. Zhang, On the accuracy of finite difference solutions for nonlinear water waves, J. Eng. Math. 58 (2007) 211-228] is extended to three dimensions (3D). In order to obtain an optimal......, robustness and energy conservation are presented together with demonstrations of grid independent iteration count and optimal scaling of the solution effort. Calculations are made for 3D nonlinear wave problems for steep nonlinear waves and a shoaling problem which show good agreement with experimental...

  3. An efficient flexible-order model for 3D nonlinear water waves

    International Nuclear Information System (INIS)

    Engsig-Karup, A.P.; Bingham, H.B.; Lindberg, O.

    2009-01-01

    The flexible-order, finite difference based fully nonlinear potential flow model described in [H.B. Bingham, H. Zhang, On the accuracy of finite difference solutions for nonlinear water waves, J. Eng. Math. 58 (2007) 211-228] is extended to three dimensions (3D). In order to obtain an optimal scaling of the solution effort multigrid is employed to precondition a GMRES iterative solution of the discretized Laplace problem. A robust multigrid method based on Gauss-Seidel smoothing is found to require special treatment of the boundary conditions along solid boundaries, and in particular on the sea bottom. A new discretization scheme using one layer of grid points outside the fluid domain is presented and shown to provide convergent solutions over the full physical and discrete parameter space of interest. Linear analysis of the fundamental properties of the scheme with respect to accuracy, robustness and energy conservation are presented together with demonstrations of grid independent iteration count and optimal scaling of the solution effort. Calculations are made for 3D nonlinear wave problems for steep nonlinear waves and a shoaling problem which show good agreement with experimental measurements and other calculations from the literature

  4. An efficient flexible-order model for 3D nonlinear water waves

    Science.gov (United States)

    Engsig-Karup, A. P.; Bingham, H. B.; Lindberg, O.

    2009-04-01

    The flexible-order, finite difference based fully nonlinear potential flow model described in [H.B. Bingham, H. Zhang, On the accuracy of finite difference solutions for nonlinear water waves, J. Eng. Math. 58 (2007) 211-228] is extended to three dimensions (3D). In order to obtain an optimal scaling of the solution effort multigrid is employed to precondition a GMRES iterative solution of the discretized Laplace problem. A robust multigrid method based on Gauss-Seidel smoothing is found to require special treatment of the boundary conditions along solid boundaries, and in particular on the sea bottom. A new discretization scheme using one layer of grid points outside the fluid domain is presented and shown to provide convergent solutions over the full physical and discrete parameter space of interest. Linear analysis of the fundamental properties of the scheme with respect to accuracy, robustness and energy conservation are presented together with demonstrations of grid independent iteration count and optimal scaling of the solution effort. Calculations are made for 3D nonlinear wave problems for steep nonlinear waves and a shoaling problem which show good agreement with experimental measurements and other calculations from the literature.

  5. An efficient flexible-order model for coastal and ocean water waves

    DEFF Research Database (Denmark)

    Engsig-Karup, Allan Peter; Bingham, Harry B.; Lindberg, Ole

    Current work are directed toward the development of an improved numerical 3D model for fully nonlinear potential water waves over arbitrary depths. The model is high-order accurate, robust and efficient for large-scale problems, and support will be included for flexibility in the description...... as in the original works \\cite{LiFleming1997,BinghamZhang2007}. The new and improved approach employs a GMRES solver with multigrid preconditioning to achieve optimal scaling of the overall solution effort, i.e., directly with $n$ the total number of grid points. A robust method is achieved through a special...

  6. From Digital Disruption to Business Model Scalability

    DEFF Research Database (Denmark)

    Nielsen, Christian; Lund, Morten; Thomsen, Peter Poulsen

    2017-01-01

    This article discusses the terms disruption, digital disruption, business models and business model scalability. It illustrates how managers should be using these terms for the benefit of their business by developing business models capable of achieving exponentially increasing returns to scale...... will seldom lead to business model scalability capable of competing with digital disruption(s)....... as a response to digital disruption. A series of case studies illustrate that besides frequent existing messages in the business literature relating to the importance of creating agile businesses, both in growing and declining economies, as well as hard to copy value propositions or value propositions that take...

  7. The Concept of Business Model Scalability

    DEFF Research Database (Denmark)

    Lund, Morten; Nielsen, Christian

    2018-01-01

    -term pro table business. However, the main message of this article is that while providing a good value proposition may help the rm ‘get by’, the really successful businesses of today are those able to reach the sweet-spot of business model scalability. Design/Methodology/Approach: The article is based...... on a ve-year longitudinal action research project of over 90 companies that participated in the International Center for Innovation project aimed at building 10 global network-based business models. Findings: This article introduces and discusses the term scalability from a company-level perspective......Purpose: The purpose of the article is to de ne what scalable business models are. Central to the contemporary understanding of business models is the value proposition towards the customer and the hypotheses generated about delivering value to the customer which become a good foundation for a long...

  8. The Concept of Business Model Scalability

    DEFF Research Database (Denmark)

    Nielsen, Christian; Lund, Morten

    2015-01-01

    The power of business models lies in their ability to visualize and clarify how firms’ may configure their value creation processes. Among the key aspects of business model thinking are a focus on what the customer values, how this value is best delivered to the customer and how strategic partners...... are leveraged in this value creation, delivery and realization exercise. Central to the mainstream understanding of business models is the value proposition towards the customer and the hypothesis generated is that if the firm delivers to the customer what he/she requires, then there is a good foundation...... for a long-term profitable business. However, the message conveyed in this article is that while providing a good value proposition may help the firm ‘get by’, the really successful businesses of today are those able to reach the sweet-spot of business model scalability. This article introduces and discusses...

  9. Scalable inference for stochastic block models

    KAUST Repository

    Peng, Chengbin

    2017-12-08

    Community detection in graphs is widely used in social and biological networks, and the stochastic block model is a powerful probabilistic tool for describing graphs with community structures. However, in the era of "big data," traditional inference algorithms for such a model are increasingly limited due to their high time complexity and poor scalability. In this paper, we propose a multi-stage maximum likelihood approach to recover the latent parameters of the stochastic block model, in time linear with respect to the number of edges. We also propose a parallel algorithm based on message passing. Our algorithm can overlap communication and computation, providing speedup without compromising accuracy as the number of processors grows. For example, to process a real-world graph with about 1.3 million nodes and 10 million edges, our algorithm requires about 6 seconds on 64 cores of a contemporary commodity Linux cluster. Experiments demonstrate that the algorithm can produce high quality results on both benchmark and real-world graphs. An example of finding more meaningful communities is illustrated consequently in comparison with a popular modularity maximization algorithm.

  10. A Scalable Heuristic for Viral Marketing Under the Tipping Model

    Science.gov (United States)

    2013-09-01

    Flixster is a social media website that allows users to share reviews and other information about cinema . [35] It was extracted in Dec. 2010. – FourSquare...work of Reichman were developed independently . We also note that Reichman performs no experimental evaluation of the algorithm. A Scalable Heuristic...other dif- fusion models, such as the independent cascade model [21] and evolutionary graph theory [25] as well as probabilistic variants of the

  11. Scalable inference for stochastic block models

    KAUST Repository

    Peng, Chengbin; Zhang, Zhihua; Wong, Ka-Chun; Zhang, Xiangliang; Keyes, David E.

    2017-01-01

    Community detection in graphs is widely used in social and biological networks, and the stochastic block model is a powerful probabilistic tool for describing graphs with community structures. However, in the era of "big data," traditional inference

  12. Semantic Models for Scalable Search in the Internet of Things

    Directory of Open Access Journals (Sweden)

    Dennis Pfisterer

    2013-03-01

    Full Text Available The Internet of Things is anticipated to connect billions of embedded devices equipped with sensors to perceive their surroundings. Thereby, the state of the real world will be available online and in real-time and can be combined with other data and services in the Internet to realize novel applications such as Smart Cities, Smart Grids, or Smart Healthcare. This requires an open representation of sensor data and scalable search over data from diverse sources including sensors. In this paper we show how the Semantic Web technologies RDF (an open semantic data format and SPARQL (a query language for RDF-encoded data can be used to address those challenges. In particular, we describe how prediction models can be employed for scalable sensor search, how these prediction models can be encoded as RDF, and how the models can be queried by means of SPARQL.

  13. Scalability of Sustainable Business Models in Hybrid Organizations

    Directory of Open Access Journals (Sweden)

    Adam Jabłoński

    2016-02-01

    Full Text Available The dynamics of change in modern business create new mechanisms for company management to determine their pursuit and the achievement of their high performance. This performance maintained over a long period of time becomes a source of ensuring business continuity by companies. An ontological being enabling the adoption of such assumptions is such a business model that has the ability to generate results in every possible market situation and, moreover, it has the features of permanent adaptability. A feature that describes the adaptability of the business model is its scalability. Being a factor ensuring more work and more efficient work with an increasing number of components, scalability can be applied to the concept of business models as the company’s ability to maintain similar or higher performance through it. Ensuring the company’s performance in the long term helps to build the so-called sustainable business model that often balances the objectives of stakeholders and shareholders, and that is created by the implemented principles of value-based management and corporate social responsibility. This perception of business paves the way for building hybrid organizations that integrate business activities with pro-social ones. The combination of an approach typical of hybrid organizations in designing and implementing sustainable business models pursuant to the scalability criterion seems interesting from the cognitive point of view. Today, hybrid organizations are great spaces for building effective and efficient mechanisms for dialogue between business and society. This requires the appropriate business model. The purpose of the paper is to present the conceptualization and operationalization of scalability of sustainable business models that determine the performance of a hybrid organization in the network environment. The paper presents the original concept of applying scalability in sustainable business models with detailed

  14. Final Report: Center for Programming Models for Scalable Parallel Computing

    Energy Technology Data Exchange (ETDEWEB)

    Mellor-Crummey, John [William Marsh Rice University

    2011-09-13

    As part of the Center for Programming Models for Scalable Parallel Computing, Rice University collaborated with project partners in the design, development and deployment of language, compiler, and runtime support for parallel programming models to support application development for the “leadership-class” computer systems at DOE national laboratories. Work over the course of this project has focused on the design, implementation, and evaluation of a second-generation version of Coarray Fortran. Research and development efforts of the project have focused on the CAF 2.0 language, compiler, runtime system, and supporting infrastructure. This has involved working with the teams that provide infrastructure for CAF that we rely on, implementing new language and runtime features, producing an open source compiler that enabled us to evaluate our ideas, and evaluating our design and implementation through the use of benchmarks. The report details the research, development, findings, and conclusions from this work.

  15. Scalable Joint Models for Reliable Uncertainty-Aware Event Prediction.

    Science.gov (United States)

    Soleimani, Hossein; Hensman, James; Saria, Suchi

    2017-08-21

    Missing data and noisy observations pose significant challenges for reliably predicting events from irregularly sampled multivariate time series (longitudinal) data. Imputation methods, which are typically used for completing the data prior to event prediction, lack a principled mechanism to account for the uncertainty due to missingness. Alternatively, state-of-the-art joint modeling techniques can be used for jointly modeling the longitudinal and event data and compute event probabilities conditioned on the longitudinal observations. These approaches, however, make strong parametric assumptions and do not easily scale to multivariate signals with many observations. Our proposed approach consists of several key innovations. First, we develop a flexible and scalable joint model based upon sparse multiple-output Gaussian processes. Unlike state-of-the-art joint models, the proposed model can explain highly challenging structure including non-Gaussian noise while scaling to large data. Second, we derive an optimal policy for predicting events using the distribution of the event occurrence estimated by the joint model. The derived policy trades-off the cost of a delayed detection versus incorrect assessments and abstains from making decisions when the estimated event probability does not satisfy the derived confidence criteria. Experiments on a large dataset show that the proposed framework significantly outperforms state-of-the-art techniques in event prediction.

  16. Developing a scalable modeling architecture for studying survivability technologies

    Science.gov (United States)

    Mohammad, Syed; Bounker, Paul; Mason, James; Brister, Jason; Shady, Dan; Tucker, David

    2006-05-01

    To facilitate interoperability of models in a scalable environment, and provide a relevant virtual environment in which Survivability technologies can be evaluated, the US Army Research Development and Engineering Command (RDECOM) Modeling Architecture for Technology Research and Experimentation (MATREX) Science and Technology Objective (STO) program has initiated the Survivability Thread which will seek to address some of the many technical and programmatic challenges associated with the effort. In coordination with different Thread customers, such as the Survivability branches of various Army labs, a collaborative group has been formed to define the requirements for the simulation environment that would in turn provide them a value-added tool for assessing models and gauge system-level performance relevant to Future Combat Systems (FCS) and the Survivability requirements of other burgeoning programs. An initial set of customer requirements has been generated in coordination with the RDECOM Survivability IPT lead, through the Survivability Technology Area at RDECOM Tank-automotive Research Development and Engineering Center (TARDEC, Warren, MI). The results of this project are aimed at a culminating experiment and demonstration scheduled for September, 2006, which will include a multitude of components from within RDECOM and provide the framework for future experiments to support Survivability research. This paper details the components with which the MATREX Survivability Thread was created and executed, and provides insight into the capabilities currently demanded by the Survivability faculty within RDECOM.

  17. An extended systematic mapping study about the scalability of i* Models

    Directory of Open Access Journals (Sweden)

    Paulo Lima

    2016-12-01

    Full Text Available i* models have been used for requirements specification in many domains, such as healthcare, telecommunication, and air traffic control. Managing the scalability and the complexity of such models is an important challenge in Requirements Engineering (RE. Scalability is also one of the most intractable issues in the design of visual notations in general: a well-known problem with visual representations is that they do not scale well. This issue has led us to investigate scalability in i* models and its variants by means of a systematic mapping study. This paper is an extended version of a previous paper on the scalability of i* including papers indicated by specialists. Moreover, we also discuss the challenges and open issues regarding scalability of i* models and its variants. A total of 126 papers were analyzed in order to understand: how the RE community perceives scalability; and which proposals have considered this topic. We found that scalability issues are indeed perceived as relevant and that further work is still required, even though many potential solutions have already been proposed. This study can be a starting point for researchers aiming to further advance the treatment of scalability in i* models.

  18. Detailed Modeling and Evaluation of a Scalable Multilevel Checkpointing System

    Energy Technology Data Exchange (ETDEWEB)

    Mohror, Kathryn [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Moody, Adam [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Bronevetsky, Greg [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); de Supinski, Bronis R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2014-09-01

    High-performance computing (HPC) systems are growing more powerful by utilizing more components. As the system mean time before failure correspondingly drops, applications must checkpoint frequently to make progress. But, at scale, the cost of checkpointing becomes prohibitive. A solution to this problem is multilevel checkpointing, which employs multiple types of checkpoints in a single run. Moreover, lightweight checkpoints can handle the most common failure modes, while more expensive checkpoints can handle severe failures. We designed a multilevel checkpointing library, the Scalable Checkpoint/Restart (SCR) library, that writes lightweight checkpoints to node-local storage in addition to the parallel file system. We present probabilistic Markov models of SCR's performance. We show that on future large-scale systems, SCR can lead to a gain in machine efficiency of up to 35 percent, and reduce the load on the parallel file system by a factor of two. In addition, we predict that checkpoint scavenging, or only writing checkpoints to the parallel file system on application termination, can reduce the load on the parallel file system by 20 × on today's systems and still maintain high application efficiency.

  19. Efficient Delivery of Scalable Video Using a Streaming Class Model

    Directory of Open Access Journals (Sweden)

    Jason J. Quinlan

    2018-03-01

    Full Text Available When we couple the rise in video streaming with the growing number of portable devices (smart phones, tablets, laptops, we see an ever-increasing demand for high-definition video online while on the move. Wireless networks are inherently characterised by restricted shared bandwidth and relatively high error loss rates, thus presenting a challenge for the efficient delivery of high quality video. Additionally, mobile devices can support/demand a range of video resolutions and qualities. This demand for mobile streaming highlights the need for adaptive video streaming schemes that can adjust to available bandwidth and heterogeneity, and can provide a graceful changes in video quality, all while respecting viewing satisfaction. In this context, the use of well-known scalable/layered media streaming techniques, commonly known as scalable video coding (SVC, is an attractive solution. SVC encodes a number of video quality levels within a single media stream. This has been shown to be an especially effective and efficient solution, but it fares badly in the presence of datagram losses. While multiple description coding (MDC can reduce the effects of packet loss on scalable video delivery, the increased delivery cost is counterproductive for constrained networks. This situation is accentuated in cases where only the lower quality level is required. In this paper, we assess these issues and propose a new approach called Streaming Classes (SC through which we can define a key set of quality levels, each of which can be delivered in a self-contained manner. This facilitates efficient delivery, yielding reduced transmission byte-cost for devices requiring lower quality, relative to MDC and Adaptive Layer Distribution (ALD (42% and 76% respective reduction for layer 2, while also maintaining high levels of consistent quality. We also illustrate how selective packetisation technique can further reduce the effects of packet loss on viewable quality by

  20. A scalable approach to modeling groundwater flow on massively parallel computers

    International Nuclear Information System (INIS)

    Ashby, S.F.; Falgout, R.D.; Tompson, A.F.B.

    1995-12-01

    We describe a fully scalable approach to the simulation of groundwater flow on a hierarchy of computing platforms, ranging from workstations to massively parallel computers. Specifically, we advocate the use of scalable conceptual models in which the subsurface model is defined independently of the computational grid on which the simulation takes place. We also describe a scalable multigrid algorithm for computing the groundwater flow velocities. We axe thus able to leverage both the engineer's time spent developing the conceptual model and the computing resources used in the numerical simulation. We have successfully employed this approach at the LLNL site, where we have run simulations ranging in size from just a few thousand spatial zones (on workstations) to more than eight million spatial zones (on the CRAY T3D)-all using the same conceptual model

  1. Scalable Power-Component Models for Concept Testing

    Science.gov (United States)

    2011-08-17

    motor speed can be either positive or negative dependent upon the propelling or regenerative braking scenario. The simulation provides three...the machine during generation or regenerative braking . To use the model, the user modifies the motor model criteria parameters by double-clicking... SYSTEMS ENGINEERING AND TECHNOLOGY SYMPOSIUM MODELING & SIMULATION, TESTING AND VALIDATION (MSTV) MINI-SYMPOSIUM AUGUST 9-11 DEARBORN, MICHIGAN

  2. Scalable Topic Modeling: Online Learning, Diagnostics, and Recommendation

    Science.gov (United States)

    2017-03-01

    problem of estimating the conditional distribution is a well-defined mathematical problem. Model checking and application again requires the domain...Critique, Repeat: Data Analysis with Latent Variable Models. Annual Review of Statistics and Its Application , 1 203–232, 2014. 2. S. Gershman, D. Blei, K...central statistical and computational problem. 3. With the results of inference, we use our model to form predictions about the future, explore the data, or

  3. Scalable learning of probabilistic latent models for collaborative filtering

    DEFF Research Database (Denmark)

    Langseth, Helge; Nielsen, Thomas Dyhre

    2015-01-01

    variational Bayes learning and inference algorithm for these types of models. Empirical results show that the proposed algorithm achieves significantly better accuracy results than other straw-men models evaluated on a collection of well-known data sets. We also demonstrate that the algorithm has a highly...

  4. Scalable Telemonitoring Model in Cloud for Health Care Analysis

    Science.gov (United States)

    Sawant, Yogesh; Jayakumar, Naveenkumar, Dr.; Pawar, Sanket Sunil

    2017-08-01

    Telemonitoring model is health observations model that going to surveillance patients remotely. Telemonitoring model is suitable for patients to avoid high operating expense to get Emergency treatment. Telemonitoring gives the path for monitoring the medical device that generates a complete profile of patient’s health through assembling essential signs as well as additional health information. Telemonitoring model is relying on four differential modules which is capable to generate realistic synthetic electrocardiogram (ECG) signals. Telemonitoring model shows four categories of chronic disease: pulmonary state, diabetes, hypertension, as well as cardiovascular diseases. On the other hand, the results of this application model recommend facilitating despite of their nationality, socioeconomic grade, or age, patients observe amid tele-monitoring programs as well as the utilization of technologies. Patient’s multiple health status is shown in the result such as beat-to-beat variation in morphology and timing of the human ECG, including QT dispersion and R-peak amplitude modulation. This model will be utilized to evaluate biomedical signal processing methods that are utilized to calculate clinical information from the ECG.

  5. Advances in Intelligent Modelling and Simulation Artificial Intelligence-Based Models and Techniques in Scalable Computing

    CERN Document Server

    Khan, Samee; Burczy´nski, Tadeusz

    2012-01-01

    One of the most challenging issues in today’s large-scale computational modeling and design is to effectively manage the complex distributed environments, such as computational clouds, grids, ad hoc, and P2P networks operating under  various  types of users with evolving relationships fraught with  uncertainties. In this context, the IT resources and services usually belong to different owners (institutions, enterprises, or individuals) and are managed by different administrators. Moreover, uncertainties are presented to the system at hand in various forms of information that are incomplete, imprecise, fragmentary, or overloading, which hinders in the full and precise resolve of the evaluation criteria, subsequencing and selection, and the assignment scores. Intelligent scalable systems enable the flexible routing and charging, advanced user interactions and the aggregation and sharing of geographically-distributed resources in modern large-scale systems.   This book presents new ideas, theories, models...

  6. Model Transport: Towards Scalable Transfer Learning on Manifolds

    DEFF Research Database (Denmark)

    Freifeld, Oren; Hauberg, Søren; Black, Michael J.

    2014-01-01

    We consider the intersection of two research fields: transfer learning and statistics on manifolds. In particular, we consider, for manifold-valued data, transfer learning of tangent-space models such as Gaussians distributions, PCA, regression, or classifiers. Though one would hope to simply use...... ordinary Rn-transfer learning ideas, the manifold structure prevents it. We overcome this by basing our method on inner-product-preserving parallel transport, a well-known tool widely used in other problems of statistics on manifolds in computer vision. At first, this straightforward idea seems to suffer...... “commutes” with learning. Consequently, our compact framework, applicable to a large class of manifolds, is not restricted by the size of either the training or test sets. We demonstrate the approach by transferring PCA and logistic-regression models of real-world data involving 3D shapes and image...

  7. Scalable and Robust BDDC Preconditioners for Reservoir and Electromagnetics Modeling

    KAUST Repository

    Zampini, S.; Widlund, O.B.; Keyes, David E.

    2015-01-01

    The purpose of the study is to show the effectiveness of recent algorithmic advances in Balancing Domain Decomposition by Constraints (BDDC) preconditioners for the solution of elliptic PDEs with highly heterogeneous coefficients, and discretized by means of the finite element method. Applications to large linear systems generated by div- and curl- conforming finite elements discretizations commonly arising in the contexts of modelling reservoirs and electromagnetics will be presented.

  8. Scalable and Robust BDDC Preconditioners for Reservoir and Electromagnetics Modeling

    KAUST Repository

    Zampini, S.

    2015-09-13

    The purpose of the study is to show the effectiveness of recent algorithmic advances in Balancing Domain Decomposition by Constraints (BDDC) preconditioners for the solution of elliptic PDEs with highly heterogeneous coefficients, and discretized by means of the finite element method. Applications to large linear systems generated by div- and curl- conforming finite elements discretizations commonly arising in the contexts of modelling reservoirs and electromagnetics will be presented.

  9. A veracity preserving model for synthesizing scalable electricity load profiles

    OpenAIRE

    Huang, Yunyou; Zhan, Jianfeng; Luo, Chunjie; Wang, Lei; Wang, Nana; Zheng, Daoyi; Fan, Fanda; Ren, Rui

    2018-01-01

    Electricity users are the major players of the electric systems, and electricity consumption is growing at an extraordinary rate. The research on electricity consumption behaviors is becoming increasingly important to design and deployment of the electric systems. Unfortunately, electricity load profiles are difficult to acquire. Data synthesis is one of the best approaches to solving the lack of data, and the key is the model that preserves the real electricity consumption behaviors. In this...

  10. Scalable Database Design of End-Game Model with Decoupled Countermeasure and Threat Information

    Science.gov (United States)

    2017-11-01

    the Army Modular Active Protection System (MAPS) program to provide end-to-end APS modeling and simulation capabilities. The SSES simulation features...research project of scalable database design was initiated in support of SSES modularization efforts with respect to 4 major software components...Iron Curtain KE kinetic energy MAPS Modular Active Protective System OLE DB object linking and embedding database RDB relational database RPG

  11. Spatiotemporal Stochastic Modeling of IoT Enabled Cellular Networks: Scalability and Stability Analysis

    KAUST Repository

    Gharbieh, Mohammad; Elsawy, Hesham; Bader, Ahmed; Alouini, Mohamed-Slim

    2017-01-01

    The Internet of Things (IoT) is large-scale by nature, which is manifested by the massive number of connected devices as well as their vast spatial existence. Cellular networks, which provide ubiquitous, reliable, and efficient wireless access, will play fundamental rule in delivering the first-mile access for the data tsunami to be generated by the IoT. However, cellular networks may have scalability problems to provide uplink connectivity to massive numbers of connected things. To characterize the scalability of cellular uplink in the context of IoT networks, this paper develops a traffic-aware spatiotemporal mathematical model for IoT devices supported by cellular uplink connectivity. The developed model is based on stochastic geometry and queueing theory to account for the traffic requirement per IoT device, the different transmission strategies, and the mutual interference between the IoT devices. To this end, the developed model is utilized to characterize the extent to which cellular networks can accommodate IoT traffic as well as to assess and compare three different transmission strategies that incorporate a combination of transmission persistency, backoff, and power-ramping. The analysis and the results clearly illustrate the scalability problem imposed by IoT on cellular network and offer insights into effective scenarios for each transmission strategy.

  12. Spatiotemporal Stochastic Modeling of IoT Enabled Cellular Networks: Scalability and Stability Analysis

    KAUST Repository

    Gharbieh, Mohammad

    2017-05-02

    The Internet of Things (IoT) is large-scale by nature, which is manifested by the massive number of connected devices as well as their vast spatial existence. Cellular networks, which provide ubiquitous, reliable, and efficient wireless access, will play fundamental rule in delivering the first-mile access for the data tsunami to be generated by the IoT. However, cellular networks may have scalability problems to provide uplink connectivity to massive numbers of connected things. To characterize the scalability of cellular uplink in the context of IoT networks, this paper develops a traffic-aware spatiotemporal mathematical model for IoT devices supported by cellular uplink connectivity. The developed model is based on stochastic geometry and queueing theory to account for the traffic requirement per IoT device, the different transmission strategies, and the mutual interference between the IoT devices. To this end, the developed model is utilized to characterize the extent to which cellular networks can accommodate IoT traffic as well as to assess and compare three different transmission strategies that incorporate a combination of transmission persistency, backoff, and power-ramping. The analysis and the results clearly illustrate the scalability problem imposed by IoT on cellular network and offer insights into effective scenarios for each transmission strategy.

  13. A scalable variational inequality approach for flow through porous media models with pressure-dependent viscosity

    Science.gov (United States)

    Mapakshi, N. K.; Chang, J.; Nakshatrala, K. B.

    2018-04-01

    Mathematical models for flow through porous media typically enjoy the so-called maximum principles, which place bounds on the pressure field. It is highly desirable to preserve these bounds on the pressure field in predictive numerical simulations, that is, one needs to satisfy discrete maximum principles (DMP). Unfortunately, many of the existing formulations for flow through porous media models do not satisfy DMP. This paper presents a robust, scalable numerical formulation based on variational inequalities (VI), to model non-linear flows through heterogeneous, anisotropic porous media without violating DMP. VI is an optimization technique that places bounds on the numerical solutions of partial differential equations. To crystallize the ideas, a modification to Darcy equations by taking into account pressure-dependent viscosity will be discretized using the lowest-order Raviart-Thomas (RT0) and Variational Multi-scale (VMS) finite element formulations. It will be shown that these formulations violate DMP, and, in fact, these violations increase with an increase in anisotropy. It will be shown that the proposed VI-based formulation provides a viable route to enforce DMP. Moreover, it will be shown that the proposed formulation is scalable, and can work with any numerical discretization and weak form. A series of numerical benchmark problems are solved to demonstrate the effects of heterogeneity, anisotropy and non-linearity on DMP violations under the two chosen formulations (RT0 and VMS), and that of non-linearity on solver convergence for the proposed VI-based formulation. Parallel scalability on modern computational platforms will be illustrated through strong-scaling studies, which will prove the efficiency of the proposed formulation in a parallel setting. Algorithmic scalability as the problem size is scaled up will be demonstrated through novel static-scaling studies. The performed static-scaling studies can serve as a guide for users to be able to select

  14. A Scalable Version of the Navy Operational Global Atmospheric Prediction System Spectral Forecast Model

    Directory of Open Access Journals (Sweden)

    Thomas E. Rosmond

    2000-01-01

    Full Text Available The Navy Operational Global Atmospheric Prediction System (NOGAPS includes a state-of-the-art spectral forecast model similar to models run at several major operational numerical weather prediction (NWP centers around the world. The model, developed by the Naval Research Laboratory (NRL in Monterey, California, has run operational at the Fleet Numerical Meteorological and Oceanographic Center (FNMOC since 1982, and most recently is being run on a Cray C90 in a multi-tasked configuration. Typically the multi-tasked code runs on 10 to 15 processors with overall parallel efficiency of about 90%. resolution is T159L30, but other operational and research applications run at significantly lower resolutions. A scalable NOGAPS forecast model has been developed by NRL in anticipation of a FNMOC C90 replacement in about 2001, as well as for current NOGAPS research requirements to run on DOD High-Performance Computing (HPC scalable systems. The model is designed to run with message passing (MPI. Model design criteria include bit reproducibility for different processor numbers and reasonably efficient performance on fully shared memory, distributed memory, and distributed shared memory systems for a wide range of model resolutions. Results for a wide range of processor numbers, model resolutions, and different vendor architectures are presented. Single node performance has been disappointing on RISC based systems, at least compared to vector processor performance. This is a common complaint, and will require careful re-examination of traditional numerical weather prediction (NWP model software design and data organization to fully exploit future scalable architectures.

  15. SciSpark: Highly Interactive and Scalable Model Evaluation and Climate Metrics for Scientific Data and Analysis

    Data.gov (United States)

    National Aeronautics and Space Administration — We will construct SciSpark, a scalable system for interactive model evaluation and for the rapid development of climate metrics and analyses. SciSpark directly...

  16. Monte Carlo tests of the Rasch model based on scalability coefficients

    DEFF Research Database (Denmark)

    Christensen, Karl Bang; Kreiner, Svend

    2010-01-01

    that summarizes the number of Guttman errors in the data matrix. These coefficients are shown to yield efficient tests of the Rasch model using p-values computed using Markov chain Monte Carlo methods. The power of the tests of unequal item discrimination, and their ability to distinguish between local dependence......For item responses fitting the Rasch model, the assumptions underlying the Mokken model of double monotonicity are met. This makes non-parametric item response theory a natural starting-point for Rasch item analysis. This paper studies scalability coefficients based on Loevinger's H coefficient...

  17. More scalability, less pain: A simple programming model and its implementation for extreme computing

    International Nuclear Information System (INIS)

    Lusk, E.L.; Pieper, S.C.; Butler, R.M.

    2010-01-01

    This is the story of a simple programming model, its implementation for extreme computing, and a breakthrough in nuclear physics. A critical issue for the future of high-performance computing is the programming model to use on next-generation architectures. Described here is a promising approach: program very large machines by combining a simplified programming model with a scalable library implementation. The presentation takes the form of a case study in nuclear physics. The chosen application addresses fundamental issues in the origins of our Universe, while the library developed to enable this application on the largest computers may have applications beyond this one.

  18. A framework for scalable parameter estimation of gene circuit models using structural information

    KAUST Repository

    Kuwahara, Hiroyuki

    2013-06-21

    Motivation: Systematic and scalable parameter estimation is a key to construct complex gene regulatory models and to ultimately facilitate an integrative systems biology approach to quantitatively understand the molecular mechanisms underpinning gene regulation. Results: Here, we report a novel framework for efficient and scalable parameter estimation that focuses specifically on modeling of gene circuits. Exploiting the structure commonly found in gene circuit models, this framework decomposes a system of coupled rate equations into individual ones and efficiently integrates them separately to reconstruct the mean time evolution of the gene products. The accuracy of the parameter estimates is refined by iteratively increasing the accuracy of numerical integration using the model structure. As a case study, we applied our framework to four gene circuit models with complex dynamics based on three synthetic datasets and one time series microarray data set. We compared our framework to three state-of-the-art parameter estimation methods and found that our approach consistently generated higher quality parameter solutions efficiently. Although many general-purpose parameter estimation methods have been applied for modeling of gene circuits, our results suggest that the use of more tailored approaches to use domain-specific information may be a key to reverse engineering of complex biological systems. The Author 2013.

  19. A framework for scalable parameter estimation of gene circuit models using structural information

    KAUST Repository

    Kuwahara, Hiroyuki; Fan, Ming; Wang, Suojin; Gao, Xin

    2013-01-01

    Motivation: Systematic and scalable parameter estimation is a key to construct complex gene regulatory models and to ultimately facilitate an integrative systems biology approach to quantitatively understand the molecular mechanisms underpinning gene regulation. Results: Here, we report a novel framework for efficient and scalable parameter estimation that focuses specifically on modeling of gene circuits. Exploiting the structure commonly found in gene circuit models, this framework decomposes a system of coupled rate equations into individual ones and efficiently integrates them separately to reconstruct the mean time evolution of the gene products. The accuracy of the parameter estimates is refined by iteratively increasing the accuracy of numerical integration using the model structure. As a case study, we applied our framework to four gene circuit models with complex dynamics based on three synthetic datasets and one time series microarray data set. We compared our framework to three state-of-the-art parameter estimation methods and found that our approach consistently generated higher quality parameter solutions efficiently. Although many general-purpose parameter estimation methods have been applied for modeling of gene circuits, our results suggest that the use of more tailored approaches to use domain-specific information may be a key to reverse engineering of complex biological systems. The Author 2013.

  20. A framework for scalable parameter estimation of gene circuit models using structural information.

    Science.gov (United States)

    Kuwahara, Hiroyuki; Fan, Ming; Wang, Suojin; Gao, Xin

    2013-07-01

    Systematic and scalable parameter estimation is a key to construct complex gene regulatory models and to ultimately facilitate an integrative systems biology approach to quantitatively understand the molecular mechanisms underpinning gene regulation. Here, we report a novel framework for efficient and scalable parameter estimation that focuses specifically on modeling of gene circuits. Exploiting the structure commonly found in gene circuit models, this framework decomposes a system of coupled rate equations into individual ones and efficiently integrates them separately to reconstruct the mean time evolution of the gene products. The accuracy of the parameter estimates is refined by iteratively increasing the accuracy of numerical integration using the model structure. As a case study, we applied our framework to four gene circuit models with complex dynamics based on three synthetic datasets and one time series microarray data set. We compared our framework to three state-of-the-art parameter estimation methods and found that our approach consistently generated higher quality parameter solutions efficiently. Although many general-purpose parameter estimation methods have been applied for modeling of gene circuits, our results suggest that the use of more tailored approaches to use domain-specific information may be a key to reverse engineering of complex biological systems. http://sfb.kaust.edu.sa/Pages/Software.aspx. Supplementary data are available at Bioinformatics online.

  1. geoKepler Workflow Module for Computationally Scalable and Reproducible Geoprocessing and Modeling

    Science.gov (United States)

    Cowart, C.; Block, J.; Crawl, D.; Graham, J.; Gupta, A.; Nguyen, M.; de Callafon, R.; Smarr, L.; Altintas, I.

    2015-12-01

    The NSF-funded WIFIRE project has developed an open-source, online geospatial workflow platform for unifying geoprocessing tools and models for for fire and other geospatially dependent modeling applications. It is a product of WIFIRE's objective to build an end-to-end cyberinfrastructure for real-time and data-driven simulation, prediction and visualization of wildfire behavior. geoKepler includes a set of reusable GIS components, or actors, for the Kepler Scientific Workflow System (https://kepler-project.org). Actors exist for reading and writing GIS data in formats such as Shapefile, GeoJSON, KML, and using OGC web services such as WFS. The actors also allow for calling geoprocessing tools in other packages such as GDAL and GRASS. Kepler integrates functions from multiple platforms and file formats into one framework, thus enabling optimal GIS interoperability, model coupling, and scalability. Products of the GIS actors can be fed directly to models such as FARSITE and WRF. Kepler's ability to schedule and scale processes using Hadoop and Spark also makes geoprocessing ultimately extensible and computationally scalable. The reusable workflows in geoKepler can be made to run automatically when alerted by real-time environmental conditions. Here, we show breakthroughs in the speed of creating complex data for hazard assessments with this platform. We also demonstrate geoKepler workflows that use Data Assimilation to ingest real-time weather data into wildfire simulations, and for data mining techniques to gain insight into environmental conditions affecting fire behavior. Existing machine learning tools and libraries such as R and MLlib are being leveraged for this purpose in Kepler, as well as Kepler's Distributed Data Parallel (DDP) capability to provide a framework for scalable processing. geoKepler workflows can be executed via an iPython notebook as a part of a Jupyter hub at UC San Diego for sharing and reporting of the scientific analysis and results from

  2. Investigation of the blockchain systems’ scalability features using the agent based modelling

    OpenAIRE

    Šulnius, Aleksas

    2017-01-01

    Investigation of the BlockChain Systems’ Scalability Features using the Agent Based Modelling. BlockChain currently is in the spotlight of all the FinTech industry. This technology is being called revolutionary, ground breaking, disruptive and even the WEB 3.0. On the other hand it is widely agreed that the BlockChain is in its early stages of development. In its current state BlockChain is in similar position that the Internet was in the early nineties. In order for this technology to gain m...

  3. LoRa Scalability: A Simulation Model Based on Interference Measurements

    Directory of Open Access Journals (Sweden)

    Jetmir Haxhibeqiri

    2017-05-01

    Full Text Available LoRa is a long-range, low power, low bit rate and single-hop wireless communication technology. It is intended to be used in Internet of Things (IoT applications involving battery-powered devices with low throughput requirements. A LoRaWAN network consists of multiple end nodes that communicate with one or more gateways. These gateways act like a transparent bridge towards a common network server. The amount of end devices and their throughput requirements will have an impact on the performance of the LoRaWAN network. This study investigates the scalability in terms of the number of end devices per gateway of single-gateway LoRaWAN deployments. First, we determine the intra-technology interference behavior with two physical end nodes, by checking the impact of an interfering node on a transmitting node. Measurements show that even under concurrent transmission, one of the packets can be received under certain conditions. Based on these measurements, we create a simulation model for assessing the scalability of a single gateway LoRaWAN network. We show that when the number of nodes increases up to 1000 per gateway, the losses will be up to 32%. In such a case, pure Aloha will have around 90% losses. However, when the duty cycle of the application layer becomes lower than the allowed radio duty cycle of 1%, losses will be even lower. We also show network scalability simulation results for some IoT use cases based on real data.

  4. LoRa Scalability: A Simulation Model Based on Interference Measurements.

    Science.gov (United States)

    Haxhibeqiri, Jetmir; Van den Abeele, Floris; Moerman, Ingrid; Hoebeke, Jeroen

    2017-05-23

    LoRa is a long-range, low power, low bit rate and single-hop wireless communication technology. It is intended to be used in Internet of Things (IoT) applications involving battery-powered devices with low throughput requirements. A LoRaWAN network consists of multiple end nodes that communicate with one or more gateways. These gateways act like a transparent bridge towards a common network server. The amount of end devices and their throughput requirements will have an impact on the performance of the LoRaWAN network. This study investigates the scalability in terms of the number of end devices per gateway of single-gateway LoRaWAN deployments. First, we determine the intra-technology interference behavior with two physical end nodes, by checking the impact of an interfering node on a transmitting node. Measurements show that even under concurrent transmission, one of the packets can be received under certain conditions. Based on these measurements, we create a simulation model for assessing the scalability of a single gateway LoRaWAN network. We show that when the number of nodes increases up to 1000 per gateway, the losses will be up to 32%. In such a case, pure Aloha will have around 90% losses. However, when the duty cycle of the application layer becomes lower than the allowed radio duty cycle of 1%, losses will be even lower. We also show network scalability simulation results for some IoT use cases based on real data.

  5. Progress Report 2008: A Scalable and Extensible Earth System Model for Climate Change Science

    Energy Technology Data Exchange (ETDEWEB)

    Drake, John B [ORNL; Worley, Patrick H [ORNL; Hoffman, Forrest M [ORNL; Jones, Phil [Los Alamos National Laboratory (LANL)

    2009-01-01

    This project employs multi-disciplinary teams to accelerate development of the Community Climate System Model (CCSM), based at the National Center for Atmospheric Research (NCAR). A consortium of eight Department of Energy (DOE) National Laboratories collaborate with NCAR and the NASA Global Modeling and Assimilation Office (GMAO). The laboratories are Argonne (ANL), Brookhaven (BNL) Los Alamos (LANL), Lawrence Berkeley (LBNL), Lawrence Livermore (LLNL), Oak Ridge (ORNL), Pacific Northwest (PNNL) and Sandia (SNL). The work plan focuses on scalablity for petascale computation and extensibility to a more comprehensive earth system model. Our stated goal is to support the DOE mission in climate change research by helping ... To determine the range of possible climate changes over the 21st century and beyond through simulations using a more accurate climate system model that includes the full range of human and natural climate feedbacks with increased realism and spatial resolution.

  6. Scalability of the muscular action in a parametric 3D model of the index finger.

    Science.gov (United States)

    Sancho-Bru, Joaquín L; Vergara, Margarita; Rodríguez-Cervantes, Pablo-Jesús; Giurintano, David J; Pérez-González, Antonio

    2008-01-01

    A method for scaling the muscle action is proposed and used to achieve a 3D inverse dynamic model of the human finger with all its components scalable. This method is based on scaling the physiological cross-sectional area (PCSA) in a Hill muscle model. Different anthropometric parameters and maximal grip force data have been measured and their correlations have been analyzed and used for scaling the PCSA of each muscle. A linear relationship between the normalized PCSA and the product of the length and breadth of the hand has been finally used for scaling, with a slope of 0.01315 cm(-2), with the length and breadth of the hand expressed in centimeters. The parametric muscle model has been included in a parametric finger model previously developed by the authors, and it has been validated reproducing the results of an experiment in which subjects from different population groups exerted maximal voluntary forces with their index finger in a controlled posture.

  7. Scalability of Several Asynchronous Many-Task Models for In Situ Statistical Analysis.

    Energy Technology Data Exchange (ETDEWEB)

    Pebay, Philippe Pierre [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Bennett, Janine Camille [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Kolla, Hemanth [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Borghesi, Giulio [Sandia National Lab. (SNL-CA), Livermore, CA (United States)

    2017-05-01

    This report is a sequel to [PB16], in which we provided a first progress report on research and development towards a scalable, asynchronous many-task, in situ statistical analysis engine using the Legion runtime system. This earlier work included a prototype implementation of a proposed solution, using a proxy mini-application as a surrogate for a full-scale scientific simulation code. The first scalability studies were conducted with the above on modestly-sized experimental clusters. In contrast, in the current work we have integrated our in situ analysis engines with a full-size scientific application (S3D, using the Legion-SPMD model), and have conducted nu- merical tests on the largest computational platform currently available for DOE science ap- plications. We also provide details regarding the design and development of a light-weight asynchronous collectives library. We describe how this library is utilized within our SPMD- Legion S3D workflow, and compare the data aggregation technique deployed herein to the approach taken within our previous work.

  8. Model-Based Evaluation Of System Scalability: Bandwidth Analysis For Smartphone-Based Biosensing Applications

    DEFF Research Database (Denmark)

    Patou, François; Madsen, Jan; Dimaki, Maria

    2016-01-01

    Scalability is a design principle often valued for the engineering of complex systems. Scalability is the ability of a system to change the current value of one of its specification parameters. Although targeted frameworks are available for the evaluation of scalability for specific digital systems...... re-engineering of 5 independent system modules, from the replacement of a wireless Bluetooth interface, to the revision of the ADC sample-and-hold operation could help increase system bandwidth....

  9. Performance and scalability of finite-difference and finite-element wave-propagation modeling on Intel's Xeon Phi

    NARCIS (Netherlands)

    Zhebel, E.; Minisini, S.; Kononov, A.; Mulder, W.A.

    2013-01-01

    With the rapid developments in parallel compute architectures, algorithms for seismic modeling and imaging need to be reconsidered in terms of parallelization. The aim of this paper is to compare scalability of seismic modeling algorithms: finite differences, continuous mass-lumped finite elements

  10. A conclusive scalable model for the complete actuation response for IPMC transducers

    International Nuclear Information System (INIS)

    McDaid, A J; Aw, K C; Haemmerle, E; Xie, S Q

    2010-01-01

    This paper proposes a conclusive scalable model for the complete actuation response for ionic polymer metal composites (IPMC). This single model is proven to be able to accurately predict the free displacement/velocity and force actuation at varying displacements, with up to 3 V inputs. An accurate dynamic relationship between the force and displacement has been established which can be used to predict the complete actuation response of the IPMC transducer. The model is accurate at large displacements and can also predict the response when interacting with external mechanical systems and loads. This model equips engineers with a useful design tool which enables simple mechanical design, simulation and optimization when integrating IPMC actuators into an application. The response of the IPMC is modelled in three stages: (i) a nonlinear equivalent electrical circuit to predict the current drawn, (ii) an electromechanical coupling term and (iii) a segmented mechanical beam model which includes an electrically induced torque for the polymer. Model parameters are obtained using the dynamic time response and results are presented demonstrating the correspondence between the model and experimental results over a large operating range. This newly developed model is a large step forward, aiding in the progression of IPMCs towards wide acceptance as replacements to traditional actuators

  11. NYU3T: teaching, technology, teamwork: a model for interprofessional education scalability and sustainability.

    Science.gov (United States)

    Djukic, Maja; Fulmer, Terry; Adams, Jennifer G; Lee, Sabrina; Triola, Marc M

    2012-09-01

    Interprofessional education is a critical precursor to effective teamwork and the collaboration of health care professionals in clinical settings. Numerous barriers have been identified that preclude scalable and sustainable interprofessional education (IPE) efforts. This article describes NYU3T: Teaching, Technology, Teamwork, a model that uses novel technologies such as Web-based learning, virtual patients, and high-fidelity simulation to overcome some of the common barriers and drive implementation of evidence-based teamwork curricula. It outlines the program's curricular components, implementation strategy, evaluation methods, and lessons learned from the first year of delivery and describes implications for future large-scale IPE initiatives. Copyright © 2012 Elsevier Inc. All rights reserved.

  12. Working towards a scalable model of problem-based learning instruction in undergraduate engineering education

    Science.gov (United States)

    Mantri, Archana

    2014-05-01

    The intent of the study presented in this paper is to show that the model of problem-based learning (PBL) can be made scalable by designing curriculum around a set of open-ended problems (OEPs). The detailed statistical analysis of the data collected to measure the effects of traditional and PBL instructions for three courses in Electronics and Communication Engineering, namely Analog Electronics, Digital Electronics and Pulse, Digital & Switching Circuits is presented here. It measures the effects of pedagogy, gender and cognitive styles on the knowledge, skill and attitude of the students. The study was conducted two times with content designed around same set of OEPs but with two different trained facilitators for all the three courses. The repeatability of results for effects of the independent parameters on dependent parameters is studied and inferences are drawn.

  13. Scalable devices

    KAUST Repository

    Krü ger, Jens J.; Hadwiger, Markus

    2014-01-01

    In computer science in general and in particular the field of high performance computing and supercomputing the term scalable plays an important role. It indicates that a piece of hardware, a concept, an algorithm, or an entire system scales

  14. Scalability of Semi-Implicit Time Integrators for Nonhydrostatic Galerkin-based Atmospheric Models on Large Scale Cluster

    Science.gov (United States)

    2011-01-01

    present performance statistics to explain the scalability behavior. Keywords-atmospheric models, time intergrators , MPI, scal- ability, performance; I...across inter-element bound- aries. Basis functions are constructed as tensor products of Lagrange polynomials ψi (x) = hα(ξ) ⊗ hβ(η) ⊗ hγ(ζ)., where hα

  15. Fast and Scalable Gaussian Process Modeling with Applications to Astronomical Time Series

    Science.gov (United States)

    Foreman-Mackey, Daniel; Agol, Eric; Ambikasaran, Sivaram; Angus, Ruth

    2017-12-01

    The growing field of large-scale time domain astronomy requires methods for probabilistic data analysis that are computationally tractable, even with large data sets. Gaussian processes (GPs) are a popular class of models used for this purpose, but since the computational cost scales, in general, as the cube of the number of data points, their application has been limited to small data sets. In this paper, we present a novel method for GPs modeling in one dimension where the computational requirements scale linearly with the size of the data set. We demonstrate the method by applying it to simulated and real astronomical time series data sets. These demonstrations are examples of probabilistic inference of stellar rotation periods, asteroseismic oscillation spectra, and transiting planet parameters. The method exploits structure in the problem when the covariance function is expressed as a mixture of complex exponentials, without requiring evenly spaced observations or uniform noise. This form of covariance arises naturally when the process is a mixture of stochastically driven damped harmonic oscillators—providing a physical motivation for and interpretation of this choice—but we also demonstrate that it can be a useful effective model in some other cases. We present a mathematical description of the method and compare it to existing scalable GP methods. The method is fast and interpretable, with a range of potential applications within astronomical data analysis and beyond. We provide well-tested and documented open-source implementations of this method in C++, Python, and Julia.

  16. Approaches for scalable modeling and emulation of cyber systems : LDRD final report.

    Energy Technology Data Exchange (ETDEWEB)

    Mayo, Jackson R.; Minnich, Ronald G.; Armstrong, Robert C.; Rudish, Don W.

    2009-09-01

    The goal of this research was to combine theoretical and computational approaches to better understand the potential emergent behaviors of large-scale cyber systems, such as networks of {approx} 10{sup 6} computers. The scale and sophistication of modern computer software, hardware, and deployed networked systems have significantly exceeded the computational research community's ability to understand, model, and predict current and future behaviors. This predictive understanding, however, is critical to the development of new approaches for proactively designing new systems or enhancing existing systems with robustness to current and future cyber threats, including distributed malware such as botnets. We have developed preliminary theoretical and modeling capabilities that can ultimately answer questions such as: How would we reboot the Internet if it were taken down? Can we change network protocols to make them more secure without disrupting existing Internet connectivity and traffic flow? We have begun to address these issues by developing new capabilities for understanding and modeling Internet systems at scale. Specifically, we have addressed the need for scalable network simulation by carrying out emulations of a network with {approx} 10{sup 6} virtualized operating system instances on a high-performance computing cluster - a 'virtual Internet'. We have also explored mappings between previously studied emergent behaviors of complex systems and their potential cyber counterparts. Our results provide foundational capabilities for further research toward understanding the effects of complexity in cyber systems, to allow anticipating and thwarting hackers.

  17. Scalable devices

    KAUST Repository

    Krüger, Jens J.

    2014-01-01

    In computer science in general and in particular the field of high performance computing and supercomputing the term scalable plays an important role. It indicates that a piece of hardware, a concept, an algorithm, or an entire system scales with the size of the problem, i.e., it can not only be used in a very specific setting but it\\'s applicable for a wide range of problems. From small scenarios to possibly very large settings. In this spirit, there exist a number of fixed areas of research on scalability. There are works on scalable algorithms, scalable architectures but what are scalable devices? In the context of this chapter, we are interested in a whole range of display devices, ranging from small scale hardware such as tablet computers, pads, smart-phones etc. up to large tiled display walls. What interests us mostly is not so much the hardware setup but mostly the visualization algorithms behind these display systems that scale from your average smart phone up to the largest gigapixel display walls.

  18. Scalable approximate policies for Markov decision process models of hospital elective admissions.

    Science.gov (United States)

    Zhu, George; Lizotte, Dan; Hoey, Jesse

    2014-05-01

    To demonstrate the feasibility of using stochastic simulation methods for the solution of a large-scale Markov decision process model of on-line patient admissions scheduling. The problem of admissions scheduling is modeled as a Markov decision process in which the states represent numbers of patients using each of a number of resources. We investigate current state-of-the-art real time planning methods to compute solutions to this Markov decision process. Due to the complexity of the model, traditional model-based planners are limited in scalability since they require an explicit enumeration of the model dynamics. To overcome this challenge, we apply sample-based planners along with efficient simulation techniques that given an initial start state, generate an action on-demand while avoiding portions of the model that are irrelevant to the start state. We also propose a novel variant of a popular sample-based planner that is particularly well suited to the elective admissions problem. Results show that the stochastic simulation methods allow for the problem size to be scaled by a factor of almost 10 in the action space, and exponentially in the state space. We have demonstrated our approach on a problem with 81 actions, four specialities and four treatment patterns, and shown that we can generate solutions that are near-optimal in about 100s. Sample-based planners are a viable alternative to state-based planners for large Markov decision process models of elective admissions scheduling. Copyright © 2014 Elsevier B.V. All rights reserved.

  19. Scalable rule-based modelling of allosteric proteins and biochemical networks.

    Directory of Open Access Journals (Sweden)

    Julien F Ollivier

    2010-11-01

    Full Text Available Much of the complexity of biochemical networks comes from the information-processing abilities of allosteric proteins, be they receptors, ion-channels, signalling molecules or transcription factors. An allosteric protein can be uniquely regulated by each combination of input molecules that it binds. This "regulatory complexity" causes a combinatorial increase in the number of parameters required to fit experimental data as the number of protein interactions increases. It therefore challenges the creation, updating, and re-use of biochemical models. Here, we propose a rule-based modelling framework that exploits the intrinsic modularity of protein structure to address regulatory complexity. Rather than treating proteins as "black boxes", we model their hierarchical structure and, as conformational changes, internal dynamics. By modelling the regulation of allosteric proteins through these conformational changes, we often decrease the number of parameters required to fit data, and so reduce over-fitting and improve the predictive power of a model. Our method is thermodynamically grounded, imposes detailed balance, and also includes molecular cross-talk and the background activity of enzymes. We use our Allosteric Network Compiler to examine how allostery can facilitate macromolecular assembly and how competitive ligands can change the observed cooperativity of an allosteric protein. We also develop a parsimonious model of G protein-coupled receptors that explains functional selectivity and can predict the rank order of potency of agonists acting through a receptor. Our methodology should provide a basis for scalable, modular and executable modelling of biochemical networks in systems and synthetic biology.

  20. A Scalable and Extensible Earth System Model for Climate Change Science

    Energy Technology Data Exchange (ETDEWEB)

    Gent, Peter; Lamarque, Jean-Francois; Conley, Andrew; Vertenstein, Mariana; Craig, Anthony

    2013-02-13

    The objective of this award was to build a scalable and extensible Earth System Model that can be used to study climate change science. That objective has been achieved with the public release of the Community Earth System Model, version 1 (CESM1). In particular, the development of the CESM1 atmospheric chemistry component was substantially funded by this award, as was the development of the significantly improved coupler component. The CESM1 allows new climate change science in areas such as future air quality in very large cities, the effects of recovery of the southern hemisphere ozone hole, and effects of runoff from ice melt in the Greenland and Antarctic ice sheets. Results from a whole series of future climate projections using the CESM1 are also freely available via the web from the CMIP5 archive at the Lawrence Livermore National Laboratory. Many research papers using these results have now been published, and will form part of the 5th Assessment Report of the United Nations Intergovernmental Panel on Climate Change, which is to be published late in 2013.

  1. A scalable infrastructure model for carbon capture and storage: SimCCS

    International Nuclear Information System (INIS)

    Middleton, Richard S.; Bielicki, Jeffrey M.

    2009-01-01

    In the carbon capture and storage (CCS) process, CO 2 sources and geologic reservoirs may be widely spatially dispersed and need to be connected through a dedicated CO 2 pipeline network. We introduce a scalable infrastructure model for CCS (simCCS) that generates a fully integrated, cost-minimizing CCS system. SimCCS determines where and how much CO 2 to capture and store, and where to build and connect pipelines of different sizes, in order to minimize the combined annualized costs of sequestering a given amount of CO 2 . SimCCS is able to aggregate CO 2 flows between sources and reservoirs into trunk pipelines that take advantage of economies of scale. Pipeline construction costs take into account factors including topography and social impacts. SimCCS can be used to calculate the scale of CCS deployment (local, regional, national). SimCCS' deployment of a realistic, capacitated pipeline network is a major advancement for planning CCS infrastructure. We demonstrate simCCS using a set of 37 CO 2 sources and 14 reservoirs for California. The results highlight the importance of systematic planning for CCS infrastructure by examining the sensitivity of CCS infrastructure, as optimized by simCCS, to varying CO 2 targets. We finish by identifying critical future research areas for CCS infrastructure

  2. Scalable Nonlinear Solvers for Fully Implicit Coupled Nuclear Fuel Modeling. Final Report

    International Nuclear Information System (INIS)

    Cai, Xiao-Chuan; Yang, Chao; Pernice, Michael

    2014-01-01

    The focus of the project is on the development and customization of some highly scalable domain decomposition based preconditioning techniques for the numerical solution of nonlinear, coupled systems of partial differential equations (PDEs) arising from nuclear fuel simulations. These high-order PDEs represent multiple interacting physical fields (for example, heat conduction, oxygen transport, solid deformation), each is modeled by a certain type of Cahn-Hilliard and/or Allen-Cahn equations. Most existing approaches involve a careful splitting of the fields and the use of field-by-field iterations to obtain a solution of the coupled problem. Such approaches have many advantages such as ease of implementation since only single field solvers are needed, but also exhibit disadvantages. For example, certain nonlinear interactions between the fields may not be fully captured, and for unsteady problems, stable time integration schemes are difficult to design. In addition, when implemented on large scale parallel computers, the sequential nature of the field-by-field iterations substantially reduces the parallel efficiency. To overcome the disadvantages, fully coupled approaches have been investigated in order to obtain full physics simulations.

  3. Salvus: A scalable software suite for full-waveform modelling & inversion

    Science.gov (United States)

    Afanasiev, M.; Boehm, C.; van Driel, M.; Krischer, L.; Fichtner, A.

    2017-12-01

    Full-waveform inversion (FWI), whether at the lab, exploration, or planetary scale, requires the cooperation of five principal components. (1) The geometry of the domain needs to be properly discretized and an initial guess of the model parameters must be projected onto it; (2) Large volumes of recorded waveform data must be collected, organized, and processed; (3) Synthetic waveform data must be efficiently and accurately computed through complex domains; (4) Suitable misfit functions and optimization techniques must be used to relate discrepancies in data space to perturbations in the model; and (5) Some form of workflow management must be employed to schedule and run (1) - (4) in the correct order. Each one of these components can represent a formidable technical challenge which redirects energy from the true task at hand: using FWI to extract new information about some underlying continuum.In this presentation we give an overview of the current status of the Salvus software suite, which was introduced to address the challenges listed above. Specifically, we touch on (1) salvus_mesher, which eases the discretization of complex Earth models into hexahedral meshes; (2) salvus_seismo, which integrates with LASIF and ObsPy to streamline the processing and preparation of seismic data; (3) salvus_wave, a high-performance and scalable spectral-element solver capable of simulating waveforms through general unstructured 2- and 3-D domains, and (4) salvus_opt, an optimization toolbox specifically designed for full-waveform inverse problems. Tying everything together, we also discuss (5) salvus_flow: a workflow package designed to orchestrate and manage the rest of the suite. It is our hope that these developments represent a step towards the automation of large-scale seismic waveform inversion, while also lowering the barrier of entry for new applications. We include several examples of Salvus' use in (extra-) planetary seismology, non-destructive testing, and medical

  4. A scalable and deformable stylized model of the adult human eye for radiation dose assessment.

    Science.gov (United States)

    El Basha, Daniel; Furuta, Takuya; Iyer, Siva S R; Bolch, Wesley E

    2018-03-23

    With recent changes in the recommended annual limit on eye lens exposures to ionizing radiation, there is considerable interest in predictive computational dosimetry models of the human eye and its various ocular structures including the crystalline lens, ciliary body, cornea, retina, optic nerve, and central retinal artery. Computational eye models to date have been constructed as stylized models, high-resolution voxel models, and polygon mesh models. Their common feature, however, is that they are typically constructed of nominal size and of a roughly spherical shape associated with the emmetropic eye. In this study, we present a geometric eye model that is both scalable (allowing for changes in eye size) and deformable (allowing for changes in eye shape), and that is suitable for use in radiation transport studies of ocular exposures and radiation treatments of eye disease. The model allows continuous and variable changes in eye size (axial lengths from 20 to 26 mm) and eye shape (diopters from -12 to +6). As an explanatory example of its use, five models (emmetropic eyes of small, average, and large size, as well as average size eyes of -12D and +6D) were constructed and subjected to normally incident beams of monoenergetic electrons and photons, with resultant energy-dependent dose coefficients presented for both anterior and posterior eye structures. Electron dose coefficients were found to vary with changes to both eye size and shape for the posterior eye structures, while their values for the eye crystalline lens were found to be sensitive to changes in only eye size. No dependence upon eye size or eye shape was found for photon dose coefficients at energies below 2 MeV. Future applications of the model can include more extensive tabulations of dose coefficients to all ocular structures (not only the lens) as a function of eye size and shape, as well as the assessment of x-ray therapies for ocular disease for patients with non-emmetropic eyes. © 2018

  5. A scalable and deformable stylized model of the adult human eye for radiation dose assessment

    Science.gov (United States)

    El Basha, Daniel; Furuta, Takuya; Iyer, Siva S. R.; Bolch, Wesley E.

    2018-05-01

    With recent changes in the recommended annual limit on eye lens exposures to ionizing radiation, there is considerable interest in predictive computational dosimetry models of the human eye and its various ocular structures including the crystalline lens, ciliary body, cornea, retina, optic nerve, and central retinal artery. Computational eye models to date have been constructed as stylized models, high-resolution voxel models, and polygon mesh models. Their common feature, however, is that they are typically constructed of nominal size and of a roughly spherical shape associated with the emmetropic eye. In this study, we present a geometric eye model that is both scalable (allowing for changes in eye size) and deformable (allowing for changes in eye shape), and that is suitable for use in radiation transport studies of ocular exposures and radiation treatments of eye disease. The model allows continuous and variable changes in eye size (axial lengths from 20 to 26 mm) and eye shape (diopters from  ‑12 to  +6). As an explanatory example of its use, five models (emmetropic eyes of small, average, and large size, as well as average size eyes of  ‑12D and  +6D) were constructed and subjected to normally incident beams of monoenergetic electrons and photons, with resultant energy-dependent dose coefficients presented for both anterior and posterior eye structures. Electron dose coefficients were found to vary with changes to both eye size and shape for the posterior eye structures, while their values for the crystalline lens were found to be sensitive to changes in only eye size. No dependence upon eye size or eye shape was found for photon dose coefficients at energies below 2 MeV. Future applications of the model can include more extensive tabulations of dose coefficients to all ocular structures (not only the lens) as a function of eye size and shape, as well as the assessment of x-ray therapies for ocular disease for patients with non

  6. Durango: Scalable Synthetic Workload Generation for Extreme-Scale Application Performance Modeling and Simulation

    Energy Technology Data Exchange (ETDEWEB)

    Carothers, Christopher D. [Rensselaer Polytechnic Institute (RPI); Meredith, Jeremy S. [ORNL; Blanco, Marc [Rensselaer Polytechnic Institute (RPI); Vetter, Jeffrey S. [ORNL; Mubarak, Misbah [Argonne National Laboratory; LaPre, Justin [Rensselaer Polytechnic Institute (RPI); Moore, Shirley V. [ORNL

    2017-05-01

    Performance modeling of extreme-scale applications on accurate representations of potential architectures is critical for designing next generation supercomputing systems because it is impractical to construct prototype systems at scale with new network hardware in order to explore designs and policies. However, these simulations often rely on static application traces that can be difficult to work with because of their size and lack of flexibility to extend or scale up without rerunning the original application. To address this problem, we have created a new technique for generating scalable, flexible workloads from real applications, we have implemented a prototype, called Durango, that combines a proven analytical performance modeling language, Aspen, with the massively parallel HPC network modeling capabilities of the CODES framework.Our models are compact, parameterized and representative of real applications with computation events. They are not resource intensive to create and are portable across simulator environments. We demonstrate the utility of Durango by simulating the LULESH application in the CODES simulation environment on several topologies and show that Durango is practical to use for simulation without loss of fidelity, as quantified by simulation metrics. During our validation of Durango's generated communication model of LULESH, we found that the original LULESH miniapp code had a latent bug where the MPI_Waitall operation was used incorrectly. This finding underscores the potential need for a tool such as Durango, beyond its benefits for flexible workload generation and modeling.Additionally, we demonstrate the efficacy of Durango's direct integration approach, which links Aspen into CODES as part of the running network simulation model. Here, Aspen generates the application-level computation timing events, which in turn drive the start of a network communication phase. Results show that Durango's performance scales well when

  7. A Scalable Cloud Library Empowering Big Data Management, Diagnosis, and Visualization of Cloud-Resolving Models

    Science.gov (United States)

    Zhou, S.; Tao, W. K.; Li, X.; Matsui, T.; Sun, X. H.; Yang, X.

    2015-12-01

    A cloud-resolving model (CRM) is an atmospheric numerical model that can numerically resolve clouds and cloud systems at 0.25~5km horizontal grid spacings. The main advantage of the CRM is that it can allow explicit interactive processes between microphysics, radiation, turbulence, surface, and aerosols without subgrid cloud fraction, overlapping and convective parameterization. Because of their fine resolution and complex physical processes, it is challenging for the CRM community to i) visualize/inter-compare CRM simulations, ii) diagnose key processes for cloud-precipitation formation and intensity, and iii) evaluate against NASA's field campaign data and L1/L2 satellite data products due to large data volume (~10TB) and complexity of CRM's physical processes. We have been building the Super Cloud Library (SCL) upon a Hadoop framework, capable of CRM database management, distribution, visualization, subsetting, and evaluation in a scalable way. The current SCL capability includes (1) A SCL data model enables various CRM simulation outputs in NetCDF, including the NASA-Unified Weather Research and Forecasting (NU-WRF) and Goddard Cumulus Ensemble (GCE) model, to be accessed and processed by Hadoop, (2) A parallel NetCDF-to-CSV converter supports NU-WRF and GCE model outputs, (3) A technique visualizes Hadoop-resident data with IDL, (4) A technique subsets Hadoop-resident data, compliant to the SCL data model, with HIVE or Impala via HUE's Web interface, (5) A prototype enables a Hadoop MapReduce application to dynamically access and process data residing in a parallel file system, PVFS2 or CephFS, where high performance computing (HPC) simulation outputs such as NU-WRF's and GCE's are located. We are testing Apache Spark to speed up SCL data processing and analysis.With the SCL capabilities, SCL users can conduct large-domain on-demand tasks without downloading voluminous CRM datasets and various observations from NASA Field Campaigns and Satellite data to a

  8. Modeling, Fabrication and Characterization of Scalable Electroless Gold Plated Nanostructures for Enhanced Surface Plasmon Resonance

    Science.gov (United States)

    Jang, Gyoung Gug

    The scientific and industrial demand for controllable thin gold (Au) film and Au nanostructures is increasing in many fields including opto-electronics, photovoltaics, MEMS devices, diagnostics, bio-molecular sensors, spectro-/microscopic surfaces and probes. In this study, a novel continuous flow electroless (CF-EL) Au plating method is developed to fabricate uniform Au thin films in ambient condition. The enhanced local mass transfer rate and continuous deposition resulting from CF-EL plating improved physical uniformity of deposited Au films and thermally transformed nanoparticles (NPs). Au films and NPs exhibited improved optical photoluminescence (PL) and surface plasmon resonance (SPR), respectively, relative to batch immersion EL (BI-EL) plating. Suggested mass transfer models of Au mole deposition are consistent with optical feature of CF-EL and BI-EL films. The prototype CF-EL plating system is upgraded an automated scalable CF-EL plating system with real-time transmission UV-vis (T-UV) spectroscopy which provides the advantage of CF-EL plating, such as more uniform surface morphology, and overcomes the disadvantages of conventional EL plating, such as no continuous process and low deposition rate, using continuous process and controllable deposition rate. Throughout this work, dynamic morphological and chemical transitions during redox-driven self-assembly of Ag and Au film on silica surfaces under kinetic and equilibrium conditions are distinguished by correlating real-time T-UV spectroscopy with X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM) measurements. The characterization suggests that four previously unrecognized time-dependent physicochemical regimes occur during consecutive EL deposition of silver (Ag) and Au onto tin-sensitized silica surfaces: self-limiting Ag activation; transitory Ag NP formation; transitional Au-Ag alloy formation during galvanic replacement of Ag by Au; and uniform morphology formation under

  9. Scalable coherent interface

    International Nuclear Information System (INIS)

    Alnaes, K.; Kristiansen, E.H.; Gustavson, D.B.; James, D.V.

    1990-01-01

    The Scalable Coherent Interface (IEEE P1596) is establishing an interface standard for very high performance multiprocessors, supporting a cache-coherent-memory model scalable to systems with up to 64K nodes. This Scalable Coherent Interface (SCI) will supply a peak bandwidth per node of 1 GigaByte/second. The SCI standard should facilitate assembly of processor, memory, I/O and bus bridge cards from multiple vendors into massively parallel systems with throughput far above what is possible today. The SCI standard encompasses two levels of interface, a physical level and a logical level. The physical level specifies electrical, mechanical and thermal characteristics of connectors and cards that meet the standard. The logical level describes the address space, data transfer protocols, cache coherence mechanisms, synchronization primitives and error recovery. In this paper we address logical level issues such as packet formats, packet transmission, transaction handshake, flow control, and cache coherence. 11 refs., 10 figs

  10. Optimized bit extraction using distortion modeling in the scalable extension of H.264/AVC.

    Science.gov (United States)

    Maani, Ehsan; Katsaggelos, Aggelos K

    2009-09-01

    The newly adopted scalable extension of H.264/AVC video coding standard (SVC) demonstrates significant improvements in coding efficiency in addition to an increased degree of supported scalability relative to the scalable profiles of prior video coding standards. Due to the complicated hierarchical prediction structure of the SVC and the concept of key pictures, content-aware rate adaptation of SVC bit streams to intermediate bit rates is a nontrivial task. The concept of quality layers has been introduced in the design of the SVC to allow for fast content-aware prioritized rate adaptation. However, existing quality layer assignment methods are suboptimal and do not consider all network abstraction layer (NAL) units from different layers for the optimization. In this paper, we first propose a technique to accurately and efficiently estimate the quality degradation resulting from discarding an arbitrary number of NAL units from multiple layers of a bitstream by properly taking drift into account. Then, we utilize this distortion estimation technique to assign quality layers to NAL units for a more efficient extraction. Experimental results show that a significant gain can be achieved by the proposed scheme.

  11. Component-Based Modelling for Scalable Smart City Systems Interoperability: A Case Study on Integrating Energy Demand Response Systems.

    Science.gov (United States)

    Palomar, Esther; Chen, Xiaohong; Liu, Zhiming; Maharjan, Sabita; Bowen, Jonathan

    2016-10-28

    Smart city systems embrace major challenges associated with climate change, energy efficiency, mobility and future services by embedding the virtual space into a complex cyber-physical system. Those systems are constantly evolving and scaling up, involving a wide range of integration among users, devices, utilities, public services and also policies. Modelling such complex dynamic systems' architectures has always been essential for the development and application of techniques/tools to support design and deployment of integration of new components, as well as for the analysis, verification, simulation and testing to ensure trustworthiness. This article reports on the definition and implementation of a scalable component-based architecture that supports a cooperative energy demand response (DR) system coordinating energy usage between neighbouring households. The proposed architecture, called refinement of Cyber-Physical Component Systems (rCPCS), which extends the refinement calculus for component and object system (rCOS) modelling method, is implemented using Eclipse Extensible Coordination Tools (ECT), i.e., Reo coordination language. With rCPCS implementation in Reo, we specify the communication, synchronisation and co-operation amongst the heterogeneous components of the system assuring, by design scalability and the interoperability, correctness of component cooperation.

  12. Center for Programming Models for Scalable Parallel Computing - Towards Enhancing OpenMP for Manycore and Heterogeneous Nodes

    Energy Technology Data Exchange (ETDEWEB)

    Barbara Chapman

    2012-02-01

    OpenMP was not well recognized at the beginning of the project, around year 2003, because of its limited use in DoE production applications and the inmature hardware support for an efficient implementation. Yet in the recent years, it has been graduately adopted both in HPC applications, mostly in the form of MPI+OpenMP hybrid code, and in mid-scale desktop applications for scientific and experimental studies. We have observed this trend and worked deligiently to improve our OpenMP compiler and runtimes, as well as to work with the OpenMP standard organization to make sure OpenMP are evolved in the direction close to DoE missions. In the Center for Programming Models for Scalable Parallel Computing project, the HPCTools team at the University of Houston (UH), directed by Dr. Barbara Chapman, has been working with project partners, external collaborators and hardware vendors to increase the scalability and applicability of OpenMP for multi-core (and future manycore) platforms and for distributed memory systems by exploring different programming models, language extensions, compiler optimizations, as well as runtime library support.

  13. Use of modeling to assess the scalability of Ethernet networks for the ATLAS second level trigger

    CERN Document Server

    Korcyl, K; Dobinson, Robert W; Saka, F

    1999-01-01

    The second level trigger of LHC's ATLAS experiment has to perform real-time analyses on detector data at 10 GBytes/s. A switching network is required to connect more than thousand read-out buffers to about thousand processors that execute the trigger algorithm. We are investigating the use of Ethernet technology to build this large switching network. Ethernet is attractive because of the huge installed base, competitive prices, and recent introduction of the high-performance Gigabit version. Due to the network's size it has to be constructed as a layered structure of smaller units. To assess the scalability of such a structure we evaluated a single switch unit. (0 refs).

  14. Operationalizing the Reciprocal Engagement Model of Genetic Counseling Practice: a Framework for the Scalable Delivery of Genomic Counseling and Testing.

    Science.gov (United States)

    Schmidlen, Tara; Sturm, Amy C; Hovick, Shelly; Scheinfeldt, Laura; Scott Roberts, J; Morr, Lindsey; McElroy, Joseph; Toland, Amanda E; Christman, Michael; O'Daniel, Julianne M; Gordon, Erynn S; Bernhardt, Barbara A; Ormond, Kelly E; Sweet, Kevin

    2018-02-19

    With the advent of widespread genomic testing for diagnostic indications and disease risk assessment, there is increased need to optimize genetic counseling services to support the scalable delivery of precision medicine. Here, we describe how we operationalized the reciprocal engagement model of genetic counseling practice to develop a framework of counseling components and strategies for the delivery of genomic results. This framework was constructed based upon qualitative research with patients receiving genomic counseling following online receipt of potentially actionable complex disease and pharmacogenomics reports. Consultation with a transdisciplinary group of investigators, including practicing genetic counselors, was sought to ensure broad scope and applicability of these strategies for use with any large-scale genomic testing effort. We preserve the provision of pre-test education and informed consent as established in Mendelian/single-gene disease genetic counseling practice. Following receipt of genomic results, patients are afforded the opportunity to tailor the counseling agenda by selecting the specific test results they wish to discuss, specifying questions for discussion, and indicating their preference for counseling modality. The genetic counselor uses these patient preferences to set the genomic counseling session and to personalize result communication and risk reduction recommendations. Tailored visual aids and result summary reports divide areas of risk (genetic variant, family history, lifestyle) for each disease to facilitate discussion of multiple disease risks. Post-counseling, session summary reports are actively routed to both the patient and their physician team to encourage review and follow-up. Given the breadth of genomic information potentially resulting from genomic testing, this framework is put forth as a starting point to meet the need for scalable genetic counseling services in the delivery of precision medicine.

  15. Genetic algorithms and genetic programming for multiscale modeling: Applications in materials science and chemistry and advances in scalability

    Science.gov (United States)

    Sastry, Kumara Narasimha

    2007-03-01

    building blocks in organic chemistry---indicate that MOGAs produce High-quality semiempirical methods that (1) are stable to small perturbations, (2) yield accurate configuration energies on untested and critical excited states, and (3) yield ab initio quality excited-state dynamics. The proposed method enables simulations of more complex systems to realistic, multi-picosecond timescales, well beyond previous attempts or expectation of human experts, and 2--3 orders-of-magnitude reduction in computational cost. While the two applications use simple evolutionary operators, in order to tackle more complex systems, their scalability and limitations have to be investigated. The second part of the thesis addresses some of the challenges involved with a successful design of genetic algorithms and genetic programming for multiscale modeling. The first issue addressed is the scalability of genetic programming, where facetwise models are built to assess the population size required by GP to ensure adequate supply of raw building blocks and also to ensure accurate decision-making between competing building blocks. This study also presents a design of competent genetic programming, where traditional fixed recombination operators are replaced by building and sampling probabilistic models of promising candidate programs. The proposed scalable GP, called extended compact GP (eCGP), combines the ideas from extended compact genetic algorithm (eCGA) and probabilistic incremental program evolution (PIPE) and adaptively identifies, propagates and exchanges important subsolutions of a search problem. Results show that eCGP scales cubically with problem size on both GP-easy and GP-hard problems. Finally, facetwise models are developed to explore limitations of scalability of MOGAs, where the scalability of multiobjective algorithms in reliably maintaining Pareto-optimal solutions is addressed. The results show that even when the building blocks are accurately identified, massive multimodality

  16. Scalable Coupling of Multiscale AEH and PARADYN Analyses for Impact Modeling

    National Research Council Canada - National Science Library

    Valisetty, Rama R; Chung, Peter W; Namburu, Raju R

    2005-01-01

    .... An asymptotic expansion homogenization (AEH)-based microstructural model available for modeling microstructural aspects of modern armor materials is coupled with PARADYN, a parallel explicit Lagrangian finite-element code...

  17. Scalability Modeling for Optimal Provisioning of Data Centers in Telenor: A better balance between under- and over-provisioning

    OpenAIRE

    Rygg, Knut Helge

    2012-01-01

    The scalability of an information system describes the relationship between system ca-pacity and system size. This report studies the scalability of Microsoft Lync Server 2010 in order to provide guidelines for provisioning hardware resources. Optimal pro-visioning is required to reduce both deployment and operational costs, while keeping an acceptable service quality.All Lync servers in the test setup are virtualizedusingVMware ESXi 5.0 and the system runs on a Cisco Unified Computing System...

  18. Scalable geocomputation: evolving an environmental model building platform from single-core to supercomputers

    Science.gov (United States)

    Schmitz, Oliver; de Jong, Kor; Karssenberg, Derek

    2017-04-01

    There is an increasing demand to run environmental models on a big scale: simulations over large areas at high resolution. The heterogeneity of available computing hardware such as multi-core CPUs, GPUs or supercomputer potentially provides significant computing power to fulfil this demand. However, this requires detailed knowledge of the underlying hardware, parallel algorithm design and the implementation thereof in an efficient system programming language. Domain scientists such as hydrologists or ecologists often lack this specific software engineering knowledge, their emphasis is (and should be) on exploratory building and analysis of simulation models. As a result, models constructed by domain specialists mostly do not take full advantage of the available hardware. A promising solution is to separate the model building activity from software engineering by offering domain specialists a model building framework with pre-programmed building blocks that they combine to construct a model. The model building framework, consequently, needs to have built-in capabilities to make full usage of the available hardware. Developing such a framework providing understandable code for domain scientists and being runtime efficient at the same time poses several challenges on developers of such a framework. For example, optimisations can be performed on individual operations or the whole model, or tasks need to be generated for a well-balanced execution without explicitly knowing the complexity of the domain problem provided by the modeller. Ideally, a modelling framework supports the optimal use of available hardware whichsoever combination of model building blocks scientists use. We demonstrate our ongoing work on developing parallel algorithms for spatio-temporal modelling and demonstrate 1) PCRaster, an environmental software framework (http://www.pcraster.eu) providing spatio-temporal model building blocks and 2) parallelisation of about 50 of these building blocks using

  19. HYDROSCAPE: A SCAlable and ParallelizablE Rainfall Runoff Model for Hydrological Applications

    Science.gov (United States)

    Piccolroaz, S.; Di Lazzaro, M.; Zarlenga, A.; Majone, B.; Bellin, A.; Fiori, A.

    2015-12-01

    In this work we present HYDROSCAPE, an innovative streamflow routing method based on the travel time approach, and modeled through a fine-scale geomorphological description of hydrological flow paths. The model is designed aimed at being easily coupled with weather forecast or climate models providing the hydrological forcing, and at the same time preserving the geomorphological dispersion of the river network, which is kept unchanged independently on the grid size of rainfall input. This makes HYDROSCAPE particularly suitable for multi-scale applications, ranging from medium size catchments up to the continental scale, and to investigate the effects of extreme rainfall events that require an accurate description of basin response timing. Key feature of the model is its computational efficiency, which allows performing a large number of simulations for sensitivity/uncertainty analyses in a Monte Carlo framework. Further, the model is highly parsimonious, involving the calibration of only three parameters: one defining the residence time of hillslope response, one for channel velocity, and a multiplicative factor accounting for uncertainties in the identification of the potential maximum soil moisture retention in the SCS-CN method. HYDROSCAPE is designed with a simple and flexible modular structure, which makes it particularly prone to massive parallelization, customization according to the specific user needs and preferences (e.g., rainfall-runoff model), and continuous development and improvement. Finally, the possibility to specify the desired computational time step and evaluate streamflow at any location in the domain, makes HYDROSCAPE an attractive tool for many hydrological applications, and a valuable alternative to more complex and highly parametrized large scale hydrological models. Together with model development and features, we present an application to the Upper Tiber River basin (Italy), providing a practical example of model performance and

  20. A model based message passing approach for flexible and scalable home automation controllers

    Energy Technology Data Exchange (ETDEWEB)

    Bienhaus, D. [INNIAS GmbH und Co. KG, Frankenberg (Germany); David, K.; Klein, N.; Kroll, D. [ComTec Kassel Univ., SE Kassel Univ. (Germany); Heerdegen, F.; Jubeh, R.; Zuendorf, A. [Kassel Univ. (Germany). FG Software Engineering; Hofmann, J. [BSC Computer GmbH, Allendorf (Germany)

    2012-07-01

    There is a large variety of home automation systems that are largely proprietary systems from different vendors. In addition, the configuration and administration of home automation systems is frequently a very complex task especially, if more complex functionality shall be achieved. Therefore, an open model for home automation was developed that is especially designed for easy integration of various home automation systems. This solution also provides a simple modeling approach that is inspired by typical home automation components like switches, timers, etc. In addition, a model based technology to achieve rich functionality and usability was implemented. (orig.)

  1. Investigating the Role of Biogeochemical Processes in the Northern High Latitudes on Global Climate Feedbacks Using an Efficient Scalable Earth System Model

    Energy Technology Data Exchange (ETDEWEB)

    Jain, Atul K. [Univ. of Illinois, Urbana-Champaign, IL (United States)

    2016-09-14

    The overall objectives of this DOE funded project is to combine scientific and computational challenges in climate modeling by expanding our understanding of the biogeophysical-biogeochemical processes and their interactions in the northern high latitudes (NHLs) using an earth system modeling (ESM) approach, and by adopting an adaptive parallel runtime system in an ESM to achieve efficient and scalable climate simulations through improved load balancing algorithms.

  2. A scalable community detection algorithm for large graphs using stochastic block models

    KAUST Repository

    Peng, Chengbin

    2017-11-24

    Community detection in graphs is widely used in social and biological networks, and the stochastic block model is a powerful probabilistic tool for describing graphs with community structures. However, in the era of

  3. A scalable community detection algorithm for large graphs using stochastic block models

    KAUST Repository

    Peng, Chengbin; Zhang, Zhihua; Wong, Ka-Chun; Zhang, Xiangliang; Keyes, David E.

    2017-01-01

    Community detection in graphs is widely used in social and biological networks, and the stochastic block model is a powerful probabilistic tool for describing graphs with community structures. However, in the era of

  4. Scalability on LHS (Latin Hypercube Sampling) samples for use in uncertainty analysis of large numerical models

    International Nuclear Information System (INIS)

    Baron, Jorge H.; Nunez Mac Leod, J.E.

    2000-01-01

    The present paper deals with the utilization of advanced sampling statistical methods to perform uncertainty and sensitivity analysis on numerical models. Such models may represent physical phenomena, logical structures (such as boolean expressions) or other systems, and various of their intrinsic parameters and/or input variables are usually treated as random variables simultaneously. In the present paper a simple method to scale-up Latin Hypercube Sampling (LHS) samples is presented, starting with a small sample and duplicating its size at each step, making it possible to use the already run numerical model results with the smaller sample. The method does not distort the statistical properties of the random variables and does not add any bias to the samples. The results is a significant reduction in numerical models running time can be achieved (by re-using the previously run samples), keeping all the advantages of LHS, until an acceptable representation level is achieved in the output variables. (author)

  5. Sustainability and scalability of university spinouts:a business model perspective

    OpenAIRE

    Ziaee Bigdeli, Ali; Li, Feng; Shi, Xiaohui

    2015-01-01

    Most previous studies of university spinouts (USOs) have focused on what determines their formation from the perspectives of the entrepreneurs or of their parent universities. However, few studies have investigated how these entrepreneurial businesses actually grow and how their business models evolve in the process. This paper examines the evolution of USOs' business models over their different development phases. Using empirical evidence gathered from three comprehensive case studies, we ex...

  6. Fast, Automated, Scalable Generation of Textured 3D Models of Indoor Environments

    Science.gov (United States)

    2014-12-18

    throughs of environments, gaming entertainment, augmented reality , indoor navigation, and energy simulation analysis. These applications rely on the...models are used in virtual reality , gaming, navigation, and simulation applica- tions. State-of-the-art scanning produces accurate point-clouds of...meshes that remove furniture and other temporary objects. We propose a method to texture-map these models from captured camera imagery to produce

  7. Scalable and Accurate SMT-Based Model Checking of Data Flow Systems

    Science.gov (United States)

    2013-10-31

    of variable x is always less than that of variable y) can be represented in this theory. • A theory of inductive datatypes . Modeling software... datatypes can be done directly in this theory. • A theory of arrays. Software that uses arrays can be modeled with constraints in this theory, as can...Arithmetic (and specialized fragments) Arrays Inductive datatypes Bit-vectors Uninterpreted functions SMT Engine Input interfaces FEATURES Support for

  8. PATHLOGIC-S: a scalable Boolean framework for modelling cellular signalling.

    Directory of Open Access Journals (Sweden)

    Liam G Fearnley

    Full Text Available Curated databases of signal transduction have grown to describe several thousand reactions, and efficient use of these data requires the development of modelling tools to elucidate and explore system properties. We present PATHLOGIC-S, a Boolean specification for a signalling model, with its associated GPL-licensed implementation using integer programming techniques. The PATHLOGIC-S specification has been designed to function on current desktop workstations, and is capable of providing analyses on some of the largest currently available datasets through use of Boolean modelling techniques to generate predictions of stable and semi-stable network states from data in community file formats. PATHLOGIC-S also addresses major problems associated with the presence and modelling of inhibition in Boolean systems, and reduces logical incoherence due to common inhibitory mechanisms in signalling systems. We apply this approach to signal transduction networks including Reactome and two pathways from the Panther Pathways database, and present the results of computations on each along with a discussion of execution time. A software implementation of the framework and model is freely available under a GPL license.

  9. Scalable Bayesian nonparametric regression via a Plackett-Luce model for conditional ranks

    Science.gov (United States)

    Gray-Davies, Tristan; Holmes, Chris C.; Caron, François

    2018-01-01

    We present a novel Bayesian nonparametric regression model for covariates X and continuous response variable Y ∈ ℝ. The model is parametrized in terms of marginal distributions for Y and X and a regression function which tunes the stochastic ordering of the conditional distributions F (y|x). By adopting an approximate composite likelihood approach, we show that the resulting posterior inference can be decoupled for the separate components of the model. This procedure can scale to very large datasets and allows for the use of standard, existing, software from Bayesian nonparametric density estimation and Plackett-Luce ranking estimation to be applied. As an illustration, we show an application of our approach to a US Census dataset, with over 1,300,000 data points and more than 100 covariates. PMID:29623150

  10. A scalable delivery framework and a pricing model for streaming media with advertisements

    Science.gov (United States)

    Al-Hadrusi, Musab; Sarhan, Nabil J.

    2008-01-01

    This paper presents a delivery framework for streaming media with advertisements and an associated pricing model. The delivery model combines the benefits of periodic broadcasting and stream merging. The advertisements' revenues are used to subsidize the price of the media content. The pricing is determined based on the total ads' viewing time. Moreover, this paper presents an efficient ad allocation scheme and three modified scheduling policies that are well suited to the proposed delivery framework. Furthermore, we study the effectiveness of the delivery framework and various scheduling polices through extensive simulation in terms of numerous metrics, including customer defection probability, average number of ads viewed per client, price, arrival rate, profit, and revenue.

  11. A Scalable Approach to Modeling Cascading Risk in the MDAP Network

    Science.gov (United States)

    2014-05-01

    Populate Decision Process Model. • Identify challenges to data acquisition. Legend: ATIE_MOD Automated Text & Image  Extraction Module  IID_MOD...8217:~ TI ~.O.Y <D1Y o:yle-~Jti<NI:Aboolate:tos>:J14 : lert•tl ::J!i <DtV o; vlc "~’"""’al>oolote:tos~: 3l4: 1•tt:t’l...DAES, PE docs, SARS – Topic models built from MDAP hub data seem to be relevant to neighbors. – Challenges : Formatting and Content inconsistencies

  12. Chiefly Symmetric: Results on the Scalability of Probabilistic Model Checking for Operating-System Code

    Directory of Open Access Journals (Sweden)

    Marcus Völp

    2012-11-01

    Full Text Available Reliability in terms of functional properties from the safety-liveness spectrum is an indispensable requirement of low-level operating-system (OS code. However, with evermore complex and thus less predictable hardware, quantitative and probabilistic guarantees become more and more important. Probabilistic model checking is one technique to automatically obtain these guarantees. First experiences with the automated quantitative analysis of low-level operating-system code confirm the expectation that the naive probabilistic model checking approach rapidly reaches its limits when increasing the numbers of processes. This paper reports on our work-in-progress to tackle the state explosion problem for low-level OS-code caused by the exponential blow-up of the model size when the number of processes grows. We studied the symmetry reduction approach and carried out our experiments with a simple test-and-test-and-set lock case study as a representative example for a wide range of protocols with natural inter-process dependencies and long-run properties. We quickly see a state-space explosion for scenarios where inter-process dependencies are insignificant. However, once inter-process dependencies dominate the picture models with hundred and more processes can be constructed and analysed.

  13. An experimental investigation for scalability of the seismic response of microconcrete model nuclear power plant structures

    International Nuclear Information System (INIS)

    Bennett, J.G.; Dove, R.C.; Dunwoody, W.E.; Farrar, C.R.

    1987-01-01

    The paper reports the results from tests including reduced stiffnesses found in the prototype and 1/4 scale model, implications of the test results on the validity of past tests, and implications of these results from the 1986 tests on the seismic behavior of actual Seismic Category I Structures and their attached equipment. (orig./HP)

  14. Developmental Impact Analysis of an ICT-Enabled Scalable Healthcare Model in BRICS Economies

    Directory of Open Access Journals (Sweden)

    Dhrubes Biswas

    2012-06-01

    Full Text Available This article highlights the need for initiating a healthcare business model in a grassroots, emerging-nation context. This article’s backdrop is a history of chronic anomalies afflicting the healthcare sector in India and similarly placed BRICS nations. In these countries, a significant percentage of populations remain deprived of basic healthcare facilities and emergency services. Community (primary care services are being offered by public and private stakeholders as a panacea to the problem. Yet, there is an urgent need for specialized (tertiary care services at all levels. As a response to this challenge, an all-inclusive health-exchange system (HES model, which utilizes information communication technology (ICT to provide solutions in rural India, has been developed. The uniqueness of the model lies in its innovative hub-and-spoke architecture and its emphasis on affordability, accessibility, and availability to the masses. This article describes a developmental impact analysis (DIA that was used to assess the impact of this model. The article contributes to the knowledge base of readers by making them aware of the healthcare challenges emerging nations are facing and ways to mitigate those challenges using entrepreneurial solutions.

  15. Non parametric, self organizing, scalable modeling of spatiotemporal inputs: the sign language paradigm.

    Science.gov (United States)

    Caridakis, G; Karpouzis, K; Drosopoulos, A; Kollias, S

    2012-12-01

    Modeling and recognizing spatiotemporal, as opposed to static input, is a challenging task since it incorporates input dynamics as part of the problem. The vast majority of existing methods tackle the problem as an extension of the static counterpart, using dynamics, such as input derivatives, at feature level and adopting artificial intelligence and machine learning techniques originally designed for solving problems that do not specifically address the temporal aspect. The proposed approach deals with temporal and spatial aspects of the spatiotemporal domain in a discriminative as well as coupling manner. Self Organizing Maps (SOM) model the spatial aspect of the problem and Markov models its temporal counterpart. Incorporation of adjacency, both in training and classification, enhances the overall architecture with robustness and adaptability. The proposed scheme is validated both theoretically, through an error propagation study, and experimentally, on the recognition of individual signs, performed by different, native Greek Sign Language users. Results illustrate the architecture's superiority when compared to Hidden Markov Model techniques and variations both in terms of classification performance and computational cost. Copyright © 2012 Elsevier Ltd. All rights reserved.

  16. Deep Potential Molecular Dynamics: A Scalable Model with the Accuracy of Quantum Mechanics

    Science.gov (United States)

    Zhang, Linfeng; Han, Jiequn; Wang, Han; Car, Roberto; E, Weinan

    2018-04-01

    We introduce a scheme for molecular simulations, the deep potential molecular dynamics (DPMD) method, based on a many-body potential and interatomic forces generated by a carefully crafted deep neural network trained with ab initio data. The neural network model preserves all the natural symmetries in the problem. It is first-principles based in the sense that there are no ad hoc components aside from the network model. We show that the proposed scheme provides an efficient and accurate protocol in a variety of systems, including bulk materials and molecules. In all these cases, DPMD gives results that are essentially indistinguishable from the original data, at a cost that scales linearly with system size.

  17. Helicopter model rotor-blade vortex interaction impulsive noise: Scalability and parametric variations

    Science.gov (United States)

    Splettstoesser, W. R.; Schultz, K. J.; Boxwell, D. A.; Schmitz, F. H.

    1984-01-01

    Acoustic data taken in the anechoic Deutsch-Niederlaendischer Windkanal (DNW) have documented the blade vortex interaction (BVI) impulsive noise radiated from a 1/7-scale model main rotor of the AH-1 series helicopter. Averaged model scale data were compared with averaged full scale, inflight acoustic data under similar nondimensional test conditions. At low advance ratios (mu = 0.164 to 0.194), the data scale remarkable well in level and waveform shape, and also duplicate the directivity pattern of BVI impulsive noise. At moderate advance ratios (mu = 0.224 to 0.270), the scaling deteriorates, suggesting that the model scale rotor is not adequately simulating the full scale BVI noise; presently, no proved explanation of this discrepancy exists. Carefully performed parametric variations over a complete matrix of testing conditions have shown that all of the four governing nondimensional parameters - tip Mach number at hover, advance ratio, local inflow ratio, and thrust coefficient - are highly sensitive to BVI noise radiation.

  18. S-ProvFlow: provenance model and tools for scalable and adaptive analysis pipelines in geoscience.

    Science.gov (United States)

    Spinuso, A.; Mihajlovski, A.; Atkinson, M.; Filgueira, R.; Klampanos, I.; Sanchez, S.

    2017-12-01

    The reproducibility of scientific findings is essential to improve the quality and application of modern data-driven research. Delivering such reproducibility is challenging in the context of systems handling large data-streams with sophisticated computational methods. Similarly, the SKA (Square Kilometer Array) will collect an unprecedented volume of radio-wave signals that will have to be reduced and transformed into derived products, with impact on space-weather research. This highlights the importance of having cross-disciplines mechanisms at the producer's side that rely on usable lineage data to support validation and traceability of the new artifacts. To be informative, provenance has to describe each methods' abstractions and their implementation as mappings onto distributed platforms and their concurrent execution, capturing relevant internal dependencies at runtime. Producers and intelligent toolsets should be able to exploit the produced provenance, steering real-time monitoring activities and inferring adaptations of methods at runtime.We present a model of provenance (S-PROV) that extends W3C PROV and ProvONE, broadening coverage of provenance to aspects related to distribution, scale-up and steering of stateful streaming operators in analytic pipelines. This is supported by a technical framework for tuneable and actionable lineage, ensuring its relevance to the users' interests, fostering its rapid exploitation to facilitate research practices. By applying concepts such as provenance typing and profiling, users define rules to capture common provenance patterns and activate selective controls based on domain-metadata. The traces are recorded in a document-store with index optimisation and a web API serves advanced interactive tools (S-ProvFlow, https://github.com/KNMI/s-provenance). These allow different classes of consumers to rapidly explore the provenance data. The system, which contributes to the SKA-Link initiative, within technology and

  19. Scalable Automated Model Search

    Science.gov (United States)

    2014-05-20

    profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on...minimization. The computer journal, 7(4):308–313, 1965. [31] K. Ousterhout, A. Panda , J. Rosen, S. Venkataraman, R. Xin, S. Ratnasamy, S. Shenker...and I. Stoica. The case for tiny tasks in compute clusters. [32] B. Panda , J. S. Herbach, S. Basu, and R. J. Bayardo. Planet: massively parallel

  20. Scalable Frequent Subgraph Mining

    KAUST Repository

    Abdelhamid, Ehab

    2017-06-19

    A graph is a data structure that contains a set of nodes and a set of edges connecting these nodes. Nodes represent objects while edges model relationships among these objects. Graphs are used in various domains due to their ability to model complex relations among several objects. Given an input graph, the Frequent Subgraph Mining (FSM) task finds all subgraphs with frequencies exceeding a given threshold. FSM is crucial for graph analysis, and it is an essential building block in a variety of applications, such as graph clustering and indexing. FSM is computationally expensive, and its existing solutions are extremely slow. Consequently, these solutions are incapable of mining modern large graphs. This slowness is caused by the underlying approaches of these solutions which require finding and storing an excessive amount of subgraph matches. This dissertation proposes a scalable solution for FSM that avoids the limitations of previous work. This solution is composed of four components. The first component is a single-threaded technique which, for each candidate subgraph, needs to find only a minimal number of matches. The second component is a scalable parallel FSM technique that utilizes a novel two-phase approach. The first phase quickly builds an approximate search space, which is then used by the second phase to optimize and balance the workload of the FSM task. The third component focuses on accelerating frequency evaluation, which is a critical step in FSM. To do so, a machine learning model is employed to predict the type of each graph node, and accordingly, an optimized method is selected to evaluate that node. The fourth component focuses on mining dynamic graphs, such as social networks. To this end, an incremental index is maintained during the dynamic updates. Only this index is processed and updated for the majority of graph updates. Consequently, search space is significantly pruned and efficiency is improved. The empirical evaluation shows that the

  1. Numeric Analysis for Relationship-Aware Scalable Streaming Scheme

    Directory of Open Access Journals (Sweden)

    Heung Ki Lee

    2014-01-01

    Full Text Available Frequent packet loss of media data is a critical problem that degrades the quality of streaming services over mobile networks. Packet loss invalidates frames containing lost packets and other related frames at the same time. Indirect loss caused by losing packets decreases the quality of streaming. A scalable streaming service can decrease the amount of dropped multimedia resulting from a single packet loss. Content providers typically divide one large media stream into several layers through a scalable streaming service and then provide each scalable layer to the user depending on the mobile network. Also, a scalable streaming service makes it possible to decode partial multimedia data depending on the relationship between frames and layers. Therefore, a scalable streaming service provides a way to decrease the wasted multimedia data when one packet is lost. However, the hierarchical structure between frames and layers of scalable streams determines the service quality of the scalable streaming service. Even if whole packets of layers are transmitted successfully, they cannot be decoded as a result of the absence of reference frames and layers. Therefore, the complicated relationship between frames and layers in a scalable stream increases the volume of abandoned layers. For providing a high-quality scalable streaming service, we choose a proper relationship between scalable layers as well as the amount of transmitted multimedia data depending on the network situation. We prove that a simple scalable scheme outperforms a complicated scheme in an error-prone network. We suggest an adaptive set-top box (AdaptiveSTB to lower the dependency between scalable layers in a scalable stream. Also, we provide a numerical model to obtain the indirect loss of multimedia data and apply it to various multimedia streams. Our AdaptiveSTB enhances the quality of a scalable streaming service by removing indirect loss.

  2. PKI Scalability Issues

    OpenAIRE

    Slagell, Adam J; Bonilla, Rafael

    2004-01-01

    This report surveys different PKI technologies such as PKIX and SPKI and the issues of PKI that affect scalability. Much focus is spent on certificate revocation methodologies and status verification systems such as CRLs, Delta-CRLs, CRS, Certificate Revocation Trees, Windowed Certificate Revocation, OCSP, SCVP and DVCS.

  3. Linking Remote Sensing Data and Energy Balance Models for a Scalable Agriculture Insurance System for sub-Saharan Africa

    Science.gov (United States)

    Brown, M. E.; Osgood, D. E.; McCarty, J. L.; Husak, G. J.; Hain, C.; Neigh, C. S. R.

    2014-12-01

    One of the most immediate and obvious impacts of climate change is on the weather-sensitive agriculture sector. Both local and global impacts on production of food will have a negative effect on the ability of humanity to meet its growing food demands. Agriculture has become more risky, particularly for farmers in the most vulnerable and food insecure regions of the world such as East Africa. Smallholders and low-income farmers need better financial tools to reduce the risk to food security while enabling productivity increases to meet the needs of a growing population. This paper will describe a recently funded project that brings together climate science, economics, and remote sensing expertise to focus on providing a scalable and sensor-independent remote sensing based product that can be used in developing regional rainfed agriculture insurance programs around the world. We will focus our efforts in Ethiopia and Kenya in East Africa and in Senegal and Burkina Faso in West Africa, where there are active index insurance pilots that can test the effectiveness of our remote sensing-based approach for use in the agriculture insurance industry. The paper will present the overall program, explain links to the insurance industry, and present comparisons of the four remote sensing datasets used to identify drought: the CHIRPS 30-year rainfall data product, the GIMMS 30-year vegetation data product from AVHRR, the ESA soil moisture ECV-30 year soil moisture data product, and a MODIS Evapotranspiration (ET) 15-year dataset. A summary of next year's plans for this project will be presented at the close of the presentation.

  4. Scalable Resolution Display Walls

    KAUST Repository

    Leigh, Jason; Johnson, Andrew; Renambot, Luc; Peterka, Tom; Jeong, Byungil; Sandin, Daniel J.; Talandis, Jonas; Jagodic, Ratko; Nam, Sungwon; Hur, Hyejung; Sun, Yiwen

    2013-01-01

    This article will describe the progress since 2000 on research and development in 2-D and 3-D scalable resolution display walls that are built from tiling individual lower resolution flat panel displays. The article will describe approaches and trends in display hardware construction, middleware architecture, and user-interaction design. The article will also highlight examples of use cases and the benefits the technology has brought to their respective disciplines. © 1963-2012 IEEE.

  5. Declarative and Scalable Selection for Map Visualizations

    DEFF Research Database (Denmark)

    Kefaloukos, Pimin Konstantin Balic

    and is itself a source and cause of prolific data creation. This calls for scalable map processing techniques that can handle the data volume and which play well with the predominant data models on the Web. (4) Maps are now consumed around the clock by a global audience. While historical maps were singleuser......-defined constraints as well as custom objectives. The purpose of the language is to derive a target multi-scale database from a source database according to holistic specifications. (b) The Glossy SQL compiler allows Glossy SQL to be scalably executed in a spatial analytics system, such as a spatial relational......, there are indications that the method is scalable for databases that contain millions of records, especially if the target language of the compiler is substituted by a cluster-ready variant of SQL. While several realistic use cases for maps have been implemented in CVL, additional non-geographic data visualization uses...

  6. Enhancing Scalability of Sparse Direct Methods

    International Nuclear Information System (INIS)

    Li, Xiaoye S.; Demmel, James; Grigori, Laura; Gu, Ming; Xia, Jianlin; Jardin, Steve; Sovinec, Carl; Lee, Lie-Quan

    2007-01-01

    TOPS is providing high-performance, scalable sparse direct solvers, which have had significant impacts on the SciDAC applications, including fusion simulation (CEMM), accelerator modeling (COMPASS), as well as many other mission-critical applications in DOE and elsewhere. Our recent developments have been focusing on new techniques to overcome scalability bottleneck of direct methods, in both time and memory. These include parallelizing symbolic analysis phase and developing linear-complexity sparse factorization methods. The new techniques will make sparse direct methods more widely usable in large 3D simulations on highly-parallel petascale computers

  7. Scalable optical quantum computer

    Energy Technology Data Exchange (ETDEWEB)

    Manykin, E A; Mel' nichenko, E V [Institute for Superconductivity and Solid-State Physics, Russian Research Centre ' Kurchatov Institute' , Moscow (Russian Federation)

    2014-12-31

    A way of designing a scalable optical quantum computer based on the photon echo effect is proposed. Individual rare earth ions Pr{sup 3+}, regularly located in the lattice of the orthosilicate (Y{sub 2}SiO{sub 5}) crystal, are suggested to be used as optical qubits. Operations with qubits are performed using coherent and incoherent laser pulses. The operation protocol includes both the method of measurement-based quantum computations and the technique of optical computations. Modern hybrid photon echo protocols, which provide a sufficient quantum efficiency when reading recorded states, are considered as most promising for quantum computations and communications. (quantum computer)

  8. Scalable optical quantum computer

    International Nuclear Information System (INIS)

    Manykin, E A; Mel'nichenko, E V

    2014-01-01

    A way of designing a scalable optical quantum computer based on the photon echo effect is proposed. Individual rare earth ions Pr 3+ , regularly located in the lattice of the orthosilicate (Y 2 SiO 5 ) crystal, are suggested to be used as optical qubits. Operations with qubits are performed using coherent and incoherent laser pulses. The operation protocol includes both the method of measurement-based quantum computations and the technique of optical computations. Modern hybrid photon echo protocols, which provide a sufficient quantum efficiency when reading recorded states, are considered as most promising for quantum computations and communications. (quantum computer)

  9. Scalable Open Source Smart Grid Simulator (SGSim)

    DEFF Research Database (Denmark)

    Ebeid, Emad Samuel Malki; Jacobsen, Rune Hylsberg; Stefanni, Francesco

    2017-01-01

    . This paper presents an open source smart grid simulator (SGSim). The simulator is based on open source SystemC Network Simulation Library (SCNSL) and aims to model scalable smart grid applications. SGSim has been tested under different smart grid scenarios that contain hundreds of thousands of households...

  10. Cooperative Scalable Moving Continuous Query Processing

    DEFF Research Database (Denmark)

    Li, Xiaohui; Karras, Panagiotis; Jensen, Christian S.

    2012-01-01

    of the global view and handle the majority of the workload. Meanwhile, moving clients, having basic memory and computation resources, handle small portions of the workload. This model is further enhanced by dynamic region allocation and grid size adjustment mechanisms that reduce the communication...... and computation cost for both servers and clients. An experimental study demonstrates that our approaches offer better scalability than competitors...

  11. Getting a Cohesive Answer from a Common Start: Scalable Multidisciplinary Analysis through Transformation of a Systems Model

    Science.gov (United States)

    Cole, Bjorn; Chung, Seung

    2012-01-01

    One of the challenges of systems engineering is in working multidisciplinary problems in a cohesive manner. When planning analysis of these problems, system engineers must trade between time and cost for analysis quality and quantity. The quality often correlates with greater run time in multidisciplinary models and the quantity is associated with the number of alternatives that can be analyzed. The trade-off is due to the resource intensive process of creating a cohesive multidisciplinary systems model and analysis. Furthermore, reuse or extension of the models used in one stage of a product life cycle for another is a major challenge. Recent developments have enabled a much less resource-intensive and more rigorous approach than hand-written translation scripts between multi-disciplinary models and their analyses. The key is to work from a core systems model defined in a MOF-based language such as SysML and in leveraging the emerging tool ecosystem, such as Query/View/Transformation (QVT), from the OMG community. SysML was designed to model multidisciplinary systems. The QVT standard was designed to transform SysML models into other models, including those leveraged by engineering analyses. The Europa Habitability Mission (EHM) team has begun to exploit these capabilities. In one case, a Matlab/Simulink model is generated on the fly from a system description for power analysis written in SysML. In a more general case, symbolic analysis (supported by Wolfram Mathematica) is coordinated by data objects transformed from the systems model, enabling extremely flexible and powerful design exploration and analytical investigations of expected system performance.

  12. A scalable multi-resolution spatio-temporal model for brain activation and connectivity in fMRI data

    KAUST Repository

    Castruccio, Stefano

    2018-01-23

    Functional Magnetic Resonance Imaging (fMRI) is a primary modality for studying brain activity. Modeling spatial dependence of imaging data at different spatial scales is one of the main challenges of contemporary neuroimaging, and it could allow for accurate testing for significance in neural activity. The high dimensionality of this type of data (on the order of hundreds of thousands of voxels) poses serious modeling challenges and considerable computational constraints. For the sake of feasibility, standard models typically reduce dimensionality by modeling covariance among regions of interest (ROIs)—coarser or larger spatial units—rather than among voxels. However, ignoring spatial dependence at different scales could drastically reduce our ability to detect activation patterns in the brain and hence produce misleading results. We introduce a multi-resolution spatio-temporal model and a computationally efficient methodology to estimate cognitive control related activation and whole-brain connectivity. The proposed model allows for testing voxel-specific activation while accounting for non-stationary local spatial dependence within anatomically defined ROIs, as well as regional dependence (between-ROIs). The model is used in a motor-task fMRI study to investigate brain activation and connectivity patterns aimed at identifying associations between these patterns and regaining motor functionality following a stroke.

  13. Getting a Cohesive Answer from a Common Start: Scalable Multidisciplinary Analysis through Transformation of a System Model

    Science.gov (United States)

    Cole, Bjorn; Chung, Seung H.

    2012-01-01

    One of the challenges of systems engineering is in working multidisciplinary problems in a cohesive manner. When planning analysis of these problems, system engineers must tradeoff time and cost for analysis quality and quantity. The quality is associated with the fidelity of the multidisciplinary models and the quantity is associated with the design space that can be analyzed. The tradeoff is due to the resource intensive process of creating a cohesive multidisciplinary system model and analysis. Furthermore, reuse or extension of the models used in one stage of a product life cycle for another is a major challenge. Recent developments have enabled a much less resource-intensive and more rigorous approach than handwritten translation scripts or codes of multidisciplinary models and their analyses. The key is to work from a core system model defined in a MOF-based language such as SysML and in leveraging the emerging tool ecosystem, such as Query-View- Transform (QVT), from the OMG community. SysML was designed to model multidisciplinary systems and analyses. The QVT standard was designed to transform SysML models. The Europa Hability Mission (EHM) team has begun to exploit these capabilities. In one case, a Matlab/Simulink model is generated on the fly from a system description for power analysis written in SysML. In a more general case, a symbolic mathematical framework (supported by Wolfram Mathematica) is coordinated by data objects transformed from the system model, enabling extremely flexible and powerful tradespace exploration and analytical investigations of expected system performance.

  14. A scalable multi-resolution spatio-temporal model for brain activation and connectivity in fMRI data

    KAUST Repository

    Castruccio, Stefano; Ombao, Hernando; Genton, Marc G.

    2018-01-01

    Functional Magnetic Resonance Imaging (fMRI) is a primary modality for studying brain activity. Modeling spatial dependence of imaging data at different spatial scales is one of the main challenges of contemporary neuroimaging, and it could allow

  15. Scalable photoreactor for hydrogen production

    KAUST Repository

    Takanabe, Kazuhiro; Shinagawa, Tatsuya

    2017-01-01

    Provided herein are scalable photoreactors that can include a membrane-free water- splitting electrolyzer and systems that can include a plurality of membrane-free water- splitting electrolyzers. Also provided herein are methods of using the scalable photoreactors provided herein.

  16. Scalable photoreactor for hydrogen production

    KAUST Repository

    Takanabe, Kazuhiro

    2017-04-06

    Provided herein are scalable photoreactors that can include a membrane-free water- splitting electrolyzer and systems that can include a plurality of membrane-free water- splitting electrolyzers. Also provided herein are methods of using the scalable photoreactors provided herein.

  17. Designing a Scalable Fault Tolerance Model for High Performance Computational Chemistry: A Case Study with Coupled Cluster Perturbative Triples.

    Science.gov (United States)

    van Dam, Hubertus J J; Vishnu, Abhinav; de Jong, Wibe A

    2011-01-11

    In the past couple of decades, the massive computational power provided by the most modern supercomputers has resulted in simulation of higher-order computational chemistry methods, previously considered intractable. As the system sizes continue to increase, the computational chemistry domain continues to escalate this trend using parallel computing with programming models such as Message Passing Interface (MPI) and Partitioned Global Address Space (PGAS) programming models such as Global Arrays. The ever increasing scale of these supercomputers comes at a cost of reduced Mean Time Between Failures (MTBF), currently on the order of days and projected to be on the order of hours for upcoming extreme scale systems. While traditional disk-based check pointing methods are ubiquitous for storing intermediate solutions, they suffer from high overhead of writing and recovering from checkpoints. In practice, checkpointing itself often brings the system down. Clearly, methods beyond checkpointing are imperative to handling the aggravating issue of reducing MTBF. In this paper, we address this challenge by designing and implementing an efficient fault tolerant version of the Coupled Cluster (CC) method with NWChem, using in-memory data redundancy. We present the challenges associated with our design, including an efficient data storage model, maintenance of at least one consistent data copy, and the recovery process. Our performance evaluation without faults shows that the current design exhibits a small overhead. In the presence of a simulated fault, the proposed design incurs negligible overhead in comparison to the state of the art implementation without faults.

  18. Intratracheal Bleomycin Aerosolization: The Best Route of Administration for a Scalable and Homogeneous Pulmonary Fibrosis Rat Model?

    Directory of Open Access Journals (Sweden)

    Alexandre Robbe

    2015-01-01

    Full Text Available Idiopathic pulmonary fibrosis (IPF is a chronic disease with a poor prognosis and is characterized by the accumulation of fibrotic tissue in lungs resulting from a dysfunction in the healing process. In humans, the pathological process is patchy and temporally heterogeneous and the exact mechanisms remain poorly understood. Different animal models were thus developed. Among these, intratracheal administration of bleomycin (BML is one of the most frequently used methods to induce lung fibrosis in rodents. In the present study, we first characterized histologically the time-course of lung alteration in rats submitted to BLM instillation. Heterogeneous damages were observed among lungs, consisting in an inflammatory phase at early time-points. It was followed by a transition to a fibrotic state characterized by an increased myofibroblast number and collagen accumulation. We then compared instillation and aerosolization routes of BLM administration. The fibrotic process was studied in each pulmonary lobe using a modified Ashcroft scale. The two quantification methods were confronted and the interobserver variability evaluated. Both methods induced fibrosis development as demonstrated by a similar progression of the highest modified Ashcroft score. However, we highlighted that aerosolization allows a more homogeneous distribution of lesions among lungs, with a persistence of higher grade damages upon time.

  19. A scalable satellite-based crop yield mapper: Integrating satellites and crop models for field-scale estimation in India

    Science.gov (United States)

    Jain, M.; Singh, B.; Srivastava, A.; Lobell, D. B.

    2015-12-01

    Food security will be challenged over the upcoming decades due to increased food demand, natural resource degradation, and climate change. In order to identify potential solutions to increase food security in the face of these changes, tools that can rapidly and accurately assess farm productivity are needed. With this aim, we have developed generalizable methods to map crop yields at the field scale using a combination of satellite imagery and crop models, and implement this approach within Google Earth Engine. We use these methods to examine wheat yield trends in Northern India, which provides over 15% of the global wheat supply and where over 80% of farmers rely on wheat as a staple food source. In addition, we identify the extent to which farmers are shifting sow date in response to heat stress, and how well shifting sow date reduces the negative impacts of heat stress on yield. To identify local-level decision-making, we map wheat sow date and yield at a high spatial resolution (30 m) using Landsat satellite imagery from 1980 to the present. This unique dataset allows us to examine sow date decisions at the field scale over 30 years, and by relating these decisions to weather experienced over the same time period, we can identify how farmers learn and adapt cropping decisions based on weather through time.

  20. Modeling, simulation, and fabrication of a fully integrated, acid-stable, scalable solar-driven water-splitting system.

    Science.gov (United States)

    Walczak, Karl; Chen, Yikai; Karp, Christoph; Beeman, Jeffrey W; Shaner, Matthew; Spurgeon, Joshua; Sharp, Ian D; Amashukeli, Xenia; West, William; Jin, Jian; Lewis, Nathan S; Xiang, Chengxiang

    2015-02-01

    A fully integrated solar-driven water-splitting system comprised of WO3 /FTO/p(+) n Si as the photoanode, Pt/TiO2 /Ti/n(+) p Si as the photocathode, and Nafion as the membrane separator, was simulated, assembled, operated in 1.0 M HClO4 , and evaluated for performance and safety characteristics under dual side illumination. A multi-physics model that accounted for the performance of the photoabsorbers and electrocatalysts, ion transport in the solution electrolyte, and gaseous product crossover was first used to define the optimal geometric design space for the system. The photoelectrodes and the membrane separators were then interconnected in a louvered design system configuration, for which the light-absorbing area and the solution-transport pathways were simultaneously optimized. The performance of the photocathode and the photoanode were separately evaluated in a traditional three-electrode photoelectrochemical cell configuration. The photocathode and photoanode were then assembled back-to-back in a tandem configuration to provide sufficient photovoltage to sustain solar-driven unassisted water-splitting. The current-voltage characteristics of the photoelectrodes showed that the low photocurrent density of the photoanode limited the overall solar-to-hydrogen (STH) conversion efficiency due to the large band gap of WO3 . A hydrogen-production rate of 0.17 mL hr(-1) and a STH conversion efficiency of 0.24 % was observed in a full cell configuration for >20 h with minimal product crossover in the fully operational, intrinsically safe, solar-driven water-splitting system. The solar-to-hydrogen conversion efficiency, ηSTH , calculated using the multiphysics numerical simulation was in excellent agreement with the experimental behavior of the system. The value of ηSTH was entirely limited by the performance of the photoelectrochemical assemblies employed in this study. The louvered design provides a robust platform for implementation of various types of

  1. Scalable Nanomanufacturing—A Review

    Directory of Open Access Journals (Sweden)

    Khershed Cooper

    2017-01-01

    Full Text Available This article describes the field of scalable nanomanufacturing, its importance and need, its research activities and achievements. The National Science Foundation is taking a leading role in fostering basic research in scalable nanomanufacturing (SNM. From this effort several novel nanomanufacturing approaches have been proposed, studied and demonstrated, including scalable nanopatterning. This paper will discuss SNM research areas in materials, processes and applications, scale-up methods with project examples, and manufacturing challenges that need to be addressed to move nanotechnology discoveries closer to the marketplace.

  2. Scalable Nonlinear Compact Schemes

    Energy Technology Data Exchange (ETDEWEB)

    Ghosh, Debojyoti [Argonne National Lab. (ANL), Argonne, IL (United States); Constantinescu, Emil M. [Univ. of Chicago, IL (United States); Brown, Jed [Univ. of Colorado, Boulder, CO (United States)

    2014-04-01

    In this work, we focus on compact schemes resulting in tridiagonal systems of equations, specifically the fifth-order CRWENO scheme. We propose a scalable implementation of the nonlinear compact schemes by implementing a parallel tridiagonal solver based on the partitioning/substructuring approach. We use an iterative solver for the reduced system of equations; however, we solve this system to machine zero accuracy to ensure that no parallelization errors are introduced. It is possible to achieve machine-zero convergence with few iterations because of the diagonal dominance of the system. The number of iterations is specified a priori instead of a norm-based exit criterion, and collective communications are avoided. The overall algorithm thus involves only point-to-point communication between neighboring processors. Our implementation of the tridiagonal solver differs from and avoids the drawbacks of past efforts in the following ways: it introduces no parallelization-related approximations (multiprocessor solutions are exactly identical to uniprocessor ones), it involves minimal communication, the mathematical complexity is similar to that of the Thomas algorithm on a single processor, and it does not require any communication and computation scheduling.

  3. Scalable and balanced dynamic hybrid data assimilation

    Science.gov (United States)

    Kauranne, Tuomo; Amour, Idrissa; Gunia, Martin; Kallio, Kari; Lepistö, Ahti; Koponen, Sampsa

    2017-04-01

    Scalability of complex weather forecasting suites is dependent on the technical tools available for implementing highly parallel computational kernels, but to an equally large extent also on the dependence patterns between various components of the suite, such as observation processing, data assimilation and the forecast model. Scalability is a particular challenge for 4D variational assimilation methods that necessarily couple the forecast model into the assimilation process and subject this combination to an inherently serial quasi-Newton minimization process. Ensemble based assimilation methods are naturally more parallel, but large models force ensemble sizes to be small and that results in poor assimilation accuracy, somewhat akin to shooting with a shotgun in a million-dimensional space. The Variational Ensemble Kalman Filter (VEnKF) is an ensemble method that can attain the accuracy of 4D variational data assimilation with a small ensemble size. It achieves this by processing a Gaussian approximation of the current error covariance distribution, instead of a set of ensemble members, analogously to the Extended Kalman Filter EKF. Ensemble members are re-sampled every time a new set of observations is processed from a new approximation of that Gaussian distribution which makes VEnKF a dynamic assimilation method. After this a smoothing step is applied that turns VEnKF into a dynamic Variational Ensemble Kalman Smoother VEnKS. In this smoothing step, the same process is iterated with frequent re-sampling of the ensemble but now using past iterations as surrogate observations until the end result is a smooth and balanced model trajectory. In principle, VEnKF could suffer from similar scalability issues as 4D-Var. However, this can be avoided by isolating the forecast model completely from the minimization process by implementing the latter as a wrapper code whose only link to the model is calling for many parallel and totally independent model runs, all of them

  4. Design issues for numerical libraries on scalable multicore architectures

    International Nuclear Information System (INIS)

    Heroux, M A

    2008-01-01

    Future generations of scalable computers will rely on multicore nodes for a significant portion of overall system performance. At present, most applications and libraries cannot exploit multiple cores beyond running addition MPI processes per node. In this paper we discuss important multicore architecture issues, programming models, algorithms requirements and software design related to effective use of scalable multicore computers. In particular, we focus on important issues for library research and development, making recommendations for how to effectively develop libraries for future scalable computer systems

  5. ALADDIN - enhancing applicability and scalability

    International Nuclear Information System (INIS)

    Roverso, Davide

    2001-02-01

    The ALADDIN project aims at the study and development of flexible, accurate, and reliable techniques and principles for computerised event classification and fault diagnosis for complex machinery and industrial processes. The main focus of the project is on advanced numerical techniques, such as wavelets, and empirical modelling with neural networks. This document reports on recent important advancements, which significantly widen the practical applicability of the developed principles, both in terms of flexibility of use, and in terms of scalability to large problem domains. In particular, two novel techniques are here described. The first, which we call Wavelet On- Line Pre-processing (WOLP), is aimed at extracting, on-line, relevant dynamic features from the process data streams. This technique allows a system a greater flexibility in detecting and processing transients at a range of different time scales. The second technique, which we call Autonomous Recursive Task Decomposition (ARTD), is aimed at tackling the problem of constructing a classifier able to discriminate among a large number of different event/fault classes, which is often the case when the application domain is a complex industrial process. ARTD also allows for incremental application development (i.e. the incremental addition of new classes to an existing classifier, without the need of retraining the entire system), and for simplified application maintenance. The description of these novel techniques is complemented by reports of quantitative experiments that show in practice the extent of these improvements. (Author)

  6. Scalable algorithms for contact problems

    CERN Document Server

    Dostál, Zdeněk; Sadowská, Marie; Vondrák, Vít

    2016-01-01

    This book presents a comprehensive and self-contained treatment of the authors’ newly developed scalable algorithms for the solutions of multibody contact problems of linear elasticity. The brand new feature of these algorithms is theoretically supported numerical scalability and parallel scalability demonstrated on problems discretized by billions of degrees of freedom. The theory supports solving multibody frictionless contact problems, contact problems with possibly orthotropic Tresca’s friction, and transient contact problems. It covers BEM discretization, jumping coefficients, floating bodies, mortar non-penetration conditions, etc. The exposition is divided into four parts, the first of which reviews appropriate facets of linear algebra, optimization, and analysis. The most important algorithms and optimality results are presented in the third part of the volume. The presentation is complete, including continuous formulation, discretization, decomposition, optimality results, and numerical experimen...

  7. Scalable cloud without dedicated storage

    Science.gov (United States)

    Batkovich, D. V.; Kompaniets, M. V.; Zarochentsev, A. K.

    2015-05-01

    We present a prototype of a scalable computing cloud. It is intended to be deployed on the basis of a cluster without the separate dedicated storage. The dedicated storage is replaced by the distributed software storage. In addition, all cluster nodes are used both as computing nodes and as storage nodes. This solution increases utilization of the cluster resources as well as improves fault tolerance and performance of the distributed storage. Another advantage of this solution is high scalability with a relatively low initial and maintenance cost. The solution is built on the basis of the open source components like OpenStack, CEPH, etc.

  8. Scalable Simulation of Electromagnetic Hybrid Codes

    International Nuclear Information System (INIS)

    Perumalla, Kalyan S.; Fujimoto, Richard; Karimabadi, Dr. Homa

    2006-01-01

    New discrete-event formulations of physics simulation models are emerging that can outperform models based on traditional time-stepped techniques. Detailed simulation of the Earth's magnetosphere, for example, requires execution of sub-models that are at widely differing timescales. In contrast to time-stepped simulation which requires tightly coupled updates to entire system state at regular time intervals, the new discrete event simulation (DES) approaches help evolve the states of sub-models on relatively independent timescales. However, parallel execution of DES-based models raises challenges with respect to their scalability and performance. One of the key challenges is to improve the computation granularity to offset synchronization and communication overheads within and across processors. Our previous work was limited in scalability and runtime performance due to the parallelization challenges. Here we report on optimizations we performed on DES-based plasma simulation models to improve parallel performance. The net result is the capability to simulate hybrid particle-in-cell (PIC) models with over 2 billion ion particles using 512 processors on supercomputing platforms

  9. Scalable shared-memory multiprocessing

    CERN Document Server

    Lenoski, Daniel E

    1995-01-01

    Dr. Lenoski and Dr. Weber have experience with leading-edge research and practical issues involved in implementing large-scale parallel systems. They were key contributors to the architecture and design of the DASH multiprocessor. Currently, they are involved with commercializing scalable shared-memory technology.

  10. Scalable group level probabilistic sparse factor analysis

    DEFF Research Database (Denmark)

    Hinrich, Jesper Løve; Nielsen, Søren Føns Vind; Riis, Nicolai Andre Brogaard

    2017-01-01

    Many data-driven approaches exist to extract neural representations of functional magnetic resonance imaging (fMRI) data, but most of them lack a proper probabilistic formulation. We propose a scalable group level probabilistic sparse factor analysis (psFA) allowing spatially sparse maps, component...... pruning using automatic relevance determination (ARD) and subject specific heteroscedastic spatial noise modeling. For task-based and resting state fMRI, we show that the sparsity constraint gives rise to components similar to those obtained by group independent component analysis. The noise modeling...... shows that noise is reduced in areas typically associated with activation by the experimental design. The psFA model identifies sparse components and the probabilistic setting provides a natural way to handle parameter uncertainties. The variational Bayesian framework easily extends to more complex...

  11. Algorithmic psychometrics and the scalable subject.

    Science.gov (United States)

    Stark, Luke

    2018-04-01

    Recent public controversies, ranging from the 2014 Facebook 'emotional contagion' study to psychographic data profiling by Cambridge Analytica in the 2016 American presidential election, Brexit referendum and elsewhere, signal watershed moments in which the intersecting trajectories of psychology and computer science have become matters of public concern. The entangled history of these two fields grounds the application of applied psychological techniques to digital technologies, and an investment in applying calculability to human subjectivity. Today, a quantifiable psychological subject position has been translated, via 'big data' sets and algorithmic analysis, into a model subject amenable to classification through digital media platforms. I term this position the 'scalable subject', arguing it has been shaped and made legible by algorithmic psychometrics - a broad set of affordances in digital platforms shaped by psychology and the behavioral sciences. In describing the contours of this 'scalable subject', this paper highlights the urgent need for renewed attention from STS scholars on the psy sciences, and on a computational politics attentive to psychology, emotional expression, and sociality via digital media.

  12. Scalable Techniques for Formal Verification

    CERN Document Server

    Ray, Sandip

    2010-01-01

    This book presents state-of-the-art approaches to formal verification techniques to seamlessly integrate different formal verification methods within a single logical foundation. It should benefit researchers and practitioners looking to get a broad overview of the spectrum of formal verification techniques, as well as approaches to combining such techniques within a single framework. Coverage includes a range of case studies showing how such combination is fruitful in developing a scalable verification methodology for industrial designs. This book outlines both theoretical and practical issue

  13. Developing Scalable Information Security Systems

    Directory of Open Access Journals (Sweden)

    Valery Konstantinovich Ablekov

    2013-06-01

    Full Text Available Existing physical security systems has wide range of lacks, including: high cost, a large number of vulnerabilities, problems of modification and support system. This paper covers an actual problem of developing systems without this list of drawbacks. The paper presents the architecture of the information security system, which operates through the network protocol TCP/IP, including the ability to connect different types of devices and integration with existing security systems. The main advantage is a significant increase in system reliability, scalability, both vertically and horizontally, with minimal cost of both financial and time resources.

  14. Scalable power selection method for wireless mesh networks

    CSIR Research Space (South Africa)

    Olwal, TO

    2009-01-01

    Full Text Available This paper addresses the problem of a scalable dynamic power control (SDPC) for wireless mesh networks (WMNs) based on IEEE 802.11 standards. An SDPC model that accounts for architectural complexities witnessed in multiple radios and hops...

  15. Scalability and efficiency of genetic algorithms for geometrical applications

    NARCIS (Netherlands)

    Dijk, van S.F.; Thierens, D.; Berg, de M.; Schoenauer, M.

    2000-01-01

    We study the scalability and efficiency of a GA that we developed earlier to solve the practical cartographic problem of labeling a map with point features. We argue that the special characteristics of our GA make that it fits in well with theoretical models predicting the optimal population size

  16. A Massively Scalable Architecture for Instant Messaging & Presence

    NARCIS (Netherlands)

    Schippers, Jorrit; Remke, Anne Katharina Ingrid; Punt, Henk; Wegdam, M.; Haverkort, Boudewijn R.H.M.; Thomas, N.; Bradley, J.; Knottenbelt, W.; Dingle, N.; Harder, U.

    2010-01-01

    This paper analyzes the scalability of Instant Messaging & Presence (IM&P) architectures. We take a queueing-based modelling and analysis approach to ��?nd the bottlenecks of the current IM&P architecture at the Dutch social network Hyves, as well as of alternative architectures. We use the

  17. Scalable Performance Measurement and Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Gamblin, Todd [Univ. of North Carolina, Chapel Hill, NC (United States)

    2009-01-01

    Concurrency levels in large-scale, distributed-memory supercomputers are rising exponentially. Modern machines may contain 100,000 or more microprocessor cores, and the largest of these, IBM's Blue Gene/L, contains over 200,000 cores. Future systems are expected to support millions of concurrent tasks. In this dissertation, we focus on efficient techniques for measuring and analyzing the performance of applications running on very large parallel machines. Tuning the performance of large-scale applications can be a subtle and time-consuming task because application developers must measure and interpret data from many independent processes. While the volume of the raw data scales linearly with the number of tasks in the running system, the number of tasks is growing exponentially, and data for even small systems quickly becomes unmanageable. Transporting performance data from so many processes over a network can perturb application performance and make measurements inaccurate, and storing such data would require a prohibitive amount of space. Moreover, even if it were stored, analyzing the data would be extremely time-consuming. In this dissertation, we present novel methods for reducing performance data volume. The first draws on multi-scale wavelet techniques from signal processing to compress systemwide, time-varying load-balance data. The second uses statistical sampling to select a small subset of running processes to generate low-volume traces. A third approach combines sampling and wavelet compression to stratify performance data adaptively at run-time and to reduce further the cost of sampled tracing. We have integrated these approaches into Libra, a toolset for scalable load-balance analysis. We present Libra and show how it can be used to analyze data from large scientific applications scalably.

  18. Requirements for Scalable Access Control and Security Management Architectures

    National Research Council Canada - National Science Library

    Keromytis, Angelos D; Smith, Jonathan M

    2005-01-01

    Maximizing local autonomy has led to a scalable Internet. Scalability and the capacity for distributed control have unfortunately not extended well to resource access control policies and mechanisms...

  19. Adaptive format conversion for scalable video coding

    Science.gov (United States)

    Wan, Wade K.; Lim, Jae S.

    2001-12-01

    The enhancement layer in many scalable coding algorithms is composed of residual coding information. There is another type of information that can be transmitted instead of (or in addition to) residual coding. Since the encoder has access to the original sequence, it can utilize adaptive format conversion (AFC) to generate the enhancement layer and transmit the different format conversion methods as enhancement data. This paper investigates the use of adaptive format conversion information as enhancement data in scalable video coding. Experimental results are shown for a wide range of base layer qualities and enhancement bitrates to determine when AFC can improve video scalability. Since the parameters needed for AFC are small compared to residual coding, AFC can provide video scalability at low enhancement layer bitrates that are not possible with residual coding. In addition, AFC can also be used in addition to residual coding to improve video scalability at higher enhancement layer bitrates. Adaptive format conversion has not been studied in detail, but many scalable applications may benefit from it. An example of an application that AFC is well-suited for is the migration path for digital television where AFC can provide immediate video scalability as well as assist future migrations.

  20. Fast and scalable inequality joins

    KAUST Repository

    Khayyat, Zuhair

    2016-09-07

    Inequality joins, which is to join relations with inequality conditions, are used in various applications. Optimizing joins has been the subject of intensive research ranging from efficient join algorithms such as sort-merge join, to the use of efficient indices such as (Formula presented.)-tree, (Formula presented.)-tree and Bitmap. However, inequality joins have received little attention and queries containing such joins are notably very slow. In this paper, we introduce fast inequality join algorithms based on sorted arrays and space-efficient bit-arrays. We further introduce a simple method to estimate the selectivity of inequality joins which is then used to optimize multiple predicate queries and multi-way joins. Moreover, we study an incremental inequality join algorithm to handle scenarios where data keeps changing. We have implemented a centralized version of these algorithms on top of PostgreSQL, a distributed version on top of Spark SQL, and an existing data cleaning system, Nadeef. By comparing our algorithms against well-known optimization techniques for inequality joins, we show our solution is more scalable and several orders of magnitude faster. © 2016 Springer-Verlag Berlin Heidelberg

  1. Accounting Fundamentals and the Variation of Stock Price: Factoring in the Investment Scalability

    OpenAIRE

    Sumiyana, Sumiyana; Baridwan, Zaki; Sugiri, Slamet; Hartono, Jogiyanto

    2010-01-01

    This study develops a new return model with respect to accounting fundamentals. The new return model is based on Chen and Zhang (2007). This study takes into account theinvestment scalability information. Specifically, this study splitsthe scale of firm’s operations into short-run and long-runinvestment scalabilities. We document that five accounting fun-damentals explain the variation of annual stock return. Thefactors, comprised book value, earnings yield, short-run andlong-run investment s...

  2. Embedded High Performance Scalable Computing Systems

    National Research Council Canada - National Science Library

    Ngo, David

    2003-01-01

    The Embedded High Performance Scalable Computing Systems (EHPSCS) program is a cooperative agreement between Sanders, A Lockheed Martin Company and DARPA that ran for three years, from Apr 1995 - Apr 1998...

  3. A system to build distributed multivariate models and manage disparate data sharing policies: implementation in the scalable national network for effectiveness research.

    Science.gov (United States)

    Meeker, Daniella; Jiang, Xiaoqian; Matheny, Michael E; Farcas, Claudiu; D'Arcy, Michel; Pearlman, Laura; Nookala, Lavanya; Day, Michele E; Kim, Katherine K; Kim, Hyeoneui; Boxwala, Aziz; El-Kareh, Robert; Kuo, Grace M; Resnic, Frederic S; Kesselman, Carl; Ohno-Machado, Lucila

    2015-11-01

    Centralized and federated models for sharing data in research networks currently exist. To build multivariate data analysis for centralized networks, transfer of patient-level data to a central computation resource is necessary. The authors implemented distributed multivariate models for federated networks in which patient-level data is kept at each site and data exchange policies are managed in a study-centric manner. The objective was to implement infrastructure that supports the functionality of some existing research networks (e.g., cohort discovery, workflow management, and estimation of multivariate analytic models on centralized data) while adding additional important new features, such as algorithms for distributed iterative multivariate models, a graphical interface for multivariate model specification, synchronous and asynchronous response to network queries, investigator-initiated studies, and study-based control of staff, protocols, and data sharing policies. Based on the requirements gathered from statisticians, administrators, and investigators from multiple institutions, the authors developed infrastructure and tools to support multisite comparative effectiveness studies using web services for multivariate statistical estimation in the SCANNER federated network. The authors implemented massively parallel (map-reduce) computation methods and a new policy management system to enable each study initiated by network participants to define the ways in which data may be processed, managed, queried, and shared. The authors illustrated the use of these systems among institutions with highly different policies and operating under different state laws. Federated research networks need not limit distributed query functionality to count queries, cohort discovery, or independently estimated analytic models. Multivariate analyses can be efficiently and securely conducted without patient-level data transport, allowing institutions with strict local data storage

  4. Final Report, Center for Programming Models for Scalable Parallel Computing: Co-Array Fortran, Grant Number DE-FC02-01ER25505

    Energy Technology Data Exchange (ETDEWEB)

    Robert W. Numrich

    2008-04-22

    The major accomplishment of this project is the production of CafLib, an 'object-oriented' parallel numerical library written in Co-Array Fortran. CafLib contains distributed objects such as block vectors and block matrices along with procedures, attached to each object, that perform basic linear algebra operations such as matrix multiplication, matrix transpose and LU decomposition. It also contains constructors and destructors for each object that hide the details of data decomposition from the programmer, and it contains collective operations that allow the programmer to calculate global reductions, such as global sums, global minima and global maxima, as well as vector and matrix norms of several kinds. CafLib is designed to be extensible in such a way that programmers can define distributed grid and field objects, based on vector and matrix objects from the library, for finite difference algorithms to solve partial differential equations. A very important extra benefit that resulted from the project is the inclusion of the co-array programming model in the next Fortran standard called Fortran 2008. It is the first parallel programming model ever included as a standard part of the language. Co-arrays will be a supported feature in all Fortran compilers, and the portability provided by standardization will encourage a large number of programmers to adopt it for new parallel application development. The combination of object-oriented programming in Fortran 2003 with co-arrays in Fortran 2008 provides a very powerful programming model for high-performance scientific computing. Additional benefits from the project, beyond the original goal, include a programto provide access to the co-array model through access to the Cray compiler as a resource for teaching and research. Several academics, for the first time, included the co-array model as a topic in their courses on parallel computing. A separate collaborative project with LANL and PNNL showed how to

  5. Scalable, sustainable cost-effective surgical care: a model for safety and quality in the developing world, part III: impact and sustainability.

    Science.gov (United States)

    Campbell, Alex; Restrepo, Carolina; Mackay, Don; Sherman, Randy; Varma, Ajit; Ayala, Ruben; Sarma, Hiteswar; Deshpande, Gaurav; Magee, William

    2014-09-01

    The Guwahati Comprehensive Cleft Care Center (GCCCC) utilizes a high-volume, subspecialized institution to provide safe, quality, and comprehensive and cost-effective surgical care to a highly vulnerable patient population. The GCCCC utilized a diagonal model of surgical care delivery, with vertical inputs of mission-based care transitioning to investments in infrastructure and human capital to create a sustainable, local care delivery system. Over the first 2.5 years of service (May 2011-November 2013), the GCCCC made significant advances in numerous areas. Progress was meticulously documented to evaluate performance and provide transparency to stakeholders including donors, government officials, medical oversight bodies, employees, and patients. During this time period, the GCCCC provided free operations to 7,034 patients, with improved safety, outcomes, and multidisciplinary services while dramatically decreasing costs and increasing investments in the local community. The center has become a regional referral cleft center, and governments of surrounding states have contracted the GCCCC to provide care for their citizens with cleft lip and cleft palate. Additional regional and global impact is anticipated through continued investments into education and training, comprehensive services, and research and outcomes. The success of this public private partnership demonstrates the value of this model of surgical care in the developing world, and offers a blueprint for reproduction. The GCCCC experience has been consistent with previous studies demonstrating a positive volume-outcomes relationship, and provides evidence for the value of the specialty hospital model for surgical delivery in the developing world.

  6. Resource-aware complexity scalability for mobile MPEG encoding

    NARCIS (Netherlands)

    Mietens, S.O.; With, de P.H.N.; Hentschel, C.; Panchanatan, S.; Vasudev, B.

    2004-01-01

    Complexity scalability attempts to scale the required resources of an algorithm with the chose quality settings, in order to broaden the application range. In this paper, we present complexity-scalable MPEG encoding of which the core processing modules are modified for scalability. Scalability is

  7. On the scalability of uncoordinated multiple access for the Internet of Things

    KAUST Repository

    Chisci, Giovanni

    2017-11-16

    The Internet of things (IoT) will entail massive number of wireless connections with sporadic traffic patterns. To support the IoT traffic, several technologies are evolving to support low power wide area (LPWA) wireless communications. However, LPWA networks rely on variations of uncoordinated spectrum access, either for data transmissions or scheduling requests, thus imposing a scalability problem to the IoT. This paper presents a novel spatiotemporal model to study the scalability of the ALOHA medium access. In particular, the developed mathematical model relies on stochastic geometry and queueing theory to account for spatial and temporal attributes of the IoT. To this end, the scalability of the ALOHA is characterized by the percentile of IoT devices that can be served while keeping their queues stable. The results highlight the scalability problem of ALOHA and quantify the extend to which ALOHA can support in terms of number of devices, traffic requirement, and transmission rate.

  8. NPTool: Towards Scalability and Reliability of Business Process Management

    Science.gov (United States)

    Braghetto, Kelly Rosa; Ferreira, João Eduardo; Pu, Calton

    Currently one important challenge in business process management is provide at the same time scalability and reliability of business process executions. This difficulty becomes more accentuated when the execution control assumes complex countless business processes. This work presents NavigationPlanTool (NPTool), a tool to control the execution of business processes. NPTool is supported by Navigation Plan Definition Language (NPDL), a language for business processes specification that uses process algebra as formal foundation. NPTool implements the NPDL language as a SQL extension. The main contribution of this paper is a description of the NPTool showing how the process algebra features combined with a relational database model can be used to provide a scalable and reliable control in the execution of business processes. The next steps of NPTool include reuse of control-flow patterns and support to data flow management.

  9. Scalable Combinatorial Tools for Health Disparities Research

    Directory of Open Access Journals (Sweden)

    Michael A. Langston

    2014-10-01

    Full Text Available Despite staggering investments made in unraveling the human genome, current estimates suggest that as much as 90% of the variance in cancer and chronic diseases can be attributed to factors outside an individual’s genetic endowment, particularly to environmental exposures experienced across his or her life course. New analytical approaches are clearly required as investigators turn to complicated systems theory and ecological, place-based and life-history perspectives in order to understand more clearly the relationships between social determinants, environmental exposures and health disparities. While traditional data analysis techniques remain foundational to health disparities research, they are easily overwhelmed by the ever-increasing size and heterogeneity of available data needed to illuminate latent gene x environment interactions. This has prompted the adaptation and application of scalable combinatorial methods, many from genome science research, to the study of population health. Most of these powerful tools are algorithmically sophisticated, highly automated and mathematically abstract. Their utility motivates the main theme of this paper, which is to describe real applications of innovative transdisciplinary models and analyses in an effort to help move the research community closer toward identifying the causal mechanisms and associated environmental contexts underlying health disparities. The public health exposome is used as a contemporary focus for addressing the complex nature of this subject.

  10. Scalable, sustainable cost-effective surgical care: a model for safety and quality in the developing world, part I: challenge and commitment.

    Science.gov (United States)

    Campbell, Alex; Restrepo, Carolina; Mackay, Don; Sherman, Randy; Varma, Ajit; Ayala, Ruben; Sarma, Hiteswar; Deshpande, Gaurav; Magee, William

    2014-09-01

    With an estimated backlog of 4,000,000 patients worldwide, cleft lip and cleft palate remain a stark example of the global burden of surgical disease. The need for a new paradigm in global surgery has been increasingly recognized by governments, funding agencies, and professionals to exponentially expand care while emphasizing safety and quality. This three-part article examines the evolution of the Operation Smile Guwahati Comprehensive Cleft Care Center (GCCCC) as an innovative model for sustainable cleft care in the developing world. The GCCCC is the result of a unique public-private partnership between government, charity, and private enterprise. In 2009, Operation Smile, the Government of Assam, the National Rural Health Mission, and the Tata Group joined together to work towards the common goal of creating a center of excellence in cleft care for the region. This partnership combined expertise in medical care and training, organizational structure and management, local health care infrastructure, and finance. A state-of-the-art surgical facility was constructed in Guwahati, Assam which includes a modern integrated operating suite with an open layout, advanced surgical equipment, sophisticated anesthesia and monitoring capabilities, central medical gases, and sterilization facilities. The combination of established leaders and dreamers from different arenas combined to create a synergy of ambitions, resources, and compassion that became the backbone of success in Guwahati.

  11. A massively parallel GPU-accelerated model for analysis of fully nonlinear free surface waves

    DEFF Research Database (Denmark)

    Engsig-Karup, Allan Peter; Madsen, Morten G.; Glimberg, Stefan Lemvig

    2011-01-01

    -storage flexible-order accurate finite difference method that is known to be efficient and scalable on a CPU core (single thread). To achieve parallel performance of the relatively complex numerical model, we investigate a new trend in high-performance computing where many-core GPUs are utilized as high......-throughput co-processors to the CPU. We describe and demonstrate how this approach makes it possible to do fast desktop computations for large nonlinear wave problems in numerical wave tanks (NWTs) with close to 50/100 million total grid points in double/ single precision with 4 GB global device memory...... available. A new code base has been developed in C++ and compute unified device architecture C and is found to improve the runtime more than an order in magnitude in double precision arithmetic for the same accuracy over an existing CPU (single thread) Fortran 90 code when executed on a single modern GPU...

  12. JPEG2000-Compatible Scalable Scheme for Wavelet-Based Video Coding

    Directory of Open Access Journals (Sweden)

    Thomas André

    2007-03-01

    Full Text Available We present a simple yet efficient scalable scheme for wavelet-based video coders, able to provide on-demand spatial, temporal, and SNR scalability, and fully compatible with the still-image coding standard JPEG2000. Whereas hybrid video coders must undergo significant changes in order to support scalability, our coder only requires a specific wavelet filter for temporal analysis, as well as an adapted bit allocation procedure based on models of rate-distortion curves. Our study shows that scalably encoded sequences have the same or almost the same quality than nonscalably encoded ones, without a significant increase in complexity. A full compatibility with Motion JPEG2000, which tends to be a serious candidate for the compression of high-definition video sequences, is ensured.

  13. JPEG2000-Compatible Scalable Scheme for Wavelet-Based Video Coding

    Directory of Open Access Journals (Sweden)

    André Thomas

    2007-01-01

    Full Text Available We present a simple yet efficient scalable scheme for wavelet-based video coders, able to provide on-demand spatial, temporal, and SNR scalability, and fully compatible with the still-image coding standard JPEG2000. Whereas hybrid video coders must undergo significant changes in order to support scalability, our coder only requires a specific wavelet filter for temporal analysis, as well as an adapted bit allocation procedure based on models of rate-distortion curves. Our study shows that scalably encoded sequences have the same or almost the same quality than nonscalably encoded ones, without a significant increase in complexity. A full compatibility with Motion JPEG2000, which tends to be a serious candidate for the compression of high-definition video sequences, is ensured.

  14. Scalable Density-Based Subspace Clustering

    DEFF Research Database (Denmark)

    Müller, Emmanuel; Assent, Ira; Günnemann, Stephan

    2011-01-01

    For knowledge discovery in high dimensional databases, subspace clustering detects clusters in arbitrary subspace projections. Scalability is a crucial issue, as the number of possible projections is exponential in the number of dimensions. We propose a scalable density-based subspace clustering...... method that steers mining to few selected subspace clusters. Our novel steering technique reduces subspace processing by identifying and clustering promising subspaces and their combinations directly. Thereby, it narrows down the search space while maintaining accuracy. Thorough experiments on real...... and synthetic databases show that steering is efficient and scalable, with high quality results. For future work, our steering paradigm for density-based subspace clustering opens research potential for speeding up other subspace clustering approaches as well....

  15. Software performance and scalability a quantitative approach

    CERN Document Server

    Liu, Henry H

    2009-01-01

    Praise from the Reviewers:"The practicality of the subject in a real-world situation distinguishes this book from othersavailable on the market."—Professor Behrouz Far, University of Calgary"This book could replace the computer organization texts now in use that every CS and CpEstudent must take. . . . It is much needed, well written, and thoughtful."—Professor Larry Bernstein, Stevens Institute of TechnologyA distinctive, educational text onsoftware performance and scalabilityThis is the first book to take a quantitative approach to the subject of software performance and scalability

  16. Content-Aware Scalability-Type Selection for Rate Adaptation of Scalable Video

    Directory of Open Access Journals (Sweden)

    Tekalp A Murat

    2007-01-01

    Full Text Available Scalable video coders provide different scaling options, such as temporal, spatial, and SNR scalabilities, where rate reduction by discarding enhancement layers of different scalability-type results in different kinds and/or levels of visual distortion depend on the content and bitrate. This dependency between scalability type, video content, and bitrate is not well investigated in the literature. To this effect, we first propose an objective function that quantifies flatness, blockiness, blurriness, and temporal jerkiness artifacts caused by rate reduction by spatial size, frame rate, and quantization parameter scaling. Next, the weights of this objective function are determined for different content (shot types and different bitrates using a training procedure with subjective evaluation. Finally, a method is proposed for choosing the best scaling type for each temporal segment that results in minimum visual distortion according to this objective function given the content type of temporal segments. Two subjective tests have been performed to validate the proposed procedure for content-aware selection of the best scalability type on soccer videos. Soccer videos scaled from 600 kbps to 100 kbps by the proposed content-aware selection of scalability type have been found visually superior to those that are scaled using a single scalability option over the whole sequence.

  17. Myria: Scalable Analytics as a Service

    Science.gov (United States)

    Howe, B.; Halperin, D.; Whitaker, A.

    2014-12-01

    At the UW eScience Institute, we're working to empower non-experts, especially in the sciences, to write and use data-parallel algorithms. To this end, we are building Myria, a web-based platform for scalable analytics and data-parallel programming. Myria's internal model of computation is the relational algebra extended with iteration, such that every program is inherently data-parallel, just as every query in a database is inherently data-parallel. But unlike databases, iteration is a first class concept, allowing us to express machine learning tasks, graph traversal tasks, and more. Programs can be expressed in a number of languages and can be executed on a number of execution environments, but we emphasize a particular language called MyriaL that supports both imperative and declarative styles and a particular execution engine called MyriaX that uses an in-memory column-oriented representation and asynchronous iteration. We deliver Myria over the web as a service, providing an editor, performance analysis tools, and catalog browsing features in a single environment. We find that this web-based "delivery vector" is critical in reaching non-experts: they are insulated from irrelevant effort technical work associated with installation, configuration, and resource management. The MyriaX backend, one of several execution runtimes we support, is a main-memory, column-oriented, RDBMS-on-the-worker system that supports cyclic data flows as a first-class citizen and has been shown to outperform competitive systems on 100-machine cluster sizes. I will describe the Myria system, give a demo, and present some new results in large-scale oceanographic microbiology.

  18. Using scalable vector graphics to evolve art

    NARCIS (Netherlands)

    den Heijer, E.; Eiben, A. E.

    2016-01-01

    In this paper, we describe our investigations of the use of scalable vector graphics as a genotype representation in evolutionary art. We describe the technical aspects of using SVG in evolutionary art, and explain our custom, SVG specific operators initialisation, mutation and crossover. We perform

  19. Scalable fast multipole accelerated vortex methods

    KAUST Repository

    Hu, Qi; Gumerov, Nail A.; Yokota, Rio; Barba, Lorena A.; Duraiswami, Ramani

    2014-01-01

    -node communication and load balance efficiently, with only a small parallel construction overhead. This algorithm can scale to large-sized clusters showing both strong and weak scalability. Careful error and timing trade-off analysis are also performed for the cutoff

  20. Scalable Domain Decomposed Monte Carlo Particle Transport

    Energy Technology Data Exchange (ETDEWEB)

    O' Brien, Matthew Joseph [Univ. of California, Davis, CA (United States)

    2013-12-05

    In this dissertation, we present the parallel algorithms necessary to run domain decomposed Monte Carlo particle transport on large numbers of processors (millions of processors). Previous algorithms were not scalable, and the parallel overhead became more computationally costly than the numerical simulation.

  1. Scalable optical switches for computing applications

    NARCIS (Netherlands)

    White, I.H.; Aw, E.T.; Williams, K.A.; Wang, Haibo; Wonfor, A.; Penty, R.V.

    2009-01-01

    A scalable photonic interconnection network architecture is proposed whereby a Clos network is populated with broadcast-and-select stages. This enables the efficient exploitation of an emerging class of photonic integrated switch fabric. A low distortion space switch technology based on recently

  2. Responsive, Flexible and Scalable Broader Impacts (Invited)

    Science.gov (United States)

    Decharon, A.; Companion, C.; Steinman, M.

    2010-12-01

    In many educator professional development workshops, scientists present content in a slideshow-type format and field questions afterwards. Drawbacks of this approach include: inability to begin the lecture with content that is responsive to audience needs; lack of flexible access to specific material within the linear presentation; and “Q&A” sessions are not easily scalable to broader audiences. Often this type of traditional interaction provides little direct benefit to the scientists. The Centers for Ocean Sciences Education Excellence - Ocean Systems (COSEE-OS) applies the technique of concept mapping with demonstrated effectiveness in helping scientists and educators “get on the same page” (deCharon et al., 2009). A key aspect is scientist professional development geared towards improving face-to-face and online communication with non-scientists. COSEE-OS promotes scientist-educator collaboration, tests the application of scientist-educator maps in new contexts through webinars, and is piloting the expansion of maps as long-lived resources for the broader community. Collaboration - COSEE-OS has developed and tested a workshop model bringing scientists and educators together in a peer-oriented process, often clarifying common misconceptions. Scientist-educator teams develop online concept maps that are hyperlinked to “assets” (i.e., images, videos, news) and are responsive to the needs of non-scientist audiences. In workshop evaluations, 91% of educators said that the process of concept mapping helped them think through science topics and 89% said that concept mapping helped build a bridge of communication with scientists (n=53). Application - After developing a concept map, with COSEE-OS staff assistance, scientists are invited to give webinar presentations that include live “Q&A” sessions. The webinars extend the reach of scientist-created concept maps to new contexts, both geographically and topically (e.g., oil spill), with a relatively small

  3. Scalable Nonlinear AUC Maximization Methods

    OpenAIRE

    Khalid, Majdi; Ray, Indrakshi; Chitsaz, Hamidreza

    2017-01-01

    The area under the ROC curve (AUC) is a measure of interest in various machine learning and data mining applications. It has been widely used to evaluate classification performance on heavily imbalanced data. The kernelized AUC maximization machines have established a superior generalization ability compared to linear AUC machines because of their capability in modeling the complex nonlinear structure underlying most real world-data. However, the high training complexity renders the kernelize...

  4. Accounting Fundamentals and the Variation of Stock Price: Factoring in the Investment Scalability

    Directory of Open Access Journals (Sweden)

    Sumiyana Sumiyana

    2010-05-01

    Full Text Available This study develops a new return model with respect to accounting fundamentals. The new return model is based on Chen and Zhang (2007. This study takes into account theinvestment scalability information. Specifically, this study splitsthe scale of firm’s operations into short-run and long-runinvestment scalabilities. We document that five accounting fun-damentals explain the variation of annual stock return. Thefactors, comprised book value, earnings yield, short-run andlong-run investment scalabilities, and growth opportunities, co associate positively with stock price. The remaining factor,which is the pure interest rate, is negatively related to annualstock return. This study finds that inducing short-run and long-run investment scalabilities into the model could improve the degree of association. In other words, they have value rel-evance. Finally, this study suggests that basic trading strategieswill improve if investors revert to the accounting fundamentals. Keywords: accounting fundamentals; book value; earnings yield; growth opportuni­ties; short­run and long­run investment scalabilities; trading strategy;value relevance

  5. Scalable Algorithms for Adaptive Statistical Designs

    Directory of Open Access Journals (Sweden)

    Robert Oehmke

    2000-01-01

    Full Text Available We present a scalable, high-performance solution to multidimensional recurrences that arise in adaptive statistical designs. Adaptive designs are an important class of learning algorithms for a stochastic environment, and we focus on the problem of optimally assigning patients to treatments in clinical trials. While adaptive designs have significant ethical and cost advantages, they are rarely utilized because of the complexity of optimizing and analyzing them. Computational challenges include massive memory requirements, few calculations per memory access, and multiply-nested loops with dynamic indices. We analyze the effects of various parallelization options, and while standard approaches do not work well, with effort an efficient, highly scalable program can be developed. This allows us to solve problems thousands of times more complex than those solved previously, which helps make adaptive designs practical. Further, our work applies to many other problems involving neighbor recurrences, such as generalized string matching.

  6. Scalable Packet Classification with Hash Tables

    Science.gov (United States)

    Wang, Pi-Chung

    In the last decade, the technique of packet classification has been widely deployed in various network devices, including routers, firewalls and network intrusion detection systems. In this work, we improve the performance of packet classification by using multiple hash tables. The existing hash-based algorithms have superior scalability with respect to the required space; however, their search performance may not be comparable to other algorithms. To improve the search performance, we propose a tuple reordering algorithm to minimize the number of accessed hash tables with the aid of bitmaps. We also use pre-computation to ensure the accuracy of our search procedure. Performance evaluation based on both real and synthetic filter databases shows that our scheme is effective and scalable and the pre-computation cost is moderate.

  7. Scalable fabrication of perovskite solar cells

    Energy Technology Data Exchange (ETDEWEB)

    Li, Zhen; Klein, Talysa R.; Kim, Dong Hoe; Yang, Mengjin; Berry, Joseph J.; van Hest, Maikel F. A. M.; Zhu, Kai

    2018-03-27

    Perovskite materials use earth-abundant elements, have low formation energies for deposition and are compatible with roll-to-roll and other high-volume manufacturing techniques. These features make perovskite solar cells (PSCs) suitable for terawatt-scale energy production with low production costs and low capital expenditure. Demonstrations of performance comparable to that of other thin-film photovoltaics (PVs) and improvements in laboratory-scale cell stability have recently made scale up of this PV technology an intense area of research focus. Here, we review recent progress and challenges in scaling up PSCs and related efforts to enable the terawatt-scale manufacturing and deployment of this PV technology. We discuss common device and module architectures, scalable deposition methods and progress in the scalable deposition of perovskite and charge-transport layers. We also provide an overview of device and module stability, module-level characterization techniques and techno-economic analyses of perovskite PV modules.

  8. Scalable Atomistic Simulation Algorithms for Materials Research

    Directory of Open Access Journals (Sweden)

    Aiichiro Nakano

    2002-01-01

    Full Text Available A suite of scalable atomistic simulation programs has been developed for materials research based on space-time multiresolution algorithms. Design and analysis of parallel algorithms are presented for molecular dynamics (MD simulations and quantum-mechanical (QM calculations based on the density functional theory. Performance tests have been carried out on 1,088-processor Cray T3E and 1,280-processor IBM SP3 computers. The linear-scaling algorithms have enabled 6.44-billion-atom MD and 111,000-atom QM calculations on 1,024 SP3 processors with parallel efficiency well over 90%. production-quality programs also feature wavelet-based computational-space decomposition for adaptive load balancing, spacefilling-curve-based adaptive data compression with user-defined error bound for scalable I/O, and octree-based fast visibility culling for immersive and interactive visualization of massive simulation data.

  9. Scalable manufacturing processes with soft materials

    OpenAIRE

    White, Edward; Case, Jennifer; Kramer, Rebecca

    2014-01-01

    The emerging field of soft robotics will benefit greatly from new scalable manufacturing techniques for responsive materials. Currently, most of soft robotic examples are fabricated one-at-a-time, using techniques borrowed from lithography and 3D printing to fabricate molds. This limits both the maximum and minimum size of robots that can be fabricated, and hinders batch production, which is critical to gain wider acceptance for soft robotic systems. We have identified electrical structures, ...

  10. Architecture Knowledge for Evaluating Scalable Databases

    Science.gov (United States)

    2015-01-16

    Architecture Knowledge for Evaluating Scalable Databases 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Nurgaliev... Scala , Erlang, Javascript Cursor-based queries Supported, Not Supported JOIN queries Supported, Not Supported Complex data types Lists, maps, sets...is therefore needed, using technology such as machine learning to extract content from product documentation. The terminology used in the database

  11. Randomized Algorithms for Scalable Machine Learning

    OpenAIRE

    Kleiner, Ariel Jacob

    2012-01-01

    Many existing procedures in machine learning and statistics are computationally intractable in the setting of large-scale data. As a result, the advent of rapidly increasing dataset sizes, which should be a boon yielding improved statistical performance, instead severely blunts the usefulness of a variety of existing inferential methods. In this work, we use randomness to ameliorate this lack of scalability by reducing complex, computationally difficult inferential problems to larger sets o...

  12. Bitcoin-NG: A Scalable Blockchain Protocol

    OpenAIRE

    Eyal, Ittay; Gencer, Adem Efe; Sirer, Emin Gun; van Renesse, Robbert

    2015-01-01

    Cryptocurrencies, based on and led by Bitcoin, have shown promise as infrastructure for pseudonymous online payments, cheap remittance, trustless digital asset exchange, and smart contracts. However, Bitcoin-derived blockchain protocols have inherent scalability limits that trade-off between throughput and latency and withhold the realization of this potential. This paper presents Bitcoin-NG, a new blockchain protocol designed to scale. Based on Bitcoin's blockchain protocol, Bitcoin-NG is By...

  13. Scuba: scalable kernel-based gene prioritization.

    Science.gov (United States)

    Zampieri, Guido; Tran, Dinh Van; Donini, Michele; Navarin, Nicolò; Aiolli, Fabio; Sperduti, Alessandro; Valle, Giorgio

    2018-01-25

    The uncovering of genes linked to human diseases is a pressing challenge in molecular biology and precision medicine. This task is often hindered by the large number of candidate genes and by the heterogeneity of the available information. Computational methods for the prioritization of candidate genes can help to cope with these problems. In particular, kernel-based methods are a powerful resource for the integration of heterogeneous biological knowledge, however, their practical implementation is often precluded by their limited scalability. We propose Scuba, a scalable kernel-based method for gene prioritization. It implements a novel multiple kernel learning approach, based on a semi-supervised perspective and on the optimization of the margin distribution. Scuba is optimized to cope with strongly unbalanced settings where known disease genes are few and large scale predictions are required. Importantly, it is able to efficiently deal both with a large amount of candidate genes and with an arbitrary number of data sources. As a direct consequence of scalability, Scuba integrates also a new efficient strategy to select optimal kernel parameters for each data source. We performed cross-validation experiments and simulated a realistic usage setting, showing that Scuba outperforms a wide range of state-of-the-art methods. Scuba achieves state-of-the-art performance and has enhanced scalability compared to existing kernel-based approaches for genomic data. This method can be useful to prioritize candidate genes, particularly when their number is large or when input data is highly heterogeneous. The code is freely available at https://github.com/gzampieri/Scuba .

  14. Optimizing Nanoelectrode Arrays for Scalable Intracellular Electrophysiology.

    Science.gov (United States)

    Abbott, Jeffrey; Ye, Tianyang; Ham, Donhee; Park, Hongkun

    2018-03-20

    , clarifying how the nanoelectrode attains intracellular access. This understanding will be translated into a circuit model for the nanobio interface, which we will then use to lay out the strategies for improving the interface. The intracellular interface of the nanoelectrode is currently inferior to that of the patch clamp electrode; reaching this benchmark will be an exciting challenge that involves optimization of electrode geometries, materials, chemical modifications, electroporation protocols, and recording/stimulation electronics, as we describe in the Account. Another important theme of this Account, beyond the optimization of the individual nanoelectrode-cell interface, is the scalability of the nanoscale electrodes. We will discuss this theme using a recent development from our groups as an example, where an array of ca. 1000 nanoelectrode pixels fabricated on a CMOS integrated circuit chip performs parallel intracellular recording from a few hundreds of cardiomyocytes, which marks a new milestone in electrophysiology.

  15. A scalable distributed RRT for motion planning

    KAUST Repository

    Jacobs, Sam Ade

    2013-05-01

    Rapidly-exploring Random Tree (RRT), like other sampling-based motion planning methods, has been very successful in solving motion planning problems. Even so, sampling-based planners cannot solve all problems of interest efficiently, so attention is increasingly turning to parallelizing them. However, one challenge in parallelizing RRT is the global computation and communication overhead of nearest neighbor search, a key operation in RRTs. This is a critical issue as it limits the scalability of previous algorithms. We present two parallel algorithms to address this problem. The first algorithm extends existing work by introducing a parameter that adjusts how much local computation is done before a global update. The second algorithm radially subdivides the configuration space into regions, constructs a portion of the tree in each region in parallel, and connects the subtrees,i removing cycles if they exist. By subdividing the space, we increase computation locality enabling a scalable result. We show that our approaches are scalable. We present results demonstrating almost linear scaling to hundreds of processors on a Linux cluster and a Cray XE6 machine. © 2013 IEEE.

  16. DISP: Optimizations towards Scalable MPI Startup

    Energy Technology Data Exchange (ETDEWEB)

    Fu, Huansong [Florida State University, Tallahassee; Pophale, Swaroop S [ORNL; Gorentla Venkata, Manjunath [ORNL; Yu, Weikuan [Florida State University, Tallahassee

    2016-01-01

    Despite the popularity of MPI for high performance computing, the startup of MPI programs faces a scalability challenge as both the execution time and memory consumption increase drastically at scale. We have examined this problem using the collective modules of Cheetah and Tuned in Open MPI as representative implementations. Previous improvements for collectives have focused on algorithmic advances and hardware off-load. In this paper, we examine the startup cost of the collective module within a communicator and explore various techniques to improve its efficiency and scalability. Accordingly, we have developed a new scalable startup scheme with three internal techniques, namely Delayed Initialization, Module Sharing and Prediction-based Topology Setup (DISP). Our DISP scheme greatly benefits the collective initialization of the Cheetah module. At the same time, it helps boost the performance of non-collective initialization in the Tuned module. We evaluate the performance of our implementation on Titan supercomputer at ORNL with up to 4096 processes. The results show that our delayed initialization can speed up the startup of Tuned and Cheetah by an average of 32.0% and 29.2%, respectively, our module sharing can reduce the memory consumption of Tuned and Cheetah by up to 24.1% and 83.5%, respectively, and our prediction-based topology setup can speed up the startup of Cheetah by up to 80%.

  17. A scalable distributed RRT for motion planning

    KAUST Repository

    Jacobs, Sam Ade; Stradford, Nicholas; Rodriguez, Cesar; Thomas, Shawna; Amato, Nancy M.

    2013-01-01

    Rapidly-exploring Random Tree (RRT), like other sampling-based motion planning methods, has been very successful in solving motion planning problems. Even so, sampling-based planners cannot solve all problems of interest efficiently, so attention is increasingly turning to parallelizing them. However, one challenge in parallelizing RRT is the global computation and communication overhead of nearest neighbor search, a key operation in RRTs. This is a critical issue as it limits the scalability of previous algorithms. We present two parallel algorithms to address this problem. The first algorithm extends existing work by introducing a parameter that adjusts how much local computation is done before a global update. The second algorithm radially subdivides the configuration space into regions, constructs a portion of the tree in each region in parallel, and connects the subtrees,i removing cycles if they exist. By subdividing the space, we increase computation locality enabling a scalable result. We show that our approaches are scalable. We present results demonstrating almost linear scaling to hundreds of processors on a Linux cluster and a Cray XE6 machine. © 2013 IEEE.

  18. Scalable robotic biofabrication of tissue spheroids

    International Nuclear Information System (INIS)

    Mehesz, A Nagy; Hajdu, Z; Visconti, R P; Markwald, R R; Mironov, V; Brown, J; Beaver, W; Da Silva, J V L

    2011-01-01

    Development of methods for scalable biofabrication of uniformly sized tissue spheroids is essential for tissue spheroid-based bioprinting of large size tissue and organ constructs. The most recent scalable technique for tissue spheroid fabrication employs a micromolded recessed template prepared in a non-adhesive hydrogel, wherein the cells loaded into the template self-assemble into tissue spheroids due to gravitational force. In this study, we present an improved version of this technique. A new mold was designed to enable generation of 61 microrecessions in each well of a 96-well plate. The microrecessions were seeded with cells using an EpMotion 5070 automated pipetting machine. After 48 h of incubation, tissue spheroids formed at the bottom of each microrecession. To assess the quality of constructs generated using this technology, 600 tissue spheroids made by this method were compared with 600 spheroids generated by the conventional hanging drop method. These analyses showed that tissue spheroids fabricated by the micromolded method are more uniform in diameter. Thus, use of micromolded recessions in a non-adhesive hydrogel, combined with automated cell seeding, is a reliable method for scalable robotic fabrication of uniform-sized tissue spheroids.

  19. Scalable robotic biofabrication of tissue spheroids

    Energy Technology Data Exchange (ETDEWEB)

    Mehesz, A Nagy; Hajdu, Z; Visconti, R P; Markwald, R R; Mironov, V [Advanced Tissue Biofabrication Center, Department of Regenerative Medicine and Cell Biology, Medical University of South Carolina, Charleston, SC (United States); Brown, J [Department of Mechanical Engineering, Clemson University, Clemson, SC (United States); Beaver, W [York Technical College, Rock Hill, SC (United States); Da Silva, J V L, E-mail: mironovv@musc.edu [Renato Archer Information Technology Center-CTI, Campinas (Brazil)

    2011-06-15

    Development of methods for scalable biofabrication of uniformly sized tissue spheroids is essential for tissue spheroid-based bioprinting of large size tissue and organ constructs. The most recent scalable technique for tissue spheroid fabrication employs a micromolded recessed template prepared in a non-adhesive hydrogel, wherein the cells loaded into the template self-assemble into tissue spheroids due to gravitational force. In this study, we present an improved version of this technique. A new mold was designed to enable generation of 61 microrecessions in each well of a 96-well plate. The microrecessions were seeded with cells using an EpMotion 5070 automated pipetting machine. After 48 h of incubation, tissue spheroids formed at the bottom of each microrecession. To assess the quality of constructs generated using this technology, 600 tissue spheroids made by this method were compared with 600 spheroids generated by the conventional hanging drop method. These analyses showed that tissue spheroids fabricated by the micromolded method are more uniform in diameter. Thus, use of micromolded recessions in a non-adhesive hydrogel, combined with automated cell seeding, is a reliable method for scalable robotic fabrication of uniform-sized tissue spheroids.

  20. Conscientiousness at the workplace: Applying mixture IRT to investigate scalability and predictive validity

    NARCIS (Netherlands)

    Egberink, I.J.L.; Meijer, R.R.; Veldkamp, Bernard P.

    2010-01-01

    Mixture item response theory (IRT) models have been used to assess multidimensionality of the construct being measured and to detect different response styles for different groups. In this study a mixture version of the graded response model was applied to investigate scalability and predictive

  1. Conscientiousness in the workplace : Applying mixture IRT to investigate scalability and predictive validity

    NARCIS (Netherlands)

    Egberink, I.J.L.; Meijer, R.R.; Veldkamp, B.P.

    Mixture item response theory (IRT) models have been used to assess multidimensionality of the construct being measured and to detect different response styles for different groups. In this study a mixture version of the graded response model was applied to investigate scalability and predictive

  2. Silicon nanophotonics for scalable quantum coherent feedback networks

    Energy Technology Data Exchange (ETDEWEB)

    Sarovar, Mohan; Brif, Constantin [Sandia National Laboratories, Livermore, CA (United States); Soh, Daniel B.S. [Sandia National Laboratories, Livermore, CA (United States); Stanford University, Edward L. Ginzton Laboratory, Stanford, CA (United States); Cox, Jonathan; DeRose, Christopher T.; Camacho, Ryan; Davids, Paul [Sandia National Laboratories, Albuquerque, NM (United States)

    2016-12-15

    The emergence of coherent quantum feedback control (CQFC) as a new paradigm for precise manipulation of dynamics of complex quantum systems has led to the development of efficient theoretical modeling and simulation tools and opened avenues for new practical implementations. This work explores the applicability of the integrated silicon photonics platform for implementing scalable CQFC networks. If proven successful, on-chip implementations of these networks would provide scalable and efficient nanophotonic components for autonomous quantum information processing devices and ultra-low-power optical processing systems at telecommunications wavelengths. We analyze the strengths of the silicon photonics platform for CQFC applications and identify the key challenges to both the theoretical formalism and experimental implementations. In particular, we determine specific extensions to the theoretical CQFC framework (which was originally developed with bulk-optics implementations in mind), required to make it fully applicable to modeling of linear and nonlinear integrated optics networks. We also report the results of a preliminary experiment that studied the performance of an in situ controllable silicon nanophotonic network of two coupled cavities and analyze the properties of this device using the CQFC formalism. (orig.)

  3. Silicon nanophotonics for scalable quantum coherent feedback networks

    International Nuclear Information System (INIS)

    Sarovar, Mohan; Brif, Constantin; Soh, Daniel B.S.; Cox, Jonathan; DeRose, Christopher T.; Camacho, Ryan; Davids, Paul

    2016-01-01

    The emergence of coherent quantum feedback control (CQFC) as a new paradigm for precise manipulation of dynamics of complex quantum systems has led to the development of efficient theoretical modeling and simulation tools and opened avenues for new practical implementations. This work explores the applicability of the integrated silicon photonics platform for implementing scalable CQFC networks. If proven successful, on-chip implementations of these networks would provide scalable and efficient nanophotonic components for autonomous quantum information processing devices and ultra-low-power optical processing systems at telecommunications wavelengths. We analyze the strengths of the silicon photonics platform for CQFC applications and identify the key challenges to both the theoretical formalism and experimental implementations. In particular, we determine specific extensions to the theoretical CQFC framework (which was originally developed with bulk-optics implementations in mind), required to make it fully applicable to modeling of linear and nonlinear integrated optics networks. We also report the results of a preliminary experiment that studied the performance of an in situ controllable silicon nanophotonic network of two coupled cavities and analyze the properties of this device using the CQFC formalism. (orig.)

  4. On eliminating synchronous communication in molecular simulations to improve scalability

    Science.gov (United States)

    Straatsma, T. P.; Chavarría-Miranda, Daniel G.

    2013-12-01

    Molecular dynamics simulation, as a complementary tool to experimentation, has become an important methodology for the understanding and design of molecular systems as it provides access to properties that are difficult, impossible or prohibitively expensive to obtain experimentally. Many of the available software packages have been parallelized to take advantage of modern massively concurrent processing resources. The challenge in achieving parallel efficiency is commonly attributed to the fact that molecular dynamics algorithms are communication intensive. This paper illustrates how an appropriately chosen data distribution and asynchronous one-sided communication approach can be used to effectively deal with the data movement within the Global Arrays/ARMCI programming model framework. A new put_notify capability is presented here, allowing the implementation of the molecular dynamics algorithm without any explicit global or local synchronization or global data reduction operations. In addition, this push-data model is shown to very effectively allow hiding data communication behind computation. Rather than data movement or explicit global reductions, the implicit synchronization of the algorithm becomes the primary challenge for scalability. Without any explicit synchronous operations, the scalability of molecular simulations is shown to depend only on the ability to evenly balance computational load.

  5. Scalable Multi-Platform Distribution of Spatial 3d Contents

    Science.gov (United States)

    Klimke, J.; Hagedorn, B.; Döllner, J.

    2013-09-01

    Virtual 3D city models provide powerful user interfaces for communication of 2D and 3D geoinformation. Providing high quality visualization of massive 3D geoinformation in a scalable, fast, and cost efficient manner is still a challenging task. Especially for mobile and web-based system environments, software and hardware configurations of target systems differ significantly. This makes it hard to provide fast, visually appealing renderings of 3D data throughout a variety of platforms and devices. Current mobile or web-based solutions for 3D visualization usually require raw 3D scene data such as triangle meshes together with textures delivered from server to client, what makes them strongly limited in terms of size and complexity of the models they can handle. In this paper, we introduce a new approach for provisioning of massive, virtual 3D city models on different platforms namely web browsers, smartphones or tablets, by means of an interactive map assembled from artificial oblique image tiles. The key concept is to synthesize such images of a virtual 3D city model by a 3D rendering service in a preprocessing step. This service encapsulates model handling and 3D rendering techniques for high quality visualization of massive 3D models. By generating image tiles using this service, the 3D rendering process is shifted from the client side, which provides major advantages: (a) The complexity of the 3D city model data is decoupled from data transfer complexity (b) the implementation of client applications is simplified significantly as 3D rendering is encapsulated on server side (c) 3D city models can be easily deployed for and used by a large number of concurrent users, leading to a high degree of scalability of the overall approach. All core 3D rendering techniques are performed on a dedicated 3D rendering server, and thin-client applications can be compactly implemented for various devices and platforms.

  6. Towards Scalable Strain Gauge-Based Joint Torque Sensors

    Science.gov (United States)

    D’Imperio, Mariapaola; Cannella, Ferdinando; Caldwell, Darwin G.; Cuschieri, Alfred

    2017-01-01

    During recent decades, strain gauge-based joint torque sensors have been commonly used to provide high-fidelity torque measurements in robotics. Although measurement of joint torque/force is often required in engineering research and development, the gluing and wiring of strain gauges used as torque sensors pose difficulties during integration within the restricted space available in small joints. The problem is compounded by the need for a scalable geometric design to measure joint torque. In this communication, we describe a novel design of a strain gauge-based mono-axial torque sensor referred to as square-cut torque sensor (SCTS), the significant features of which are high degree of linearity, symmetry, and high scalability in terms of both size and measuring range. Most importantly, SCTS provides easy access for gluing and wiring of the strain gauges on sensor surface despite the limited available space. We demonstrated that the SCTS was better in terms of symmetry (clockwise and counterclockwise rotation) and more linear. These capabilities have been shown through finite element modeling (ANSYS) confirmed by observed data obtained by load testing experiments. The high performance of SCTS was confirmed by studies involving changes in size, material and/or wings width and thickness. Finally, we demonstrated that the SCTS can be successfully implementation inside the hip joints of miniaturized hydraulically actuated quadruped robot-MiniHyQ. This communication is based on work presented at the 18th International Conference on Climbing and Walking Robots (CLAWAR). PMID:28820446

  7. Programming Scala Scalability = Functional Programming + Objects

    CERN Document Server

    Wampler, Dean

    2009-01-01

    Learn how to be more productive with Scala, a new multi-paradigm language for the Java Virtual Machine (JVM) that integrates features of both object-oriented and functional programming. With this book, you'll discover why Scala is ideal for highly scalable, component-based applications that support concurrency and distribution. Programming Scala clearly explains the advantages of Scala as a JVM language. You'll learn how to leverage the wealth of Java class libraries to meet the practical needs of enterprise and Internet projects more easily. Packed with code examples, this book provides us

  8. Tip-Based Nanofabrication for Scalable Manufacturing

    Directory of Open Access Journals (Sweden)

    Huan Hu

    2017-03-01

    Full Text Available Tip-based nanofabrication (TBN is a family of emerging nanofabrication techniques that use a nanometer scale tip to fabricate nanostructures. In this review, we first introduce the history of the TBN and the technology development. We then briefly review various TBN techniques that use different physical or chemical mechanisms to fabricate features and discuss some of the state-of-the-art techniques. Subsequently, we focus on those TBN methods that have demonstrated potential to scale up the manufacturing throughput. Finally, we discuss several research directions that are essential for making TBN a scalable nano-manufacturing technology.

  9. Tip-Based Nanofabrication for Scalable Manufacturing

    International Nuclear Information System (INIS)

    Hu, Huan; Somnath, Suhas

    2017-01-01

    Tip-based nanofabrication (TBN) is a family of emerging nanofabrication techniques that use a nanometer scale tip to fabricate nanostructures. Here in this review, we first introduce the history of the TBN and the technology development. We then briefly review various TBN techniques that use different physical or chemical mechanisms to fabricate features and discuss some of the state-of-the-art techniques. Subsequently, we focus on those TBN methods that have demonstrated potential to scale up the manufacturing throughput. Finally, we discuss several research directions that are essential for making TBN a scalable nano-manufacturing technology.

  10. Towards a Scalable, Biomimetic, Antibacterial Coating

    Science.gov (United States)

    Dickson, Mary Nora

    Corneal afflictions are the second leading cause of blindness worldwide. When a corneal transplant is unavailable or contraindicated, an artificial cornea device is the only chance to save sight. Bacterial or fungal biofilm build up on artificial cornea devices can lead to serious complications including the need for systemic antibiotic treatment and even explantation. As a result, much emphasis has been placed on anti-adhesion chemical coatings and antibiotic leeching coatings. These methods are not long-lasting, and microorganisms can eventually circumvent these measures. Thus, I have developed a surface topographical antimicrobial coating. Various surface structures including rough surfaces, superhydrophobic surfaces, and the natural surfaces of insects' wings and sharks' skin are promising anti-biofilm candidates, however none meet the criteria necessary for implementation on the surface of an artificial cornea device. In this thesis I: 1) developed scalable fabrication protocols for a library of biomimetic nanostructure polymer surfaces 2) assessed the potential these for poly(methyl methacrylate) nanopillars to kill or prevent formation of biofilm by E. coli bacteria and species of Pseudomonas and Staphylococcus bacteria and improved upon a proposed mechanism for the rupture of Gram-negative bacterial cell walls 3) developed a scalable, commercially viable method for producing antibacterial nanopillars on a curved, PMMA artificial cornea device and 4) developed scalable fabrication protocols for implantation of antibacterial nanopatterned surfaces on the surfaces of thermoplastic polyurethane materials, commonly used in catheter tubings. This project constitutes a first step towards fabrication of the first entirely PMMA artificial cornea device. The major finding of this work is that by precisely controlling the topography of a polymer surface at the nano-scale, we can kill adherent bacteria and prevent biofilm formation of certain pathogenic bacteria

  11. Scalable Optical-Fiber Communication Networks

    Science.gov (United States)

    Chow, Edward T.; Peterson, John C.

    1993-01-01

    Scalable arbitrary fiber extension network (SAFEnet) is conceptual fiber-optic communication network passing digital signals among variety of computers and input/output devices at rates from 200 Mb/s to more than 100 Gb/s. Intended for use with very-high-speed computers and other data-processing and communication systems in which message-passing delays must be kept short. Inherent flexibility makes it possible to match performance of network to computers by optimizing configuration of interconnections. In addition, interconnections made redundant to provide tolerance to faults.

  12. Scalable Tensor Factorizations with Missing Data

    DEFF Research Database (Denmark)

    Acar, Evrim; Dunlavy, Daniel M.; Kolda, Tamara G.

    2010-01-01

    of missing data, many important data sets will be discarded or improperly analyzed. Therefore, we need a robust and scalable approach for factorizing multi-way arrays (i.e., tensors) in the presence of missing data. We focus on one of the most well-known tensor factorizations, CANDECOMP/PARAFAC (CP...... is shown to successfully factor tensors with noise and up to 70% missing data. Moreover, our approach is significantly faster than the leading alternative and scales to larger problems. To show the real-world usefulness of CP-WOPT, we illustrate its applicability on a novel EEG (electroencephalogram...

  13. Scalable and Anonymous Group Communication with MTor

    Directory of Open Access Journals (Sweden)

    Lin Dong

    2016-04-01

    Full Text Available This paper presents MTor, a low-latency anonymous group communication system. We construct MTor as an extension to Tor, allowing the construction of multi-source multicast trees on top of the existing Tor infrastructure. MTor does not depend on an external service to broker the group communication, and avoids central points of failure and trust. MTor’s substantial bandwidth savings and graceful scalability enable new classes of anonymous applications that are currently too bandwidth-intensive to be viable through traditional unicast Tor communication-e.g., group file transfer, collaborative editing, streaming video, and real-time audio conferencing.

  14. Grassmann Averages for Scalable Robust PCA

    DEFF Research Database (Denmark)

    Hauberg, Søren; Feragen, Aasa; Black, Michael J.

    2014-01-01

    As the collection of large datasets becomes increasingly automated, the occurrence of outliers will increase—“big data” implies “big outliers”. While principal component analysis (PCA) is often used to reduce the size of data, and scalable solutions exist, it is well-known that outliers can...... to vectors (subspaces) or elements of vectors; we focus on the latter and use a trimmed average. The resulting Trimmed Grassmann Average (TGA) is particularly appropriate for computer vision because it is robust to pixel outliers. The algorithm has low computational complexity and minimal memory requirements...

  15. Overview of the Scalable Coherent Interface, IEEE STD 1596 (SCI)

    International Nuclear Information System (INIS)

    Gustavson, D.B.; James, D.V.; Wiggers, H.A.

    1992-10-01

    The Scalable Coherent Interface standard defines a new generation of interconnection that spans the full range from supercomputer memory 'bus' to campus-wide network. SCI provides bus-like services and a shared-memory software model while using an underlying, packet protocol on many independent communication links. Initially these links are 1 GByte/s (wires) and 1 GBit/s (fiber), but the protocol scales well to future faster or lower-cost technologies. The interconnect may use switches, meshes, and rings. The SCI distributed-shared-memory model is simple and versatile, enabling for the first time a smooth integration of highly parallel multiprocessors, workstations, personal computers, I/O, networking and data acquisition

  16. Vortex Filaments in Grids for Scalable, Fine Smoke Simulation.

    Science.gov (United States)

    Meng, Zhang; Weixin, Si; Yinling, Qian; Hanqiu, Sun; Jing, Qin; Heng, Pheng-Ann

    2015-01-01

    Vortex modeling can produce attractive visual effects of dynamic fluids, which are widely applicable for dynamic media, computer games, special effects, and virtual reality systems. However, it is challenging to effectively simulate intensive and fine detailed fluids such as smoke with fast increasing vortex filaments and smoke particles. The authors propose a novel vortex filaments in grids scheme in which the uniform grids dynamically bridge the vortex filaments and smoke particles for scalable, fine smoke simulation with macroscopic vortex structures. Using the vortex model, their approach supports the trade-off between simulation speed and scale of details. After computing the whole velocity, external control can be easily exerted on the embedded grid to guide the vortex-based smoke motion. The experimental results demonstrate the efficiency of using the proposed scheme for a visually plausible smoke simulation with macroscopic vortex structures.

  17. Simplifying Scalable Graph Processing with a Domain-Specific Language

    KAUST Repository

    Hong, Sungpack; Salihoglu, Semih; Widom, Jennifer; Olukotun, Kunle

    2014-01-01

    Large-scale graph processing, with its massive data sets, requires distributed processing. However, conventional frameworks for distributed graph processing, such as Pregel, use non-traditional programming models that are well-suited for parallelism and scalability but inconvenient for implementing non-trivial graph algorithms. In this paper, we use Green-Marl, a Domain-Specific Language for graph analysis, to intuitively describe graph algorithms and extend its compiler to generate equivalent Pregel implementations. Using the semantic information captured by Green-Marl, the compiler applies a set of transformation rules that convert imperative graph algorithms into Pregel's programming model. Our experiments show that the Pregel programs generated by the Green-Marl compiler perform similarly to manually coded Pregel implementations of the same algorithms. The compiler is even able to generate a Pregel implementation of a complicated graph algorithm for which a manual Pregel implementation is very challenging.

  18. Simplifying Scalable Graph Processing with a Domain-Specific Language

    KAUST Repository

    Hong, Sungpack

    2014-01-01

    Large-scale graph processing, with its massive data sets, requires distributed processing. However, conventional frameworks for distributed graph processing, such as Pregel, use non-traditional programming models that are well-suited for parallelism and scalability but inconvenient for implementing non-trivial graph algorithms. In this paper, we use Green-Marl, a Domain-Specific Language for graph analysis, to intuitively describe graph algorithms and extend its compiler to generate equivalent Pregel implementations. Using the semantic information captured by Green-Marl, the compiler applies a set of transformation rules that convert imperative graph algorithms into Pregel\\'s programming model. Our experiments show that the Pregel programs generated by the Green-Marl compiler perform similarly to manually coded Pregel implementations of the same algorithms. The compiler is even able to generate a Pregel implementation of a complicated graph algorithm for which a manual Pregel implementation is very challenging.

  19. A Scalable Framework and Prototype for CAS e-Science

    Directory of Open Access Journals (Sweden)

    Yuanchun Zhou

    2007-07-01

    Full Text Available Based on the Small-World model of CAS e-Science and the power low of Internet, this paper presents a scalable CAS e-Science Grid framework based on virtual region called Virtual Region Grid Framework (VRGF. VRGF takes virtual region and layer as logic manage-unit. In VRGF, the mode of intra-virtual region is pure P2P, and the model of inter-virtual region is centralized. Therefore, VRGF is decentralized framework with some P2P properties. Further more, VRGF is able to achieve satisfactory performance on resource organizing and locating at a small cost, and is well adapted to the complicated and dynamic features of scientific collaborations. We have implemented a demonstration VRGF based Grid prototype—SDG.

  20. Scalability Optimization of Seamless Positioning Service

    Directory of Open Access Journals (Sweden)

    Juraj Machaj

    2016-01-01

    Full Text Available Recently positioning services are getting more attention not only within research community but also from service providers. From the service providers point of view positioning service that will be able to work seamlessly in all environments, for example, indoor, dense urban, and rural, has a huge potential to open new markets. However, such system does not only need to provide accurate position estimates but have to be scalable and resistant to fake positioning requests. In the previous works we have proposed a modular system, which is able to provide seamless positioning in various environments. The system automatically selects optimal positioning module based on available radio signals. The system currently consists of three positioning modules—GPS, GSM based positioning, and Wi-Fi based positioning. In this paper we will propose algorithm which will reduce time needed for position estimation and thus allow higher scalability of the modular system and thus allow providing positioning services to higher amount of users. Such improvement is extremely important, for real world application where large number of users will require position estimates, since positioning error is affected by response time of the positioning server.

  1. Highly scalable Ab initio genomic motif identification

    KAUST Repository

    Marchand, Benoit; Bajic, Vladimir B.; Kaushik, Dinesh

    2011-01-01

    We present results of scaling an ab initio motif family identification system, Dragon Motif Finder (DMF), to 65,536 processor cores of IBM Blue Gene/P. DMF seeks groups of mutually similar polynucleotide patterns within a set of genomic sequences and builds various motif families from them. Such information is of relevance to many problems in life sciences. Prior attempts to scale such ab initio motif-finding algorithms achieved limited success. We solve the scalability issues using a combination of mixed-mode MPI-OpenMP parallel programming, master-slave work assignment, multi-level workload distribution, multi-level MPI collectives, and serial optimizations. While the scalability of our algorithm was excellent (94% parallel efficiency on 65,536 cores relative to 256 cores on a modest-size problem), the final speedup with respect to the original serial code exceeded 250,000 when serial optimizations are included. This enabled us to carry out many large-scale ab initio motiffinding simulations in a few hours while the original serial code would have needed decades of execution time. Copyright 2011 ACM.

  2. Towards Scalable Graph Computation on Mobile Devices.

    Science.gov (United States)

    Chen, Yiqi; Lin, Zhiyuan; Pienta, Robert; Kahng, Minsuk; Chau, Duen Horng

    2014-10-01

    Mobile devices have become increasingly central to our everyday activities, due to their portability, multi-touch capabilities, and ever-improving computational power. Such attractive features have spurred research interest in leveraging mobile devices for computation. We explore a novel approach that aims to use a single mobile device to perform scalable graph computation on large graphs that do not fit in the device's limited main memory, opening up the possibility of performing on-device analysis of large datasets, without relying on the cloud. Based on the familiar memory mapping capability provided by today's mobile operating systems, our approach to scale up computation is powerful and intentionally kept simple to maximize its applicability across the iOS and Android platforms. Our experiments demonstrate that an iPad mini can perform fast computation on large real graphs with as many as 272 million edges (Google+ social graph), at a speed that is only a few times slower than a 13″ Macbook Pro. Through creating a real world iOS app with this technique, we demonstrate the strong potential application for scalable graph computation on a single mobile device using our approach.

  3. Scalable fast multipole accelerated vortex methods

    KAUST Repository

    Hu, Qi

    2014-05-01

    The fast multipole method (FMM) is often used to accelerate the calculation of particle interactions in particle-based methods to simulate incompressible flows. To evaluate the most time-consuming kernels - the Biot-Savart equation and stretching term of the vorticity equation, we mathematically reformulated it so that only two Laplace scalar potentials are used instead of six. This automatically ensuring divergence-free far-field computation. Based on this formulation, we developed a new FMM-based vortex method on heterogeneous architectures, which distributed the work between multicore CPUs and GPUs to best utilize the hardware resources and achieve excellent scalability. The algorithm uses new data structures which can dynamically manage inter-node communication and load balance efficiently, with only a small parallel construction overhead. This algorithm can scale to large-sized clusters showing both strong and weak scalability. Careful error and timing trade-off analysis are also performed for the cutoff functions induced by the vortex particle method. Our implementation can perform one time step of the velocity+stretching calculation for one billion particles on 32 nodes in 55.9 seconds, which yields 49.12 Tflop/s.

  4. Computational scalability of large size image dissemination

    Science.gov (United States)

    Kooper, Rob; Bajcsy, Peter

    2011-01-01

    We have investigated the computational scalability of image pyramid building needed for dissemination of very large image data. The sources of large images include high resolution microscopes and telescopes, remote sensing and airborne imaging, and high resolution scanners. The term 'large' is understood from a user perspective which means either larger than a display size or larger than a memory/disk to hold the image data. The application drivers for our work are digitization projects such as the Lincoln Papers project (each image scan is about 100-150MB or about 5000x8000 pixels with the total number to be around 200,000) and the UIUC library scanning project for historical maps from 17th and 18th century (smaller number but larger images). The goal of our work is understand computational scalability of the web-based dissemination using image pyramids for these large image scans, as well as the preservation aspects of the data. We report our computational benchmarks for (a) building image pyramids to be disseminated using the Microsoft Seadragon library, (b) a computation execution approach using hyper-threading to generate image pyramids and to utilize the underlying hardware, and (c) an image pyramid preservation approach using various hard drive configurations of Redundant Array of Independent Disks (RAID) drives for input/output operations. The benchmarks are obtained with a map (334.61 MB, JPEG format, 17591x15014 pixels). The discussion combines the speed and preservation objectives.

  5. Towards Scalable Graph Computation on Mobile Devices

    Science.gov (United States)

    Chen, Yiqi; Lin, Zhiyuan; Pienta, Robert; Kahng, Minsuk; Chau, Duen Horng

    2015-01-01

    Mobile devices have become increasingly central to our everyday activities, due to their portability, multi-touch capabilities, and ever-improving computational power. Such attractive features have spurred research interest in leveraging mobile devices for computation. We explore a novel approach that aims to use a single mobile device to perform scalable graph computation on large graphs that do not fit in the device's limited main memory, opening up the possibility of performing on-device analysis of large datasets, without relying on the cloud. Based on the familiar memory mapping capability provided by today's mobile operating systems, our approach to scale up computation is powerful and intentionally kept simple to maximize its applicability across the iOS and Android platforms. Our experiments demonstrate that an iPad mini can perform fast computation on large real graphs with as many as 272 million edges (Google+ social graph), at a speed that is only a few times slower than a 13″ Macbook Pro. Through creating a real world iOS app with this technique, we demonstrate the strong potential application for scalable graph computation on a single mobile device using our approach. PMID:25859564

  6. Big data integration: scalability and sustainability

    KAUST Repository

    Zhang, Zhang

    2016-01-26

    Integration of various types of omics data is critically indispensable for addressing most important and complex biological questions. In the era of big data, however, data integration becomes increasingly tedious, time-consuming and expensive, posing a significant obstacle to fully exploit the wealth of big biological data. Here we propose a scalable and sustainable architecture that integrates big omics data through community-contributed modules. Community modules are contributed and maintained by different committed groups and each module corresponds to a specific data type, deals with data collection, processing and visualization, and delivers data on-demand via web services. Based on this community-based architecture, we build Information Commons for Rice (IC4R; http://ic4r.org), a rice knowledgebase that integrates a variety of rice omics data from multiple community modules, including genome-wide expression profiles derived entirely from RNA-Seq data, resequencing-based genomic variations obtained from re-sequencing data of thousands of rice varieties, plant homologous genes covering multiple diverse plant species, post-translational modifications, rice-related literatures, and community annotations. Taken together, such architecture achieves integration of different types of data from multiple community-contributed modules and accordingly features scalable, sustainable and collaborative integration of big data as well as low costs for database update and maintenance, thus helpful for building IC4R into a comprehensive knowledgebase covering all aspects of rice data and beneficial for both basic and translational researches.

  7. Scalable domain decomposition solvers for stochastic PDEs in high performance computing

    International Nuclear Information System (INIS)

    Desai, Ajit; Pettit, Chris; Poirel, Dominique; Sarkar, Abhijit

    2017-01-01

    Stochastic spectral finite element models of practical engineering systems may involve solutions of linear systems or linearized systems for non-linear problems with billions of unknowns. For stochastic modeling, it is therefore essential to design robust, parallel and scalable algorithms that can efficiently utilize high-performance computing to tackle such large-scale systems. Domain decomposition based iterative solvers can handle such systems. And though these algorithms exhibit excellent scalabilities, significant algorithmic and implementational challenges exist to extend them to solve extreme-scale stochastic systems using emerging computing platforms. Intrusive polynomial chaos expansion based domain decomposition algorithms are extended here to concurrently handle high resolution in both spatial and stochastic domains using an in-house implementation. Sparse iterative solvers with efficient preconditioners are employed to solve the resulting global and subdomain level local systems through multi-level iterative solvers. We also use parallel sparse matrix–vector operations to reduce the floating-point operations and memory requirements. Numerical and parallel scalabilities of these algorithms are presented for the diffusion equation having spatially varying diffusion coefficient modeled by a non-Gaussian stochastic process. Scalability of the solvers with respect to the number of random variables is also investigated.

  8. MicROS-drt: supporting real-time and scalable data distribution in distributed robotic systems.

    Science.gov (United States)

    Ding, Bo; Wang, Huaimin; Fan, Zedong; Zhang, Pengfei; Liu, Hui

    A primary requirement in distributed robotic software systems is the dissemination of data to all interested collaborative entities in a timely and scalable manner. However, providing such a service in a highly dynamic and resource-limited robotic environment is a challenging task, and existing robot software infrastructure has limitations in this aspect. This paper presents a novel robot software infrastructure, micROS-drt, which supports real-time and scalable data distribution. The solution is based on a loosely coupled data publish-subscribe model with the ability to support various time-related constraints. And to realize this model, a mature data distribution standard, the data distribution service for real-time systems (DDS), is adopted as the foundation of the transport layer of this software infrastructure. By elaborately adapting and encapsulating the capability of the underlying DDS middleware, micROS-drt can meet the requirement of real-time and scalable data distribution in distributed robotic systems. Evaluation results in terms of scalability, latency jitter and transport priority as well as the experiment on real robots validate the effectiveness of this work.

  9. Scalable conditional induction variables (CIV) analysis

    DEFF Research Database (Denmark)

    Oancea, Cosmin Eugen; Rauchwerger, Lawrence

    2015-01-01

    parallelizing compiler and evaluated its impact on five Fortran benchmarks. We have found that that there are many important loops using CIV subscripts and that our analysis can lead to their scalable parallelization. This in turn has led to the parallelization of the benchmark programs they appear in.......Subscripts using induction variables that cannot be expressed as a formula in terms of the enclosing-loop indices appear in the low-level implementation of common programming abstractions such as filter, or stack operations and pose significant challenges to automatic parallelization. Because...... the complexity of such induction variables is often due to their conditional evaluation across the iteration space of loops we name them Conditional Induction Variables (CIV). This paper presents a flow-sensitive technique that summarizes both such CIV-based and affine subscripts to program level, using the same...

  10. Scalable Faceted Ranking in Tagging Systems

    Science.gov (United States)

    Orlicki, José I.; Alvarez-Hamelin, J. Ignacio; Fierens, Pablo I.

    Nowadays, web collaborative tagging systems which allow users to upload, comment on and recommend contents, are growing. Such systems can be represented as graphs where nodes correspond to users and tagged-links to recommendations. In this paper we analyze the problem of computing a ranking of users with respect to a facet described as a set of tags. A straightforward solution is to compute a PageRank-like algorithm on a facet-related graph, but it is not feasible for online computation. We propose an alternative: (i) a ranking for each tag is computed offline on the basis of tag-related subgraphs; (ii) a faceted order is generated online by merging rankings corresponding to all the tags in the facet. Based on the graph analysis of YouTube and Flickr, we show that step (i) is scalable. We also present efficient algorithms for step (ii), which are evaluated by comparing their results with two gold standards.

  11. A graph algebra for scalable visual analytics.

    Science.gov (United States)

    Shaverdian, Anna A; Zhou, Hao; Michailidis, George; Jagadish, Hosagrahar V

    2012-01-01

    Visual analytics (VA), which combines analytical techniques with advanced visualization features, is fast becoming a standard tool for extracting information from graph data. Researchers have developed many tools for this purpose, suggesting a need for formal methods to guide these tools' creation. Increased data demands on computing requires redesigning VA tools to consider performance and reliability in the context of analysis of exascale datasets. Furthermore, visual analysts need a way to document their analyses for reuse and results justification. A VA graph framework encapsulated in a graph algebra helps address these needs. Its atomic operators include selection and aggregation. The framework employs a visual operator and supports dynamic attributes of data to enable scalable visual exploration of data.

  12. Parallel scalability of Hartree-Fock calculations

    Science.gov (United States)

    Chow, Edmond; Liu, Xing; Smelyanskiy, Mikhail; Hammond, Jeff R.

    2015-03-01

    Quantum chemistry is increasingly performed using large cluster computers consisting of multiple interconnected nodes. For a fixed molecular problem, the efficiency of a calculation usually decreases as more nodes are used, due to the cost of communication between the nodes. This paper empirically investigates the parallel scalability of Hartree-Fock calculations. The construction of the Fock matrix and the density matrix calculation are analyzed separately. For the former, we use a parallelization of Fock matrix construction based on a static partitioning of work followed by a work stealing phase. For the latter, we use density matrix purification from the linear scaling methods literature, but without using sparsity. When using large numbers of nodes for moderately sized problems, density matrix computations are network-bandwidth bound, making purification methods potentially faster than eigendecomposition methods.

  13. iSIGHT-FD scalability test report.

    Energy Technology Data Exchange (ETDEWEB)

    Clay, Robert L.; Shneider, Max S.

    2008-07-01

    The engineering analysis community at Sandia National Laboratories uses a number of internal and commercial software codes and tools, including mesh generators, preprocessors, mesh manipulators, simulation codes, post-processors, and visualization packages. We define an analysis workflow as the execution of an ordered, logical sequence of these tools. Various forms of analysis (and in particular, methodologies that use multiple function evaluations or samples) involve executing parameterized variations of these workflows. As part of the DART project, we are evaluating various commercial workflow management systems, including iSIGHT-FD from Engineous. This report documents the results of a scalability test that was driven by DAKOTA and conducted on a parallel computer (Thunderbird). The purpose of this experiment was to examine the suitability and performance of iSIGHT-FD for large-scale, parameterized analysis workflows. As the results indicate, we found iSIGHT-FD to be suitable for this type of application.

  14. Scalable on-chip quantum state tomography

    Science.gov (United States)

    Titchener, James G.; Gräfe, Markus; Heilmann, René; Solntsev, Alexander S.; Szameit, Alexander; Sukhorukov, Andrey A.

    2018-03-01

    Quantum information systems are on a path to vastly exceed the complexity of any classical device. The number of entangled qubits in quantum devices is rapidly increasing, and the information required to fully describe these systems scales exponentially with qubit number. This scaling is the key benefit of quantum systems, however it also presents a severe challenge. To characterize such systems typically requires an exponentially long sequence of different measurements, becoming highly resource demanding for large numbers of qubits. Here we propose and demonstrate a novel and scalable method for characterizing quantum systems based on expanding a multi-photon state to larger dimensionality. We establish that the complexity of this new measurement technique only scales linearly with the number of qubits, while providing a tomographically complete set of data without a need for reconfigurability. We experimentally demonstrate an integrated photonic chip capable of measuring two- and three-photon quantum states with statistical reconstruction fidelity of 99.71%.

  15. A versatile scalable PET processing system

    International Nuclear Information System (INIS)

    Dong, H.; Weisenberger, A.; McKisson, J.; Wenze, Xi; Cuevas, C.; Wilson, J.; Zukerman, L.

    2011-01-01

    Positron Emission Tomography (PET) historically has major clinical and preclinical applications in cancerous oncology, neurology, and cardiovascular diseases. Recently, in a new direction, an application specific PET system is being developed at Thomas Jefferson National Accelerator Facility (Jefferson Lab) in collaboration with Duke University, University of Maryland at Baltimore (UMAB), and West Virginia University (WVU) targeted for plant eco-physiology research. The new plant imaging PET system is versatile and scalable such that it could adapt to several plant imaging needs - imaging many important plant organs including leaves, roots, and stems. The mechanical arrangement of the detectors is designed to accommodate the unpredictable and random distribution in space of the plant organs without requiring the plant be disturbed. Prototyping such a system requires a new data acquisition system (DAQ) and data processing system which are adaptable to the requirements of these unique and versatile detectors.

  16. The scalable coherent interface, IEEE P1596

    International Nuclear Information System (INIS)

    Gustavson, D.B.

    1990-01-01

    IEEE P1596, the scalable coherent interface (formerly known as SuperBus) is based on experience gained while developing Fastbus (ANSI/IEEE 960--1986, IEC 935), Futurebus (IEEE P896.x) and other modern 32-bit buses. SCI goals include a minimum bandwidth of 1 GByte/sec per processor in multiprocessor systems with thousands of processors; efficient support of a coherent distributed-cache image of distributed shared memory; support for repeaters which interface to existing or future buses; and support for inexpensive small rings as well as for general switched interconnections like Banyan, Omega, or crossbar networks. This paper presents a summary of current directions, reports the status of the work in progress, and suggests some applications in data acquisition and physics

  17. BASSET: Scalable Gateway Finder in Large Graphs

    Energy Technology Data Exchange (ETDEWEB)

    Tong, H; Papadimitriou, S; Faloutsos, C; Yu, P S; Eliassi-Rad, T

    2010-11-03

    Given a social network, who is the best person to introduce you to, say, Chris Ferguson, the poker champion? Or, given a network of people and skills, who is the best person to help you learn about, say, wavelets? The goal is to find a small group of 'gateways': persons who are close enough to us, as well as close enough to the target (person, or skill) or, in other words, are crucial in connecting us to the target. The main contributions are the following: (a) we show how to formulate this problem precisely; (b) we show that it is sub-modular and thus it can be solved near-optimally; (c) we give fast, scalable algorithms to find such gateways. Experiments on real data sets validate the effectiveness and efficiency of the proposed methods, achieving up to 6,000,000x speedup.

  18. Scalable quantum search using trapped ions

    International Nuclear Information System (INIS)

    Ivanov, S. S.; Ivanov, P. A.; Linington, I. E.; Vitanov, N. V.

    2010-01-01

    We propose a scalable implementation of Grover's quantum search algorithm in a trapped-ion quantum information processor. The system is initialized in an entangled Dicke state by using adiabatic techniques. The inversion-about-average and oracle operators take the form of single off-resonant laser pulses. This is made possible by utilizing the physical symmetries of the trapped-ion linear crystal. The physical realization of the algorithm represents a dramatic simplification: each logical iteration (oracle and inversion about average) requires only two physical interaction steps, in contrast to the large number of concatenated gates required by previous approaches. This not only facilitates the implementation but also increases the overall fidelity of the algorithm.

  19. Scalable graphene aptasensors for drug quantification

    Science.gov (United States)

    Vishnubhotla, Ramya; Ping, Jinglei; Gao, Zhaoli; Lee, Abigail; Saouaf, Olivia; Vrudhula, Amey; Johnson, A. T. Charlie

    2017-11-01

    Simpler and more rapid approaches for therapeutic drug-level monitoring are highly desirable to enable use at the point-of-care. We have developed an all-electronic approach for detection of the HIV drug tenofovir based on scalable fabrication of arrays of graphene field-effect transistors (GFETs) functionalized with a commercially available DNA aptamer. The shift in the Dirac voltage of the GFETs varied systematically with the concentration of tenofovir in deionized water, with a detection limit less than 1 ng/mL. Tests against a set of negative controls confirmed the specificity of the sensor response. This approach offers the potential for further development into a rapid and convenient point-of-care tool with clinically relevant performance.

  20. Scalable Transactions for Web Applications in the Cloud

    NARCIS (Netherlands)

    Zhou, W.; Pierre, G.E.O.; Chi, C.-H.

    2009-01-01

    Cloud Computing platforms provide scalability and high availability properties for web applications but they sacrifice data consistency at the same time. However, many applications cannot afford any data inconsistency. We present a scalable transaction manager for NoSQL cloud database services to

  1. New Complexity Scalable MPEG Encoding Techniques for Mobile Applications

    Directory of Open Access Journals (Sweden)

    Stephan Mietens

    2004-03-01

    Full Text Available Complexity scalability offers the advantage of one-time design of video applications for a large product family, including mobile devices, without the need of redesigning the applications on the algorithmic level to meet the requirements of the different products. In this paper, we present complexity scalable MPEG encoding having core modules with modifications for scalability. The interdependencies of the scalable modules and the system performance are evaluated. Experimental results show scalability giving a smooth change in complexity and corresponding video quality. Scalability is basically achieved by varying the number of computed DCT coefficients and the number of evaluated motion vectors but other modules are designed such they scale with the previous parameters. In the experiments using the “Stefan” sequence, the elapsed execution time of the scalable encoder, reflecting the computational complexity, can be gradually reduced to roughly 50% of its original execution time. The video quality scales between 20 dB and 48 dB PSNR with unity quantizer setting, and between 21.5 dB and 38.5 dB PSNR for different sequences targeting 1500 kbps. The implemented encoder and the scalability techniques can be successfully applied in mobile systems based on MPEG video compression.

  2. Building scalable apps with Redis and Node.js

    CERN Document Server

    Johanan, Joshua

    2014-01-01

    If the phrase scalability sounds alien to you, then this is an ideal book for you. You will not need much Node.js experience as each framework is demonstrated in a way that requires no previous knowledge of the framework. You will be building scalable Node.js applications in no time! Knowledge of JavaScript is required.

  3. Fourier transform based scalable image quality measure.

    Science.gov (United States)

    Narwaria, Manish; Lin, Weisi; McLoughlin, Ian; Emmanuel, Sabu; Chia, Liang-Tien

    2012-08-01

    We present a new image quality assessment (IQA) algorithm based on the phase and magnitude of the 2D (twodimensional) Discrete Fourier Transform (DFT). The basic idea is to compare the phase and magnitude of the reference and distorted images to compute the quality score. However, it is well known that the Human Visual Systems (HVSs) sensitivity to different frequency components is not the same. We accommodate this fact via a simple yet effective strategy of nonuniform binning of the frequency components. This process also leads to reduced space representation of the image thereby enabling the reduced-reference (RR) prospects of the proposed scheme. We employ linear regression to integrate the effects of the changes in phase and magnitude. In this way, the required weights are determined via proper training and hence more convincing and effective. Lastly, using the fact that phase usually conveys more information than magnitude, we use only the phase for RR quality assessment. This provides the crucial advantage of further reduction in the required amount of reference image information. The proposed method is therefore further scalable for RR scenarios. We report extensive experimental results using a total of 9 publicly available databases: 7 image (with a total of 3832 distorted images with diverse distortions) and 2 video databases (totally 228 distorted videos). These show that the proposed method is overall better than several of the existing fullreference (FR) algorithms and two RR algorithms. Additionally, there is a graceful degradation in prediction performance as the amount of reference image information is reduced thereby confirming its scalability prospects. To enable comparisons and future study, a Matlab implementation of the proposed algorithm is available at http://www.ntu.edu.sg/home/wslin/reduced_phase.rar.

  4. Improving diabetes medication adherence: successful, scalable interventions

    Directory of Open Access Journals (Sweden)

    Zullig LL

    2015-01-01

    Full Text Available Leah L Zullig,1,2 Walid F Gellad,3,4 Jivan Moaddeb,2,5 Matthew J Crowley,1,2 William Shrank,6 Bradi B Granger,7 Christopher B Granger,8 Troy Trygstad,9 Larry Z Liu,10 Hayden B Bosworth1,2,7,11 1Center for Health Services Research in Primary Care, Durham Veterans Affairs Medical Center, Durham, NC, USA; 2Department of Medicine, Duke University, Durham, NC, USA; 3Center for Health Equity Research and Promotion, Pittsburgh Veterans Affairs Medical Center, Pittsburgh, PA, USA; 4Division of General Internal Medicine, University of Pittsburgh, Pittsburgh, PA, USA; 5Institute for Genome Sciences and Policy, Duke University, Durham, NC, USA; 6CVS Caremark Corporation; 7School of Nursing, Duke University, Durham, NC, USA; 8Department of Medicine, Division of Cardiology, Duke University School of Medicine, Durham, NC, USA; 9North Carolina Community Care Networks, Raleigh, NC, USA; 10Pfizer, Inc., and Weill Medical College of Cornell University, New York, NY, USA; 11Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA Abstract: Effective medications are a cornerstone of prevention and disease treatment, yet only about half of patients take their medications as prescribed, resulting in a common and costly public health challenge for the US healthcare system. Since poor medication adherence is a complex problem with many contributing causes, there is no one universal solution. This paper describes interventions that were not only effective in improving medication adherence among patients with diabetes, but were also potentially scalable (ie, easy to implement to a large population. We identify key characteristics that make these interventions effective and scalable. This information is intended to inform healthcare systems seeking proven, low resource, cost-effective solutions to improve medication adherence. Keywords: medication adherence, diabetes mellitus, chronic disease, dissemination research

  5. Scalable and Media Aware Adaptive Video Streaming over Wireless Networks

    Directory of Open Access Journals (Sweden)

    Béatrice Pesquet-Popescu

    2008-07-01

    Full Text Available This paper proposes an advanced video streaming system based on scalable video coding in order to optimize resource utilization in wireless networks with retransmission mechanisms at radio protocol level. The key component of this system is a packet scheduling algorithm which operates on the different substreams of a main scalable video stream and which is implemented in a so-called media aware network element. The concerned type of transport channel is a dedicated channel subject to parameters (bitrate, loss rate variations on the long run. Moreover, we propose a combined scalability approach in which common temporal and SNR scalability features can be used jointly with a partitioning of the image into regions of interest. Simulation results show that our approach provides substantial quality gain compared to classical packet transmission methods and they demonstrate how ROI coding combined with SNR scalability allows to improve again the visual quality.

  6. fastBMA: scalable network inference and transitive reduction.

    Science.gov (United States)

    Hung, Ling-Hong; Shi, Kaiyuan; Wu, Migao; Young, William Chad; Raftery, Adrian E; Yeung, Ka Yee

    2017-10-01

    Inferring genetic networks from genome-wide expression data is extremely demanding computationally. We have developed fastBMA, a distributed, parallel, and scalable implementation of Bayesian model averaging (BMA) for this purpose. fastBMA also includes a computationally efficient module for eliminating redundant indirect edges in the network by mapping the transitive reduction to an easily solved shortest-path problem. We evaluated the performance of fastBMA on synthetic data and experimental genome-wide time series yeast and human datasets. When using a single CPU core, fastBMA is up to 100 times faster than the next fastest method, LASSO, with increased accuracy. It is a memory-efficient, parallel, and distributed application that scales to human genome-wide expression data. A 10 000-gene regulation network can be obtained in a matter of hours using a 32-core cloud cluster (2 nodes of 16 cores). fastBMA is a significant improvement over its predecessor ScanBMA. It is more accurate and orders of magnitude faster than other fast network inference methods such as the 1 based on LASSO. The improved scalability allows it to calculate networks from genome scale data in a reasonable time frame. The transitive reduction method can improve accuracy in denser networks. fastBMA is available as code (M.I.T. license) from GitHub (https://github.com/lhhunghimself/fastBMA), as part of the updated networkBMA Bioconductor package (https://www.bioconductor.org/packages/release/bioc/html/networkBMA.html) and as ready-to-deploy Docker images (https://hub.docker.com/r/biodepot/fastbma/). © The Authors 2017. Published by Oxford University Press.

  7. SWAP-Assembler: scalable and efficient genome assembly towards thousands of cores.

    Science.gov (United States)

    Meng, Jintao; Wang, Bingqiang; Wei, Yanjie; Feng, Shengzhong; Balaji, Pavan

    2014-01-01

    There is a widening gap between the throughput of massive parallel sequencing machines and the ability to analyze these sequencing data. Traditional assembly methods requiring long execution time and large amount of memory on a single workstation limit their use on these massive data. This paper presents a highly scalable assembler named as SWAP-Assembler for processing massive sequencing data using thousands of cores, where SWAP is an acronym for Small World Asynchronous Parallel model. In the paper, a mathematical description of multi-step bi-directed graph (MSG) is provided to resolve the computational interdependence on merging edges, and a highly scalable computational framework for SWAP is developed to automatically preform the parallel computation of all operations. Graph cleaning and contig extension are also included for generating contigs with high quality. Experimental results show that SWAP-Assembler scales up to 2048 cores on Yanhuang dataset using only 26 minutes, which is better than several other parallel assemblers, such as ABySS, Ray, and PASHA. Results also show that SWAP-Assembler can generate high quality contigs with good N50 size and low error rate, especially it generated the longest N50 contig sizes for Fish and Yanhuang datasets. In this paper, we presented a highly scalable and efficient genome assembly software, SWAP-Assembler. Compared with several other assemblers, it showed very good performance in terms of scalability and contig quality. This software is available at: https://sourceforge.net/projects/swapassembler.

  8. A Numerical Study of Scalable Cardiac Electro-Mechanical Solvers on HPC Architectures

    Directory of Open Access Journals (Sweden)

    Piero Colli Franzone

    2018-04-01

    Full Text Available We introduce and study some scalable domain decomposition preconditioners for cardiac electro-mechanical 3D simulations on parallel HPC (High Performance Computing architectures. The electro-mechanical model of the cardiac tissue is composed of four coupled sub-models: (1 the static finite elasticity equations for the transversely isotropic deformation of the cardiac tissue; (2 the active tension model describing the dynamics of the intracellular calcium, cross-bridge binding and myofilament tension; (3 the anisotropic Bidomain model describing the evolution of the intra- and extra-cellular potentials in the deforming cardiac tissue; and (4 the ionic membrane model describing the dynamics of ionic currents, gating variables, ionic concentrations and stretch-activated channels. This strongly coupled electro-mechanical model is discretized in time with a splitting semi-implicit technique and in space with isoparametric finite elements. The resulting scalable parallel solver is based on Multilevel Additive Schwarz preconditioners for the solution of the Bidomain system and on BDDC preconditioned Newton-Krylov solvers for the non-linear finite elasticity system. The results of several 3D parallel simulations show the scalability of both linear and non-linear solvers and their application to the study of both physiological excitation-contraction cardiac dynamics and re-entrant waves in the presence of different mechano-electrical feedbacks.

  9. Online Hashing for Scalable Remote Sensing Image Retrieval

    Directory of Open Access Journals (Sweden)

    Peng Li

    2018-05-01

    Full Text Available Recently, hashing-based large-scale remote sensing (RS image retrieval has attracted much attention. Many new hashing algorithms have been developed and successfully applied to fast RS image retrieval tasks. However, there exists an important problem rarely addressed in the research literature of RS image hashing. The RS images are practically produced in a streaming manner in many real-world applications, which means the data distribution keeps changing over time. Most existing RS image hashing methods are batch-based models whose hash functions are learned once for all and kept fixed all the time. Therefore, the pre-trained hash functions might not fit the ever-growing new RS images. Moreover, the batch-based models have to load all the training images into memory for model learning, which consumes many computing and memory resources. To address the above deficiencies, we propose a new online hashing method, which learns and adapts its hashing functions with respect to the newly incoming RS images in terms of a novel online partial random learning scheme. Our hash model is updated in a sequential mode such that the representative power of the learned binary codes for RS images are improved accordingly. Moreover, benefiting from the online learning strategy, our proposed hashing approach is quite suitable for scalable real-world remote sensing image retrieval. Extensive experiments on two large-scale RS image databases under online setting demonstrated the efficacy and effectiveness of the proposed method.

  10. Scalability Dilemma and Statistic Multiplexed Computing — A Theory and Experiment

    Directory of Open Access Journals (Sweden)

    Justin Yuan Shi

    2017-08-01

    Full Text Available The For the last three decades, end-to-end computing paradigms, such as MPI (Message Passing Interface, RPC (Remote Procedure Call and RMI (Remote Method Invocation, have been the de facto paradigms for distributed and parallel programming. Despite of the successes, applications built using these paradigms suffer due to the proportionality factor of crash in the application with its size. Checkpoint/restore and backup/recovery are the only means to save otherwise lost critical information. The scalability dilemma is such a practical challenge that the probability of the data losses increases as the application scales in size. The theoretical significance of this practical challenge is that it undermines the fundamental structure of the scientific discovery process and mission critical services in production today. In 1997, the direct use of end-to-end reference model in distributed programming was recognized as a fallacy. The scalability dilemma was predicted. However, this voice was overrun by the passage of time. Today, the rapidly growing digitized data demands solving the increasingly critical scalability challenges. Computing architecture scalability, although loosely defined, is now the front and center of large-scale computing efforts. Constrained only by the economic law of diminishing returns, this paper proposes a narrow definition of a Scalable Computing Service (SCS. Three scalability tests are also proposed in order to distinguish service architecture flaws from poor application programming. Scalable data intensive service requires additional treatments. Thus, the data storage is assumed reliable in this paper. A single-sided Statistic Multiplexed Computing (SMC paradigm is proposed. A UVR (Unidirectional Virtual Ring SMC architecture is examined under SCS tests. SMC was designed to circumvent the well-known impossibility of end-to-end paradigms. It relies on the proven statistic multiplexing principle to deliver reliable service

  11. Integration of an intelligent systems behavior simulator and a scalable soldier-machine interface

    Science.gov (United States)

    Johnson, Tony; Manteuffel, Chris; Brewster, Benjamin; Tierney, Terry

    2007-04-01

    As the Army's Future Combat Systems (FCS) introduce emerging technologies and new force structures to the battlefield, soldiers will increasingly face new challenges in workload management. The next generation warfighter will be responsible for effectively managing robotic assets in addition to performing other missions. Studies of future battlefield operational scenarios involving the use of automation, including the specification of existing and proposed technologies, will provide significant insight into potential problem areas regarding soldier workload. The US Army Tank Automotive Research, Development, and Engineering Center (TARDEC) is currently executing an Army technology objective program to analyze and evaluate the effect of automated technologies and their associated control devices with respect to soldier workload. The Human-Robotic Interface (HRI) Intelligent Systems Behavior Simulator (ISBS) is a human performance measurement simulation system that allows modelers to develop constructive simulations of military scenarios with various deployments of interface technologies in order to evaluate operator effectiveness. One such interface is TARDEC's Scalable Soldier-Machine Interface (SMI). The scalable SMI provides a configurable machine interface application that is capable of adapting to several hardware platforms by recognizing the physical space limitations of the display device. This paper describes the integration of the ISBS and Scalable SMI applications, which will ultimately benefit both systems. The ISBS will be able to use the Scalable SMI to visualize the behaviors of virtual soldiers performing HRI tasks, such as route planning, and the scalable SMI will benefit from stimuli provided by the ISBS simulation environment. The paper describes the background of each system and details of the system integration approach.

  12. Oracle database performance and scalability a quantitative approach

    CERN Document Server

    Liu, Henry H

    2011-01-01

    A data-driven, fact-based, quantitative text on Oracle performance and scalability With database concepts and theories clearly explained in Oracle's context, readers quickly learn how to fully leverage Oracle's performance and scalability capabilities at every stage of designing and developing an Oracle-based enterprise application. The book is based on the author's more than ten years of experience working with Oracle, and is filled with dependable, tested, and proven performance optimization techniques. Oracle Database Performance and Scalability is divided into four parts that enable reader

  13. Scalable-to-lossless transform domain distributed video coding

    DEFF Research Database (Denmark)

    Huang, Xin; Ukhanova, Ann; Veselov, Anton

    2010-01-01

    Distributed video coding (DVC) is a novel approach providing new features as low complexity encoding by mainly exploiting the source statistics at the decoder based on the availability of decoder side information. In this paper, scalable-tolossless DVC is presented based on extending a lossy Tran...... codec provides frame by frame encoding. Comparing the lossless coding efficiency, the proposed scalable-to-lossless TDWZ video codec can save up to 5%-13% bits compared to JPEG LS and H.264 Intra frame lossless coding and do so as a scalable-to-lossless coding....

  14. Building Scalable Knowledge Graphs for Earth Science

    Science.gov (United States)

    Ramachandran, R.; Maskey, M.; Gatlin, P. N.; Zhang, J.; Duan, X.; Bugbee, K.; Christopher, S. A.; Miller, J. J.

    2017-12-01

    Estimates indicate that the world's information will grow by 800% in the next five years. In any given field, a single researcher or a team of researchers cannot keep up with this rate of knowledge expansion without the help of cognitive systems. Cognitive computing, defined as the use of information technology to augment human cognition, can help tackle large systemic problems. Knowledge graphs, one of the foundational components of cognitive systems, link key entities in a specific domain with other entities via relationships. Researchers could mine these graphs to make probabilistic recommendations and to infer new knowledge. At this point, however, there is a dearth of tools to generate scalable Knowledge graphs using existing corpus of scientific literature for Earth science research. Our project is currently developing an end-to-end automated methodology for incrementally constructing Knowledge graphs for Earth Science. Semantic Entity Recognition (SER) is one of the key steps in this methodology. SER for Earth Science uses external resources (including metadata catalogs and controlled vocabulary) as references to guide entity extraction and recognition (i.e., labeling) from unstructured text, in order to build a large training set to seed the subsequent auto-learning component in our algorithm. Results from several SER experiments will be presented as well as lessons learned.

  15. CODA: A scalable, distributed data acquisition system

    International Nuclear Information System (INIS)

    Watson, W.A. III; Chen, J.; Heyes, G.; Jastrzembski, E.; Quarrie, D.

    1994-01-01

    A new data acquisition system has been designed for physics experiments scheduled to run at CEBAF starting in the summer of 1994. This system runs on Unix workstations connected via ethernet, FDDI, or other network hardware to multiple intelligent front end crates -- VME, CAMAC or FASTBUS. CAMAC crates may either contain intelligent processors, or may be interfaced to VME. The system is modular and scalable, from a single front end crate and one workstation linked by ethernet, to as may as 32 clusters of front end crates ultimately connected via a high speed network to a set of analysis workstations. The system includes an extensible, device independent slow controls package with drivers for CAMAC, VME, and high voltage crates, as well as a link to CEBAF accelerator controls. All distributed processes are managed by standard remote procedure calls propagating change-of-state requests, or reading and writing program variables. Custom components may be easily integrated. The system is portable to any front end processor running the VxWorks real-time kernel, and to most workstations supplying a few standard facilities such as rsh and X-windows, and Motif and socket libraries. Sample implementations exist for 2 Unix workstation families connected via ethernet or FDDI to VME (with interfaces to FASTBUS or CAMAC), and via ethernet to FASTBUS or CAMAC

  16. Ancestors protocol for scalable key management

    Directory of Open Access Journals (Sweden)

    Dieter Gollmann

    2010-06-01

    Full Text Available Group key management is an important functional building block for secure multicast architecture. Thereby, it has been extensively studied in the literature. The main proposed protocol is Adaptive Clustering for Scalable Group Key Management (ASGK. According to ASGK protocol, the multicast group is divided into clusters, where each cluster consists of areas of members. Each cluster uses its own Traffic Encryption Key (TEK. These clusters are updated periodically depending on the dynamism of the members during the secure session. The modified protocol has been proposed based on ASGK with some modifications to balance the number of affected members and the encryption/decryption overhead with any number of the areas when a member joins or leaves the group. This modified protocol is called Ancestors protocol. According to Ancestors protocol, every area receives the dynamism of the members from its parents. The main objective of the modified protocol is to reduce the number of affected members during the leaving and joining members, then 1 affects n overhead would be reduced. A comparative study has been done between ASGK protocol and the modified protocol. According to the comparative results, it found that the modified protocol is always outperforming the ASGK protocol.

  17. Percolator: Scalable Pattern Discovery in Dynamic Graphs

    Energy Technology Data Exchange (ETDEWEB)

    Choudhury, Sutanay; Purohit, Sumit; Lin, Peng; Wu, Yinghui; Holder, Lawrence B.; Agarwal, Khushbu

    2018-02-06

    We demonstrate Percolator, a distributed system for graph pattern discovery in dynamic graphs. In contrast to conventional mining systems, Percolator advocates efficient pattern mining schemes that (1) support pattern detection with keywords; (2) integrate incremental and parallel pattern mining; and (3) support analytical queries such as trend analysis. The core idea of Percolator is to dynamically decide and verify a small fraction of patterns and their in- stances that must be inspected in response to buffered updates in dynamic graphs, with a total mining cost independent of graph size. We demonstrate a) the feasibility of incremental pattern mining by walking through each component of Percolator, b) the efficiency and scalability of Percolator over the sheer size of real-world dynamic graphs, and c) how the user-friendly GUI of Percolator inter- acts with users to support keyword-based queries that detect, browse and inspect trending patterns. We also demonstrate two user cases of Percolator, in social media trend analysis and academic collaboration analysis, respectively.

  18. Scalable Notch Antenna System for Multiport Applications

    Directory of Open Access Journals (Sweden)

    Abdurrahim Toktas

    2016-01-01

    Full Text Available A novel and compact scalable antenna system is designed for multiport applications. The basic design is built on a square patch with an electrical size of 0.82λ0×0.82λ0 (at 2.4 GHz on a dielectric substrate. The design consists of four symmetrical and orthogonal triangular notches with circular feeding slots at the corners of the common patch. The 4-port antenna can be simply rearranged to 8-port and 12-port systems. The operating band of the system can be tuned by scaling (S the size of the system while fixing the thickness of the substrate. The antenna system with S: 1/1 in size of 103.5×103.5 mm2 operates at the frequency band of 2.3–3.0 GHz. By scaling the antenna with S: 1/2.3, a system of 45×45 mm2 is achieved, and thus the operating band is tuned to 4.7–6.1 GHz with the same scattering characteristic. A parametric study is also conducted to investigate the effects of changing the notch dimensions. The performance of the antenna is verified in terms of the antenna characteristics as well as diversity and multiplexing parameters. The antenna system can be tuned by scaling so that it is applicable to the multiport WLAN, WIMAX, and LTE devices with port upgradability.

  19. Scalable conditional induction variables (CIV) analysis

    KAUST Repository

    Oancea, Cosmin E.

    2015-02-01

    Subscripts using induction variables that cannot be expressed as a formula in terms of the enclosing-loop indices appear in the low-level implementation of common programming abstractions such as Alter, or stack operations and pose significant challenges to automatic parallelization. Because the complexity of such induction variables is often due to their conditional evaluation across the iteration space of loops we name them Conditional Induction Variables (CIV). This paper presents a flow-sensitive technique that summarizes both such CIV-based and affine subscripts to program level, using the same representation. Our technique requires no modifications of our dependence tests, which is agnostic to the original shape of the subscripts, and is more powerful than previously reported dependence tests that rely on the pairwise disambiguation of read-write references. We have implemented the CIV analysis in our parallelizing compiler and evaluated its impact on five Fortran benchmarks. We have found that that there are many important loops using CIV subscripts and that our analysis can lead to their scalable parallelization. This in turn has led to the parallelization of the benchmark programs they appear in.

  20. A Programmable, Scalable-Throughput Interleaver

    Directory of Open Access Journals (Sweden)

    E. J. C. Rijshouwer

    2010-01-01

    Full Text Available The interleaver stages of digital communication standards show a surprisingly large variation in throughput, state sizes, and permutation functions. Furthermore, data rates for 4G standards such as LTE-Advanced will exceed typical baseband clock frequencies of handheld devices. Multistream operation for Software Defined Radio and iterative decoding algorithms will call for ever higher interleave data rates. Our interleave machine is built around 8 single-port SRAM banks and can be programmed to generate up to 8 addresses every clock cycle. The scalable architecture combines SIMD and VLIW concepts with an efficient resolution of bank conflicts. A wide range of cellular, connectivity, and broadcast interleavers have been mapped on this machine, with throughputs up to more than 0.5 Gsymbol/second. Although it was designed for channel interleaving, the application domain of the interleaver extends also to Turbo interleaving. The presented configuration of the architecture is designed as a part of a programmable outer receiver on a prototype board. It offers (near universal programmability to enable the implementation of new interleavers. The interleaver measures 2.09 mm2 in 65 nm CMOS (including memories and proves functional on silicon.

  1. A Programmable, Scalable-Throughput Interleaver

    Directory of Open Access Journals (Sweden)

    Rijshouwer EJC

    2010-01-01

    Full Text Available The interleaver stages of digital communication standards show a surprisingly large variation in throughput, state sizes, and permutation functions. Furthermore, data rates for 4G standards such as LTE-Advanced will exceed typical baseband clock frequencies of handheld devices. Multistream operation for Software Defined Radio and iterative decoding algorithms will call for ever higher interleave data rates. Our interleave machine is built around 8 single-port SRAM banks and can be programmed to generate up to 8 addresses every clock cycle. The scalable architecture combines SIMD and VLIW concepts with an efficient resolution of bank conflicts. A wide range of cellular, connectivity, and broadcast interleavers have been mapped on this machine, with throughputs up to more than 0.5 Gsymbol/second. Although it was designed for channel interleaving, the application domain of the interleaver extends also to Turbo interleaving. The presented configuration of the architecture is designed as a part of a programmable outer receiver on a prototype board. It offers (near universal programmability to enable the implementation of new interleavers. The interleaver measures 2.09 m in 65 nm CMOS (including memories and proves functional on silicon.

  2. Enabling Highly-Scalable Remote Memory Access Programming with MPI-3 One Sided

    Directory of Open Access Journals (Sweden)

    Robert Gerstenberger

    2014-01-01

    Full Text Available Modern interconnects offer remote direct memory access (RDMA features. Yet, most applications rely on explicit message passing for communications albeit their unwanted overheads. The MPI-3.0 standard defines a programming interface for exploiting RDMA networks directly, however, it's scalability and practicability has to be demonstrated in practice. In this work, we develop scalable bufferless protocols that implement the MPI-3.0 specification. Our protocols support scaling to millions of cores with negligible memory consumption while providing highest performance and minimal overheads. To arm programmers, we provide a spectrum of performance models for all critical functions and demonstrate the usability of our library and models with several application studies with up to half a million processes. We show that our design is comparable to, or better than UPC and Fortran Coarrays in terms of latency, bandwidth and message rate. We also demonstrate application performance improvements with comparable programming complexity.

  3. A Testbed for Highly-Scalable Mission Critical Information Systems

    National Research Council Canada - National Science Library

    Birman, Kenneth P

    2005-01-01

    ... systems in a networked environment. Headed by Professor Ken Birman, the project is exploring a novel fusion of classical protocols for reliable multicast communication with a new style of peer-to-peer protocol called scalable "gossip...

  4. Scalable Partitioning Algorithms for FPGAs With Heterogeneous Resources

    National Research Council Canada - National Science Library

    Selvakkumaran, Navaratnasothie; Ranjan, Abhishek; Raje, Salil; Karypis, George

    2004-01-01

    As FPGA densities increase, partitioning-based FPGA placement approaches are becoming increasingly important as they can be used to provide high-quality and computationally scalable placement solutions...

  5. SOL: A Library for Scalable Online Learning Algorithms

    OpenAIRE

    Wu, Yue; Hoi, Steven C. H.; Liu, Chenghao; Lu, Jing; Sahoo, Doyen; Yu, Nenghai

    2016-01-01

    SOL is an open-source library for scalable online learning algorithms, and is particularly suitable for learning with high-dimensional data. The library provides a family of regular and sparse online learning algorithms for large-scale binary and multi-class classification tasks with high efficiency, scalability, portability, and extensibility. SOL was implemented in C++, and provided with a collection of easy-to-use command-line tools, python wrappers and library calls for users and develope...

  6. Modular Universal Scalable Ion-trap Quantum Computer

    Science.gov (United States)

    2016-06-02

    SECURITY CLASSIFICATION OF: The main goal of the original MUSIQC proposal was to construct and demonstrate a modular and universally- expandable ion...Distribution Unlimited UU UU UU UU 02-06-2016 1-Aug-2010 31-Jan-2016 Final Report: Modular Universal Scalable Ion-trap Quantum Computer The views...P.O. Box 12211 Research Triangle Park, NC 27709-2211 Ion trap quantum computation, scalable modular architectures REPORT DOCUMENTATION PAGE 11

  7. Architectures and Applications for Scalable Quantum Information Systems

    Science.gov (United States)

    2007-01-01

    Gershenfeld and I. Chuang. Quantum computing with molecules. Scientific American, June 1998. [16] A. Globus, D. Bailey, J. Han, R. Jaffe, C. Levit , R...AFRL-IF-RS-TR-2007-12 Final Technical Report January 2007 ARCHITECTURES AND APPLICATIONS FOR SCALABLE QUANTUM INFORMATION SYSTEMS...NUMBER 5b. GRANT NUMBER FA8750-01-2-0521 4. TITLE AND SUBTITLE ARCHITECTURES AND APPLICATIONS FOR SCALABLE QUANTUM INFORMATION SYSTEMS 5c

  8. On the scalability of LISP and advanced overlaid services

    OpenAIRE

    Coras, Florin

    2015-01-01

    In just four decades the Internet has gone from a lab experiment to a worldwide, business critical infrastructure that caters to the communication needs of almost a half of the Earth's population. With these figures on its side, arguing against the Internet's scalability would seem rather unwise. However, the Internet's organic growth is far from finished and, as billions of new devices are expected to be joined in the not so distant future, scalability, or lack thereof, is commonly believed ...

  9. Scalable, full-colour and controllable chromotropic plasmonic printing

    OpenAIRE

    Xue, Jiancai; Zhou, Zhang-Kai; Wei, Zhiqiang; Su, Rongbin; Lai, Juan; Li, Juntao; Li, Chao; Zhang, Tengwei; Wang, Xue-Hua

    2015-01-01

    Plasmonic colour printing has drawn wide attention as a promising candidate for the next-generation colour-printing technology. However, an efficient approach to realize full colour and scalable fabrication is still lacking, which prevents plasmonic colour printing from practical applications. Here we present a scalable and full-colour plasmonic printing approach by combining conjugate twin-phase modulation with a plasmonic broadband absorber. More importantly, our approach also demonstrates ...

  10. Microscopic Characterization of Scalable Coherent Rydberg Superatoms

    Directory of Open Access Journals (Sweden)

    Johannes Zeiher

    2015-08-01

    Full Text Available Strong interactions can amplify quantum effects such that they become important on macroscopic scales. Controlling these coherently on a single-particle level is essential for the tailored preparation of strongly correlated quantum systems and opens up new prospects for quantum technologies. Rydberg atoms offer such strong interactions, which lead to extreme nonlinearities in laser-coupled atomic ensembles. As a result, multiple excitation of a micrometer-sized cloud can be blocked while the light-matter coupling becomes collectively enhanced. The resulting two-level system, often called a “superatom,” is a valuable resource for quantum information, providing a collective qubit. Here, we report on the preparation of 2 orders of magnitude scalable superatoms utilizing the large interaction strength provided by Rydberg atoms combined with precise control of an ensemble of ultracold atoms in an optical lattice. The latter is achieved with sub-shot-noise precision by local manipulation of a two-dimensional Mott insulator. We microscopically confirm the superatom picture by in situ detection of the Rydberg excitations and observe the characteristic square-root scaling of the optical coupling with the number of atoms. Enabled by the full control over the atomic sample, including the motional degrees of freedom, we infer the overlap of the produced many-body state with a W state from the observed Rabi oscillations and deduce the presence of entanglement. Finally, we investigate the breakdown of the superatom picture when two Rydberg excitations are present in the system, which leads to dephasing and a loss of coherence.

  11. SAChES: Scalable Adaptive Chain-Ensemble Sampling.

    Energy Technology Data Exchange (ETDEWEB)

    Swiler, Laura Painton [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ray, Jaideep [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Ebeida, Mohamed Salah [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Huang, Maoyi [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hou, Zhangshuan [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Bao, Jie [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Ren, Huiying [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2017-08-01

    We present the development of a parallel Markov Chain Monte Carlo (MCMC) method called SAChES, Scalable Adaptive Chain-Ensemble Sampling. This capability is targed to Bayesian calibration of com- putationally expensive simulation models. SAChES involves a hybrid of two methods: Differential Evo- lution Monte Carlo followed by Adaptive Metropolis. Both methods involve parallel chains. Differential evolution allows one to explore high-dimensional parameter spaces using loosely coupled (i.e., largely asynchronous) chains. Loose coupling allows the use of large chain ensembles, with far more chains than the number of parameters to explore. This reduces per-chain sampling burden, enables high-dimensional inversions and the use of computationally expensive forward models. The large number of chains can also ameliorate the impact of silent-errors, which may affect only a few chains. The chain ensemble can also be sampled to provide an initial condition when an aberrant chain is re-spawned. Adaptive Metropolis takes the best points from the differential evolution and efficiently hones in on the poste- rior density. The multitude of chains in SAChES is leveraged to (1) enable efficient exploration of the parameter space; and (2) ensure robustness to silent errors which may be unavoidable in extreme-scale computational platforms of the future. This report outlines SAChES, describes four papers that are the result of the project, and discusses some additional results.

  12. GASPRNG: GPU accelerated scalable parallel random number generator library

    Science.gov (United States)

    Gao, Shuang; Peterson, Gregory D.

    2013-04-01

    Graphics processors represent a promising technology for accelerating computational science applications. Many computational science applications require fast and scalable random number generation with good statistical properties, so they use the Scalable Parallel Random Number Generators library (SPRNG). We present the GPU Accelerated SPRNG library (GASPRNG) to accelerate SPRNG in GPU-based high performance computing systems. GASPRNG includes code for a host CPU and CUDA code for execution on NVIDIA graphics processing units (GPUs) along with a programming interface to support various usage models for pseudorandom numbers and computational science applications executing on the CPU, GPU, or both. This paper describes the implementation approach used to produce high performance and also describes how to use the programming interface. The programming interface allows a user to be able to use GASPRNG the same way as SPRNG on traditional serial or parallel computers as well as to develop tightly coupled programs executing primarily on the GPU. We also describe how to install GASPRNG and use it. To help illustrate linking with GASPRNG, various demonstration codes are included for the different usage models. GASPRNG on a single GPU shows up to 280x speedup over SPRNG on a single CPU core and is able to scale for larger systems in the same manner as SPRNG. Because GASPRNG generates identical streams of pseudorandom numbers as SPRNG, users can be confident about the quality of GASPRNG for scalable computational science applications. Catalogue identifier: AEOI_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEOI_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: UTK license. No. of lines in distributed program, including test data, etc.: 167900 No. of bytes in distributed program, including test data, etc.: 1422058 Distribution format: tar.gz Programming language: C and CUDA. Computer: Any PC or

  13. Designing Psychological Treatments for Scalability: The PREMIUM Approach.

    Directory of Open Access Journals (Sweden)

    Sukumar Vellakkal

    Full Text Available Lack of access to empirically-supported psychological treatments (EPT that are contextually appropriate and feasible to deliver by non-specialist health workers (referred to as 'counsellors' are major barrier for the treatment of mental health problems in resource poor countries. To address this barrier, the 'Program for Effective Mental Health Interventions in Under-resourced Health Systems' (PREMIUM designed a method for the development of EPT for severe depression and harmful drinking. This was implemented over three years in India. This study assessed the relative usefulness and costs of the five 'steps' (Systematic reviews, In-depth interviews, Key informant surveys, Workshops with international experts, and Workshops with local experts in the first phase of identifying the strategies and theoretical model of the treatment and two 'steps' (Case series with specialists, and Case series and pilot trial with counsellors in the second phase of enhancing the acceptability and feasibility of its delivery by counsellors in PREMIUM with the aim of arriving at a parsimonious set of steps for future investigators to use for developing scalable EPT.The study used two sources of data: the usefulness ratings by the investigators and the resource utilization. The usefulness of each of the seven steps was assessed through the ratings by the investigators involved in the development of each of the two EPT, viz. Healthy Activity Program for severe depression and Counselling for Alcohol Problems for harmful drinking. Quantitative responses were elicited to rate the utility (usefulness/influence, followed by open-ended questions for explaining the rankings. The resources used by PREMIUM were computed in terms of time (months and monetary costs.The theoretical core of the new treatments were consistent with those of EPT derived from global evidence, viz. Behavioural Activation and Motivational Enhancement for severe depression and harmful drinking respectively

  14. GPU-based Scalable Volumetric Reconstruction for Multi-view Stereo

    Energy Technology Data Exchange (ETDEWEB)

    Kim, H; Duchaineau, M; Max, N

    2011-09-21

    We present a new scalable volumetric reconstruction algorithm for multi-view stereo using a graphics processing unit (GPU). It is an effectively parallelized GPU algorithm that simultaneously uses a large number of GPU threads, each of which performs voxel carving, in order to integrate depth maps with images from multiple views. Each depth map, triangulated from pair-wise semi-dense correspondences, represents a view-dependent surface of the scene. This algorithm also provides scalability for large-scale scene reconstruction in a high resolution voxel grid by utilizing streaming and parallel computation. The output is a photo-realistic 3D scene model in a volumetric or point-based representation. We demonstrate the effectiveness and the speed of our algorithm with a synthetic scene and real urban/outdoor scenes. Our method can also be integrated with existing multi-view stereo algorithms such as PMVS2 to fill holes or gaps in textureless regions.

  15. A Bit Stream Scalable Speech/Audio Coder Combining Enhanced Regular Pulse Excitation and Parametric Coding

    Science.gov (United States)

    Riera-Palou, Felip; den Brinker, Albertus C.

    2007-12-01

    This paper introduces a new audio and speech broadband coding technique based on the combination of a pulse excitation coder and a standardized parametric coder, namely, MPEG-4 high-quality parametric coder. After presenting a series of enhancements to regular pulse excitation (RPE) to make it suitable for the modeling of broadband signals, it is shown how pulse and parametric codings complement each other and how they can be merged to yield a layered bit stream scalable coder able to operate at different points in the quality bit rate plane. The performance of the proposed coder is evaluated in a listening test. The major result is that the extra functionality of the bit stream scalability does not come at the price of a reduced performance since the coder is competitive with standardized coders (MP3, AAC, SSC).

  16. A Bit Stream Scalable Speech/Audio Coder Combining Enhanced Regular Pulse Excitation and Parametric Coding

    Directory of Open Access Journals (Sweden)

    Albertus C. den Brinker

    2007-01-01

    Full Text Available This paper introduces a new audio and speech broadband coding technique based on the combination of a pulse excitation coder and a standardized parametric coder, namely, MPEG-4 high-quality parametric coder. After presenting a series of enhancements to regular pulse excitation (RPE to make it suitable for the modeling of broadband signals, it is shown how pulse and parametric codings complement each other and how they can be merged to yield a layered bit stream scalable coder able to operate at different points in the quality bit rate plane. The performance of the proposed coder is evaluated in a listening test. The major result is that the extra functionality of the bit stream scalability does not come at the price of a reduced performance since the coder is competitive with standardized coders (MP3, AAC, SSC.

  17. A Scalable Parallel PWTD-Accelerated SIE Solver for Analyzing Transient Scattering from Electrically Large Objects

    KAUST Repository

    Liu, Yang

    2015-12-17

    A scalable parallel plane-wave time-domain (PWTD) algorithm for efficient and accurate analysis of transient scattering from electrically large objects is presented. The algorithm produces scalable communication patterns on very large numbers of processors by leveraging two mechanisms: (i) a hierarchical parallelization strategy to evenly distribute the computation and memory loads at all levels of the PWTD tree among processors, and (ii) a novel asynchronous communication scheme to reduce the cost and memory requirement of the communications between the processors. The efficiency and accuracy of the algorithm are demonstrated through its applications to the analysis of transient scattering from a perfect electrically conducting (PEC) sphere with a diameter of 70 wavelengths and a PEC square plate with a dimension of 160 wavelengths. Furthermore, the proposed algorithm is used to analyze transient fields scattered from realistic airplane and helicopter models under high frequency excitation.

  18. Laplacian embedded regression for scalable manifold regularization.

    Science.gov (United States)

    Chen, Lin; Tsang, Ivor W; Xu, Dong

    2012-06-01

    world data sets show the effectiveness and scalability of the proposed framework.

  19. Decentralized control of a scalable photovoltaic (PV)-battery hybrid power system

    International Nuclear Information System (INIS)

    Kim, Myungchin; Bae, Sungwoo

    2017-01-01

    Highlights: • This paper introduces the design and control of a PV-battery hybrid power system. • Reliable and scalable operation of hybrid power systems is achieved. • System and power control are performed without a centralized controller. • Reliability and scalability characteristics are studied in a quantitative manner. • The system control performance is verified using realistic solar irradiation data. - Abstract: This paper presents the design and control of a sustainable standalone photovoltaic (PV)-battery hybrid power system (HPS). The research aims to develop an approach that contributes to increased level of reliability and scalability for an HPS. To achieve such objectives, a PV-battery HPS with a passively connected battery was studied. A quantitative hardware reliability analysis was performed to assess the effect of energy storage configuration to the overall system reliability. Instead of requiring the feedback control information of load power through a centralized supervisory controller, the power flow in the proposed HPS is managed by a decentralized control approach that takes advantage of the system architecture. Reliable system operation of an HPS is achieved through the proposed control approach by not requiring a separate supervisory controller. Furthermore, performance degradation of energy storage can be prevented by selecting the controller gains such that the charge rate does not exceed operational requirements. The performance of the proposed system architecture with the control strategy was verified by simulation results using realistic irradiance data and a battery model in which its temperature effect was considered. With an objective to support scalable operation, details on how the proposed design could be applied were also studied so that the HPS could satisfy potential system growth requirements. Such scalability was verified by simulating various cases that involve connection and disconnection of sources and loads. The

  20. The Scalable Coherent Interface and related standards projects

    International Nuclear Information System (INIS)

    Gustavson, D.B.

    1991-09-01

    The Scalable Coherent Interface (SCI) project (IEEE P1596) found a way to avoid the limits that are inherent in bus technology. SCI provides bus-like services by transmitting packets on a collection of point-to-point unidirectional links. The SCI protocols support cache coherence in a distributed-shared-memory multiprocessor model, message passing, I/O, and local-area-network-like communication over fiber optic or wire links. VLSI circuits that operate parallel links at 1000 MByte/s and serial links at 1000 Mbit/s will be available early in 1992. Several ongoing SCI-related projects are applying the SCI technology to new areas or extending it to more difficult problems. P1596.1 defines the architecture of a bridge between SCI and VME; P1596.2 compatibly extends the cache coherence mechanism for efficient operation with kiloprocessor systems; P1596.3 defines new low-voltage (about 0.25 V) differential signals suitable for low power interfaces for CMOS or GaAs VLSI implementations of SCI; P1596.4 defines a high performance memory chip interface using these signals; P1596.5 defines data transfer formats for efficient interprocessor communication in heterogeneous multiprocessor systems. This paper reports the current status of SCI, related standards, and new projects. 16 refs

  1. A scalable platform for biomechanical studies of tissue cutting forces

    International Nuclear Information System (INIS)

    Valdastri, P; Tognarelli, S; Menciassi, A; Dario, P

    2009-01-01

    This paper presents a novel and scalable experimental platform for biomechanical analysis of tissue cutting that exploits a triaxial force-sensitive scalpel and a high resolution vision system. Real-time measurements of cutting forces can be used simultaneously with accurate visual information in order to extract important biomechanical clues in real time that would aid the surgeon during minimally invasive intervention in preserving healthy tissues. Furthermore, the in vivo data gathered can be used for modeling the viscoelastic behavior of soft tissues, which is an important issue in surgical simulator development. Thanks to a modular approach, this platform can be scaled down, thus enabling in vivo real-time robotic applications. Several cutting experiments were conducted with soft porcine tissues (lung, liver and kidney) chosen as ideal candidates for biopsy procedures. The cutting force curves show repeated self-similar units of localized loading followed by unloading. With regards to tissue properties, the depth of cut plays a significant role in the magnitude of the cutting force acting on the blade. Image processing techniques and dedicated algorithms were used to outline the surface of the tissues and estimate the time variation of the depth of cut. The depth of cut was finally used to obtain the normalized cutting force, thus allowing comparative biomechanical analysis

  2. Toward a Scalable and Sustainable Intervention for Complementary Food Safety.

    Science.gov (United States)

    Rahman, Musarrat J; Nizame, Fosiul A; Nuruzzaman, Mohammad; Akand, Farhana; Islam, Mohammad Aminul; Parvez, Sarker Masud; Stewart, Christine P; Unicomb, Leanne; Luby, Stephen P; Winch, Peter J

    2016-06-01

    Contaminated complementary foods are associated with diarrhea and malnutrition among children aged 6 to 24 months. However, existing complementary food safety intervention models are likely not scalable and sustainable. To understand current behaviors, motivations for these behaviors, and the potential barriers to behavior change and to identify one or two simple actions that can address one or few food contamination pathways and have potential to be sustainably delivered to a larger population. Data were collected from 2 rural sites in Bangladesh through semistructured observations (12), video observations (12), in-depth interviews (18), and focus group discussions (3). Although mothers report preparing dedicated foods for children, observations show that these are not separate from family foods. Children are regularly fed store-bought foods that are perceived to be bad for children. Mothers explained that long storage durations, summer temperatures, flies, animals, uncovered food, and unclean utensils are threats to food safety. Covering foods, storing foods on elevated surfaces, and reheating foods before consumption are methods believed to keep food safe. Locally made cabinet-like hardware is perceived to be acceptable solution to address reported food safety threats. Conventional approaches that include teaching food safety and highlighting benefits such as reduced contamination may be a disincentive for rural mothers who need solutions for their physical environment. We propose extending existing beneficial behaviors by addressing local preferences of taste and convenience. © The Author(s) 2016.

  3. Scalable Pressure Sensor Based on Electrothermally Operated Resonator

    KAUST Repository

    Hajjaj, Amal Z.; Hafiz, Md Abdullah Al; Alcheikh, Nouha; Younis, Mohammad I.

    2017-01-01

    We experimentally demonstrate a new pressure sensor that offers the flexibility of being scalable to small sizes up to the nano regime. Unlike conventional pressure sensors that rely on large diaphragms and big-surface structures, the principle of operation here relies on convective cooling of the air surrounding an electrothermally heated resonant structure, which can be a beam or a bridge. This concept is demonstrated using an electrothermally tuned and electrostatically driven MEMS resonator, which is designed to be deliberately curved. We show that the variation of pressure can be tracked accurately by monitoring the change in the resonance frequency of the resonator at a constant electrothermal voltage. We show that the range of the sensed pressure and the sensitivity of detection are controllable by the amount of the applied electrothermal voltage. Theoretically, we verify the device concept using a multi-physics nonlinear finite element model. The proposed pressure sensor is simple in principle and design and offers the possibility of further miniaturization to the nanoscale.

  4. Scalable Pressure Sensor Based on Electrothermally Operated Resonator

    KAUST Repository

    Hajjaj, Amal Z.

    2017-11-03

    We experimentally demonstrate a new pressure sensor that offers the flexibility of being scalable to small sizes up to the nano regime. Unlike conventional pressure sensors that rely on large diaphragms and big-surface structures, the principle of operation here relies on convective cooling of the air surrounding an electrothermally heated resonant structure, which can be a beam or a bridge. This concept is demonstrated using an electrothermally tuned and electrostatically driven MEMS resonator, which is designed to be deliberately curved. We show that the variation of pressure can be tracked accurately by monitoring the change in the resonance frequency of the resonator at a constant electrothermal voltage. We show that the range of the sensed pressure and the sensitivity of detection are controllable by the amount of the applied electrothermal voltage. Theoretically, we verify the device concept using a multi-physics nonlinear finite element model. The proposed pressure sensor is simple in principle and design and offers the possibility of further miniaturization to the nanoscale.

  5. Superhydrophobic hierarchical arrays fabricated by a scalable colloidal lithography approach.

    Science.gov (United States)

    Kothary, Pratik; Dou, Xuan; Fang, Yin; Gu, Zhuxiao; Leo, Sin-Yen; Jiang, Peng

    2017-02-01

    Here we report an unconventional colloidal lithography approach for fabricating a variety of periodic polymer nanostructures with tunable geometries and hydrophobic properties. Wafer-sized, double-layer, non-close-packed silica colloidal crystal embedded in a polymer matrix is first assembled by a scalable spin-coating technology. The unusual non-close-packed crystal structure combined with a thin polymer film separating the top and the bottom colloidal layers render great versatility in templating periodic nanostructures, including arrays of nanovoids, nanorings, and hierarchical nanovoids. These different geometries result in varied fractions of entrapped air in between the templated nanostructures, which in turn lead to different apparent water contact angles. Superhydrophobic surfaces with >150° water contact angles and <5° contact angle hysteresis are achieved on fluorosilane-modified polymer hierarchical nanovoid arrays with large fractions of entrapped air. The experimental contact angle measurements are complemented with theoretical predictions using the Cassie's model to gain insights into the fundamental microstructure-dewetting property relationships. The experimental and theoretical contact angles follow the same trends as determined by the unique hierarchical structures of the templated periodic arrays. Copyright © 2016 Elsevier Inc. All rights reserved.

  6. Scalable and Flexible Multiview MAX-VAR Canonical Correlation Analysis

    Science.gov (United States)

    Fu, Xiao; Huang, Kejun; Hong, Mingyi; Sidiropoulos, Nicholas D.; So, Anthony Man-Cho

    2017-08-01

    Generalized canonical correlation analysis (GCCA) aims at finding latent low-dimensional common structure from multiple views (feature vectors in different domains) of the same entities. Unlike principal component analysis (PCA) that handles a single view, (G)CCA is able to integrate information from different feature spaces. Here we focus on MAX-VAR GCCA, a popular formulation which has recently gained renewed interest in multilingual processing and speech modeling. The classic MAX-VAR GCCA problem can be solved optimally via eigen-decomposition of a matrix that compounds the (whitened) correlation matrices of the views; but this solution has serious scalability issues, and is not directly amenable to incorporating pertinent structural constraints such as non-negativity and sparsity on the canonical components. We posit regularized MAX-VAR GCCA as a non-convex optimization problem and propose an alternating optimization (AO)-based algorithm to handle it. Our algorithm alternates between {\\em inexact} solutions of a regularized least squares subproblem and a manifold-constrained non-convex subproblem, thereby achieving substantial memory and computational savings. An important benefit of our design is that it can easily handle structure-promoting regularization. We show that the algorithm globally converges to a critical point at a sublinear rate, and approaches a global optimal solution at a linear rate when no regularization is considered. Judiciously designed simulations and large-scale word embedding tasks are employed to showcase the effectiveness of the proposed algorithm.

  7. New Region-Scalable Discriminant and Fitting Energy Functional for Driving Geometric Active Contours in Medical Image Segmentation

    Directory of Open Access Journals (Sweden)

    Xuchu Wang

    2014-01-01

    that uses region-scalable discriminant and fitting energy functional for handling the intensity inhomogeneity and weak boundary problems in medical image segmentation. The region-scalable discriminant and fitting energy functional is defined to capture the image intensity characteristics in local and global regions for driving the evolution of active contour. The discriminant term in the model aims at separating background and foreground in scalable regions while the fitting term tends to fit the intensity in these regions. This model is then transformed into a variational level set formulation with a level set regularization term for accurate computation. The new model utilizes intensity information in the local and global regions as much as possible; so it not only handles better intensity inhomogeneity, but also allows more robustness to noise and more flexible initialization in comparison to the original global region and regional-scalable based models. Experimental results for synthetic and real medical image segmentation show the advantages of the proposed method in terms of accuracy and robustness.

  8. ParaText : scalable solutions for processing and searching very large document collections : final LDRD report.

    Energy Technology Data Exchange (ETDEWEB)

    Crossno, Patricia Joyce; Dunlavy, Daniel M.; Stanton, Eric T.; Shead, Timothy M.

    2010-09-01

    This report is a summary of the accomplishments of the 'Scalable Solutions for Processing and Searching Very Large Document Collections' LDRD, which ran from FY08 through FY10. Our goal was to investigate scalable text analysis; specifically, methods for information retrieval and visualization that could scale to extremely large document collections. Towards that end, we designed, implemented, and demonstrated a scalable framework for text analysis - ParaText - as a major project deliverable. Further, we demonstrated the benefits of using visual analysis in text analysis algorithm development, improved performance of heterogeneous ensemble models in data classification problems, and the advantages of information theoretic methods in user analysis and interpretation in cross language information retrieval. The project involved 5 members of the technical staff and 3 summer interns (including one who worked two summers). It resulted in a total of 14 publications, 3 new software libraries (2 open source and 1 internal to Sandia), several new end-user software applications, and over 20 presentations. Several follow-on projects have already begun or will start in FY11, with additional projects currently in proposal.

  9. Differentiation of Human Pluripotent Stem Cells into Functional Endothelial Cells in Scalable Suspension Culture

    Directory of Open Access Journals (Sweden)

    Ruth Olmer

    2018-05-01

    Full Text Available Summary: Endothelial cells (ECs are involved in a variety of cellular responses. As multifunctional components of vascular structures, endothelial (progenitor cells have been utilized in cellular therapies and are required as an important cellular component of engineered tissue constructs and in vitro disease models. Although primary ECs from different sources are readily isolated and expanded, cell quantity and quality in terms of functionality and karyotype stability is limited. ECs derived from human induced pluripotent stem cells (hiPSCs represent an alternative and potentially superior cell source, but traditional culture approaches and 2D differentiation protocols hardly allow for production of large cell numbers. Aiming at the production of ECs, we have developed a robust approach for efficient endothelial differentiation of hiPSCs in scalable suspension culture. The established protocol results in relevant numbers of ECs for regenerative approaches and industrial applications that show in vitro proliferation capacity and a high degree of chromosomal stability. : In this article, U. Martin and colleagues show the generation of hiPSC endothelial cells in scalable cultures in up to 100 mL culture volume. The generated ECs show in vitro proliferation capacity and a high degree of chromosomal stability after in vitro expansion. The established protocol allows to generate hiPSC-derived ECs in relevant numbers for regenerative approaches. Keywords: hiPSC differentiation, endothelial cells, scalable culture

  10. Temporal Scalability of Dynamic Volume Data using Mesh Compensated Wavelet Lifting.

    Science.gov (United States)

    Schnurrer, Wolfgang; Pallast, Niklas; Richter, Thomas; Kaup, Andre

    2017-10-12

    Due to their high resolution, dynamic medical 2D+t and 3D+t volumes from computed tomography (CT) and magnetic resonance tomography (MR) reach a size which makes them very unhandy for teleradiologic applications. A lossless scalable representation offers the advantage of a down-scaled version which can be used for orientation or previewing, while the remaining information for reconstructing the full resolution is transmitted on demand. The wavelet transform offers the desired scalability. A very high quality of the lowpass sub-band is crucial in order to use it as a down-scaled representation. We propose an approach based on compensated wavelet lifting for obtaining a scalable representation of dynamic CT and MR volumes with very high quality. The mesh compensation is feasible to model the displacement in dynamic volumes which is mainly given by expansion and contraction of tissue over time. To achieve this, we propose an optimized estimation of the mesh compensation parameters to optimally fit for dynamic volumes. Within the lifting structure, the inversion of the motion compensation is crucial in the update step. We propose to take this inversion directly into account during the estimation step and can improve the quality of the lowpass sub-band by 0.63 dB and 0.43 dB on average for our tested dynamic CT and MR volumes at the cost of an increase of the rate by 2.4% and 1.2% on average.

  11. Improved work zone design guidelines and enhanced model of travel delays in work zones : Phase I, portability and scalability of interarrival and service time probability distribution functions for different locations in Ohio and the establishment of impr

    Science.gov (United States)

    2006-01-01

    The project focuses on two major issues - the improvement of current work zone design practices and an analysis of : vehicle interarrival time (IAT) and speed distributions for the development of a digital computer simulation model for : queues and t...

  12. Quality Scalability Compression on Single-Loop Solution in HEVC

    Directory of Open Access Journals (Sweden)

    Mengmeng Zhang

    2014-01-01

    Full Text Available This paper proposes a quality scalable extension design for the upcoming high efficiency video coding (HEVC standard. In the proposed design, the single-loop decoder solution is extended into the proposed scalable scenario. A novel interlayer intra/interprediction is added to reduce the amount of bits representation by exploiting the correlation between coding layers. The experimental results indicate that the average Bjøntegaard delta rate decrease of 20.50% can be gained compared with the simulcast encoding. The proposed technique achieved 47.98% Bjøntegaard delta rate reduction compared with the scalable video coding extension of the H.264/AVC. Consequently, significant rate savings confirm that the proposed method achieves better performance.

  13. Coalescent: an open-source and scalable framework for exact calculations in coalescent theory

    Science.gov (United States)

    2012-01-01

    Background Currently, there is no open-source, cross-platform and scalable framework for coalescent analysis in population genetics. There is no scalable GUI based user application either. Such a framework and application would not only drive the creation of more complex and realistic models but also make them truly accessible. Results As a first attempt, we built a framework and user application for the domain of exact calculations in coalescent analysis. The framework provides an API with the concepts of model, data, statistic, phylogeny, gene tree and recursion. Infinite-alleles and infinite-sites models are considered. It defines pluggable computations such as counting and listing all the ancestral configurations and genealogies and computing the exact probability of data. It can visualize a gene tree, trace and visualize the internals of the recursion algorithm for further improvement and attach dynamically a number of output processors. The user application defines jobs in a plug-in like manner so that they can be activated, deactivated, installed or uninstalled on demand. Multiple jobs can be run and their inputs edited. Job inputs are persisted across restarts and running jobs can be cancelled where applicable. Conclusions Coalescent theory plays an increasingly important role in analysing molecular population genetic data. Models involved are mathematically difficult and computationally challenging. An open-source, scalable framework that lets users immediately take advantage of the progress made by others will enable exploration of yet more difficult and realistic models. As models become more complex and mathematically less tractable, the need for an integrated computational approach is obvious. Object oriented designs, though has upfront costs, are practical now and can provide such an integrated approach. PMID:23033878

  14. Coalescent: an open-source and scalable framework for exact calculations in coalescent theory

    Directory of Open Access Journals (Sweden)

    Tewari Susanta

    2012-10-01

    Full Text Available Abstract Background Currently, there is no open-source, cross-platform and scalable framework for coalescent analysis in population genetics. There is no scalable GUI based user application either. Such a framework and application would not only drive the creation of more complex and realistic models but also make them truly accessible. Results As a first attempt, we built a framework and user application for the domain of exact calculations in coalescent analysis. The framework provides an API with the concepts of model, data, statistic, phylogeny, gene tree and recursion. Infinite-alleles and infinite-sites models are considered. It defines pluggable computations such as counting and listing all the ancestral configurations and genealogies and computing the exact probability of data. It can visualize a gene tree, trace and visualize the internals of the recursion algorithm for further improvement and attach dynamically a number of output processors. The user application defines jobs in a plug-in like manner so that they can be activated, deactivated, installed or uninstalled on demand. Multiple jobs can be run and their inputs edited. Job inputs are persisted across restarts and running jobs can be cancelled where applicable. Conclusions Coalescent theory plays an increasingly important role in analysing molecular population genetic data. Models involved are mathematically difficult and computationally challenging. An open-source, scalable framework that lets users immediately take advantage of the progress made by others will enable exploration of yet more difficult and realistic models. As models become more complex and mathematically less tractable, the need for an integrated computational approach is obvious. Object oriented designs, though has upfront costs, are practical now and can provide such an integrated approach.

  15. Scalable DeNoise-and-Forward in Bidirectional Relay Networks

    DEFF Research Database (Denmark)

    Sørensen, Jesper Hemming; Krigslund, Rasmus; Popovski, Petar

    2010-01-01

    In this paper a scalable relaying scheme is proposed based on an existing concept called DeNoise-and-Forward, DNF. We call it Scalable DNF, S-DNF, and it targets the scenario with multiple communication flows through a single common relay. The idea of the scheme is to combine packets at the relay...... in order to save transmissions. To ensure decodability at the end-nodes, a priori information about the content of the combined packets must be available. This is gathered during the initial transmissions to the relay. The trade-off between decodability and number of necessary transmissions is analysed...

  16. Scalability of optical networks : crosstalk limitations

    NARCIS (Netherlands)

    Tafur Monroy, I.

    2000-01-01

    Optical networks represent a promising solution for the future high capacity and flexible transport network. This paper presents a model for the performance evaluation of optical networks with respect to linear crosstalk and accumulated spontaneous emission noise. The proposed model is intended for

  17. Scalable BDDC Algorithms for Cardiac Electromechanical Coupling

    KAUST Repository

    Pavarino, L. F.; Scacchi, S.; Verdi, C.; Zampieri, E.; Zampini, Stefano

    2017-01-01

    The spread of electrical excitation in the cardiac muscle and the subsequent contraction-relaxation process is quantitatively described by the cardiac electromechanical coupling model. The electrical model consists of the Bidomain system, which is a degenerate parabolic system of two nonlinear partial differential equations (PDEs) of reaction-diffusion type, describing the evolution in space and time of the intra- and extracellular electric potentials. The PDEs are coupled through the reaction term with a stiff system of ordinary differential equations (ODEs), the membrane model, which describes the flow of the ionic currents through the cellular membrane and the dynamics of the associated gating variables. The mechanical model consists of the quasi-static finite elasticity system, modeling the cardiac tissue as a nearly-incompressible transversely isotropic hyperelastic material, and coupled with a system of ODEs accounting for the development of biochemically generated active force.

  18. Scalable BDDC Algorithms for Cardiac Electromechanical Coupling

    KAUST Repository

    Pavarino, L. F.

    2017-03-17

    The spread of electrical excitation in the cardiac muscle and the subsequent contraction-relaxation process is quantitatively described by the cardiac electromechanical coupling model. The electrical model consists of the Bidomain system, which is a degenerate parabolic system of two nonlinear partial differential equations (PDEs) of reaction-diffusion type, describing the evolution in space and time of the intra- and extracellular electric potentials. The PDEs are coupled through the reaction term with a stiff system of ordinary differential equations (ODEs), the membrane model, which describes the flow of the ionic currents through the cellular membrane and the dynamics of the associated gating variables. The mechanical model consists of the quasi-static finite elasticity system, modeling the cardiac tissue as a nearly-incompressible transversely isotropic hyperelastic material, and coupled with a system of ODEs accounting for the development of biochemically generated active force.

  19. Recurrent, Robust and Scalable Patterns Underlie Human Approach and Avoidance

    Science.gov (United States)

    Kennedy, David N.; Lehár, Joseph; Lee, Myung Joo; Blood, Anne J.; Lee, Sang; Perlis, Roy H.; Smoller, Jordan W.; Morris, Robert; Fava, Maurizio

    2010-01-01

    Background Approach and avoidance behavior provide a means for assessing the rewarding or aversive value of stimuli, and can be quantified by a keypress procedure whereby subjects work to increase (approach), decrease (avoid), or do nothing about time of exposure to a rewarding/aversive stimulus. To investigate whether approach/avoidance behavior might be governed by quantitative principles that meet engineering criteria for lawfulness and that encode known features of reward/aversion function, we evaluated whether keypress responses toward pictures with potential motivational value produced any regular patterns, such as a trade-off between approach and avoidance, or recurrent lawful patterns as observed with prospect theory. Methodology/Principal Findings Three sets of experiments employed this task with beautiful face images, a standardized set of affective photographs, and pictures of food during controlled states of hunger and satiety. An iterative modeling approach to data identified multiple law-like patterns, based on variables grounded in the individual. These patterns were consistent across stimulus types, robust to noise, describable by a simple power law, and scalable between individuals and groups. Patterns included: (i) a preference trade-off counterbalancing approach and avoidance, (ii) a value function linking preference intensity to uncertainty about preference, and (iii) a saturation function linking preference intensity to its standard deviation, thereby setting limits to both. Conclusions/Significance These law-like patterns were compatible with critical features of prospect theory, the matching law, and alliesthesia. Furthermore, they appeared consistent with both mean-variance and expected utility approaches to the assessment of risk. Ordering of responses across categories of stimuli demonstrated three properties thought to be relevant for preference-based choice, suggesting these patterns might be grouped together as a relative preference

  20. Recurrent, robust and scalable patterns underlie human approach and avoidance.

    Directory of Open Access Journals (Sweden)

    Byoung Woo Kim

    2010-05-01

    Full Text Available Approach and avoidance behavior provide a means for assessing the rewarding or aversive value of stimuli, and can be quantified by a keypress procedure whereby subjects work to increase (approach, decrease (avoid, or do nothing about time of exposure to a rewarding/aversive stimulus. To investigate whether approach/avoidance behavior might be governed by quantitative principles that meet engineering criteria for lawfulness and that encode known features of reward/aversion function, we evaluated whether keypress responses toward pictures with potential motivational value produced any regular patterns, such as a trade-off between approach and avoidance, or recurrent lawful patterns as observed with prospect theory.Three sets of experiments employed this task with beautiful face images, a standardized set of affective photographs, and pictures of food during controlled states of hunger and satiety. An iterative modeling approach to data identified multiple law-like patterns, based on variables grounded in the individual. These patterns were consistent across stimulus types, robust to noise, describable by a simple power law, and scalable between individuals and groups. Patterns included: (i a preference trade-off counterbalancing approach and avoidance, (ii a value function linking preference intensity to uncertainty about preference, and (iii a saturation function linking preference intensity to its standard deviation, thereby setting limits to both.These law-like patterns were compatible with critical features of prospect theory, the matching law, and alliesthesia. Furthermore, they appeared consistent with both mean-variance and expected utility approaches to the assessment of risk. Ordering of responses across categories of stimuli demonstrated three properties thought to be relevant for preference-based choice, suggesting these patterns might be grouped together as a relative preference theory. Since variables in these patterns have been

  1. Using Python to Construct a Scalable Parallel Nonlinear Wave Solver

    KAUST Repository

    Mandli, Kyle

    2011-01-01

    Computational scientists seek to provide efficient, easy-to-use tools and frameworks that enable application scientists within a specific discipline to build and/or apply numerical models with up-to-date computing technologies that can be executed on all available computing systems. Although many tools could be useful for groups beyond a specific application, it is often difficult and time consuming to combine existing software, or to adapt it for a more general purpose. Python enables a high-level approach where a general framework can be supplemented with tools written for different fields and in different languages. This is particularly important when a large number of tools are necessary, as is the case for high performance scientific codes. This motivated our development of PetClaw, a scalable distributed-memory solver for time-dependent nonlinear wave propagation, as a case-study for how Python can be used as a highlevel framework leveraging a multitude of codes, efficient both in the reuse of code and programmer productivity. We present scaling results for computations on up to four racks of Shaheen, an IBM BlueGene/P supercomputer at King Abdullah University of Science and Technology. One particularly important issue that PetClaw has faced is the overhead associated with dynamic loading leading to catastrophic scaling. We use the walla library to solve the issue which does so by supplanting high-cost filesystem calls with MPI operations at a low enough level that developers may avoid any changes to their codes.

  2. Design for scalability in 3D computer graphics architectures

    DEFF Research Database (Denmark)

    Holten-Lund, Hans Erik

    2002-01-01

    This thesis describes useful methods and techniques for designing scalable hybrid parallel rendering architectures for 3D computer graphics. Various techniques for utilizing parallelism in a pipelines system are analyzed. During the Ph.D study a prototype 3D graphics architecture named Hybris has...

  3. Scalable storage for a DBMS using transparent distribution

    NARCIS (Netherlands)

    J.S. Karlsson; M.L. Kersten (Martin)

    1997-01-01

    textabstractScalable Distributed Data Structures (SDDSs) provide a self-managing and self-organizing data storage of potentially unbounded size. This stands in contrast to common distribution schemas deployed in conventional distributed DBMS. SDDSs, however, have mostly been used in synthetic

  4. Scalable force directed graph layout algorithms using fast multipole methods

    KAUST Repository

    Yunis, Enas Abdulrahman; Yokota, Rio; Ahmadia, Aron

    2012-01-01

    We present an extension to ExaFMM, a Fast Multipole Method library, as a generalized approach for fast and scalable execution of the Force-Directed Graph Layout algorithm. The Force-Directed Graph Layout algorithm is a physics-based approach

  5. Cascaded column generation for scalable predictive demand side management

    NARCIS (Netherlands)

    Toersche, Hermen; Molderink, Albert; Hurink, Johann L.; Smit, Gerardus Johannes Maria

    2014-01-01

    We propose a nested Dantzig-Wolfe decomposition, combined with dynamic programming, for the distributed scheduling of a large heterogeneous fleet of residential appliances with nonlinear behavior. A cascaded column generation approach gives a scalable optimization strategy, provided that the problem

  6. Efficient Enhancement for Spatial Scalable Video Coding Transmission

    Directory of Open Access Journals (Sweden)

    Mayada Khairy

    2017-01-01

    Full Text Available Scalable Video Coding (SVC is an international standard technique for video compression. It is an extension of H.264 Advanced Video Coding (AVC. In the encoding of video streams by SVC, it is suitable to employ the macroblock (MB mode because it affords superior coding efficiency. However, the exhaustive mode decision technique that is usually used for SVC increases the computational complexity, resulting in a longer encoding time (ET. Many other algorithms were proposed to solve this problem with imperfection of increasing transmission time (TT across the network. To minimize the ET and TT, this paper introduces four efficient algorithms based on spatial scalability. The algorithms utilize the mode-distribution correlation between the base layer (BL and enhancement layers (ELs and interpolation between the EL frames. The proposed algorithms are of two categories. Those of the first category are based on interlayer residual SVC spatial scalability. They employ two methods, namely, interlayer interpolation (ILIP and the interlayer base mode (ILBM method, and enable ET and TT savings of up to 69.3% and 83.6%, respectively. The algorithms of the second category are based on full-search SVC spatial scalability. They utilize two methods, namely, full interpolation (FIP and the full-base mode (FBM method, and enable ET and TT savings of up to 55.3% and 76.6%, respectively.

  7. Scalable Robust Principal Component Analysis Using Grassmann Averages

    DEFF Research Database (Denmark)

    Hauberg, Søren; Feragen, Aasa; Enficiaud, Raffi

    2016-01-01

    In large datasets, manual data verification is impossible, and we must expect the number of outliers to increase with data size. While principal component analysis (PCA) can reduce data size, and scalable solutions exist, it is well-known that outliers can arbitrarily corrupt the results. Unfortu...

  8. A Scalable Smart Meter Data Generator Using Spark

    DEFF Research Database (Denmark)

    Iftikhar, Nadeem; Liu, Xiufeng; Danalachi, Sergiu

    2017-01-01

    Today, smart meters are being used worldwide. As a matter of fact smart meters produce large volumes of data. Thus, it is important for smart meter data management and analytics systems to process petabytes of data. Benchmarking and testing of these systems require scalable data, however, it can ...

  9. Scalable electro-photonic integration concept based on polymer waveguides

    NARCIS (Netherlands)

    Bosman, E.; Steenberge, G. van; Boersma, A.; Wiegersma, S.; Harmsma, P.J.; Karppinen, M.; Korhonen, T.; Offrein, B.J.; Dangel, R.; Daly, A.; Ortsiefer, M.; Justice, J.; Corbett, B.; Dorrestein, S.; Duis, J.

    2016-01-01

    A novel method for fabricating a single mode optical interconnection platform is presented. The method comprises the miniaturized assembly of optoelectronic single dies, the scalable fabrication of polymer single mode waveguides and the coupling to glass fiber arrays providing the I/O's. The low

  10. Adolescent sexuality education: An appraisal of some scalable ...

    African Journals Online (AJOL)

    Adolescent sexuality education: An appraisal of some scalable interventions for the Nigerian context. VC Pam. Abstract. Most issues around sexual intercourse are highly sensitive topics in Nigeria. Despite the disturbingly high adolescent HIV prevalence and teenage pregnancy rate in Nigeria, sexuality education is ...

  11. Scalable multifunction RF system concepts for joint operations

    NARCIS (Netherlands)

    Otten, M.P.G.; Wit, J.J.M. de; Smits, F.M.A.; Rossum, W.L. van; Huizing, A.

    2010-01-01

    RF systems based on modular architectures have the potential of better re-use of technology, decreasing development time, and decreasing life cycle cost. Moreover, modular architectures provide scalability, allowing low cost upgrades and adaptability to different platforms. To achieve maximum

  12. Estimates of the Sampling Distribution of Scalability Coefficient H

    Science.gov (United States)

    Van Onna, Marieke J. H.

    2004-01-01

    Coefficient "H" is used as an index of scalability in nonparametric item response theory (NIRT). It indicates the degree to which a set of items rank orders examinees. Theoretical sampling distributions, however, have only been derived asymptotically and only under restrictive conditions. Bootstrap methods offer an alternative possibility to…

  13. DySectAPI: Scalable Prescriptive Debugging

    DEFF Research Database (Denmark)

    Jensen, Nicklas Bo; Karlsson, Sven; Quarfot Nielsen, Niklas

    We present the DySectAPI, a tool that allow users to construct probe trees for automatic, event-driven debugging at scale. The traditional, interactive debugging model, whereby users manually step through and inspect their application, does not scale well even for current supercomputers. While...... lightweight debugging models scale well, they can currently only debug a subset of bug classes. DySectAPI fills the gap between these two approaches with a novel user-guided approach. Using both experimental results and analytical modeling we show how DySectAPI scales and can run with a low overhead...

  14. An integrated tiered service delivery model (ITSDM based on local CD4 testing demands can improve turn-around times and save costs whilst ensuring accessible and scalable CD4 services across a national programme.

    Directory of Open Access Journals (Sweden)

    Deborah K Glencross

    Full Text Available The South African National Health Laboratory Service (NHLS responded to HIV treatment initiatives with two-tiered CD4 laboratory services in 2004. Increasing programmatic burden, as more patients access anti-retroviral therapy (ART, has demanded extending CD4 services to meet increasing clinical needs. The aim of this study was to review existing services and develop a service-model that integrated laboratory-based and point-of-care testing (POCT, to extend national coverage, improve local turn-around/(TAT and contain programmatic costs.NHLS Corporate Data Warehouse CD4 data, from 60-70 laboratories and 4756 referring health facilities was reviewed for referral laboratory workload, respective referring facility volumes and related TAT, from 2009-2012.An integrated tiered service delivery model (ITSDM is proposed. Tier-1/POCT delivers CD4 testing at single health-clinics providing ART in hard-to-reach areas (350-1500 tests/day, serving ≥ 200 health-clinics. Tier-6 provides national support for standardisation, harmonization and quality across the organization.The ITSDM offers improved local TAT by extending CD4 services into rural/remote areas with new Tier-3 or Tier-2/POC-Hub services installed in existing community laboratories, most with developed infrastructure. The advantage of lower laboratory CD4 costs and use of existing infrastructure enables subsidization of delivery of more expensive POC services, into hard-to-reach districts without reasonable access to a local CD4 laboratory. Full ITSDM implementation across 5 service tiers (as opposed to widespread implementation of POC testing to extend service can facilitate sustainable 'full service coverage' across South Africa, and save>than R125 million in HIV/AIDS programmatic costs. ITSDM hierarchical parental-support also assures laboratory/POC management, equipment maintenance, quality control and on-going training between tiers.

  15. Scalable Learning for Geostatistics and Speaker Recognition

    Science.gov (United States)

    2011-01-01

    Device Architecture (CUDA)[63], a parallel programming model that leverages the parallel compute engine in NVIDIA GPUs to solve general purpose...validation. 3.1 Geospatial data reconstruction Sensors deployed on satellites are often used to collect enviromental data where a direct measurement is...same decision as training a model on B and testing on A, which is desirable in many recognition engines . We shall address this in the next chapter. The

  16. Evaluation of 3D printed anatomically scalable transfemoral prosthetic knee.

    Science.gov (United States)

    Ramakrishnan, Tyagi; Schlafly, Millicent; Reed, Kyle B

    2017-07-01

    This case study compares a transfemoral amputee's gait while using the existing Ossur Total Knee 2000 and our novel 3D printed anatomically scalable transfemoral prosthetic knee. The anatomically scalable transfemoral prosthetic knee is 3D printed out of a carbon-fiber and nylon composite that has a gear-mesh coupling with a hard-stop weight-actuated locking mechanism aided by a cross-linked four-bar spring mechanism. This design can be scaled using anatomical dimensions of a human femur and tibia to have a unique fit for each user. The transfemoral amputee who was tested is high functioning and walked on the Computer Assisted Rehabilitation Environment (CAREN) at a self-selected pace. The motion capture and force data that was collected showed that there were distinct differences in the gait dynamics. The data was used to perform the Combined Gait Asymmetry Metric (CGAM), where the scores revealed that the overall asymmetry of the gait on the Ossur Total Knee was more asymmetric than the anatomically scalable transfemoral prosthetic knee. The anatomically scalable transfemoral prosthetic knee had higher peak knee flexion that caused a large step time asymmetry. This made walking on the anatomically scalable transfemoral prosthetic knee more strenuous due to the compensatory movements in adapting to the different dynamics. This can be overcome by tuning the cross-linked spring mechanism to emulate the dynamics of the subject better. The subject stated that the knee would be good for daily use and has the potential to be adapted as a running knee.

  17. Blind Cooperative Routing for Scalable and Energy-Efficient Internet of Things

    KAUST Repository

    Bader, Ahmed; Alouini, Mohamed-Slim

    2016-01-01

    Multihop networking is promoted in this paper for energy-efficient and highly-scalable Internet of Things (IoT). Recognizing concerns related to the scalability of classical multihop routing and medium access techniques, the use of blind cooperation

  18. Generic algorithms for high performance scalable geocomputing

    Science.gov (United States)

    de Jong, Kor; Schmitz, Oliver; Karssenberg, Derek

    2016-04-01

    During the last decade, the characteristics of computing hardware have changed a lot. For example, instead of a single general purpose CPU core, personal computers nowadays contain multiple cores per CPU and often general purpose accelerators, like GPUs. Additionally, compute nodes are often grouped together to form clusters or a supercomputer, providing enormous amounts of compute power. For existing earth simulation models to be able to use modern hardware platforms, their compute intensive parts must be rewritten. This can be a major undertaking and may involve many technical challenges. Compute tasks must be distributed over CPU cores, offloaded to hardware accelerators, or distributed to different compute nodes. And ideally, all of this should be done in such a way that the compute task scales well with the hardware resources. This presents two challenges: 1) how to make good use of all the compute resources and 2) how to make these compute resources available for developers of simulation models, who may not (want to) have the required technical background for distributing compute tasks. The first challenge requires the use of specialized technology (e.g.: threads, OpenMP, MPI, OpenCL, CUDA). The second challenge requires the abstraction of the logic handling the distribution of compute tasks from the model-specific logic, hiding the technical details from the model developer. To assist the model developer, we are developing a C++ software library (called Fern) containing algorithms that can use all CPU cores available in a single compute node (distributing tasks over multiple compute nodes will be done at a later stage). The algorithms are grid-based (finite difference) and include local and spatial operations such as convolution filters. The algorithms handle distribution of the compute tasks to CPU cores internally. In the resulting model the low-level details of how this is done is separated from the model-specific logic representing the modeled system

  19. Scalable Adaptive Multilevel Solvers for Multiphysics Problems

    Energy Technology Data Exchange (ETDEWEB)

    Xu, Jinchao [Pennsylvania State Univ., University Park, PA (United States). Dept. of Mathematics

    2014-11-26

    In this project, we carried out many studies on adaptive and parallel multilevel methods for numerical modeling for various applications, including Magnetohydrodynamics (MHD) and complex fluids. We have made significant efforts and advances in adaptive multilevel methods of the multiphysics problems: multigrid methods, adaptive finite element methods, and applications.

  20. Scalable printed electronics: an organic decoder addressing ferroelectric non-volatile memory

    Science.gov (United States)

    Ng, Tse Nga; Schwartz, David E.; Lavery, Leah L.; Whiting, Gregory L.; Russo, Beverly; Krusor, Brent; Veres, Janos; Bröms, Per; Herlogsson, Lars; Alam, Naveed; Hagel, Olle; Nilsson, Jakob; Karlsson, Christer

    2012-01-01

    Scalable circuits of organic logic and memory are realized using all-additive printing processes. A 3-bit organic complementary decoder is fabricated and used to read and write non-volatile, rewritable ferroelectric memory. The decoder-memory array is patterned by inkjet and gravure printing on flexible plastics. Simulation models for the organic transistors are developed, enabling circuit designs tolerant of the variations in printed devices. We explain the key design rules in fabrication of complex printed circuits and elucidate the performance requirements of materials and devices for reliable organic digital logic. PMID:22900143

  1. Scalability analysis of large-scale LoRaWAN networks in ns-3

    OpenAIRE

    Abeele, Floris Van den; Haxhibeqiri, Jetmir; Moerman, Ingrid; Hoebeke, Jeroen

    2017-01-01

    As LoRaWAN networks are actively being deployed in the field, it is important to comprehend the limitations of this Low Power Wide Area Network technology. Previous work has raised questions in terms of the scalability and capacity of LoRaWAN networks as the number of end devices grows to hundreds or thousands per gateway. Some works have modeled LoRaWAN networks as pure ALOHA networks, which fails to capture important characteristics such as the capture effect and the effects of interference...

  2. Performance and scalability analysis of teraflop-scale parallel architectures using multidimensional wavefront applications

    International Nuclear Information System (INIS)

    Hoisie, A.; Lubeck, O.; Wasserman, H.

    1998-01-01

    The authors develop a model for the parallel performance of algorithms that consist of concurrent, two-dimensional wavefronts implemented in a message passing environment. The model, based on a LogGP machine parameterization, combines the separate contributions of computation and communication wavefronts. They validate the model on three important supercomputer systems, on up to 500 processors. They use data from a deterministic particle transport application taken from the ASCI workload, although the model is general to any wavefront algorithm implemented on a 2-D processor domain. They also use the validated model to make estimates of performance and scalability of wavefront algorithms on 100-TFLOPS computer systems expected to be in existence within the next decade as part of the ASCI program and elsewhere. In this context, they analyze two problem sizes. The model shows that on the largest such problem (1 billion cells), inter-processor communication performance is not the bottleneck. Single-node efficiency is the dominant factor

  3. Temporal scalability comparison of the H.264/SVC and distributed video codec

    DEFF Research Database (Denmark)

    Huang, Xin; Ukhanova, Ann; Belyaev, Evgeny

    2009-01-01

    The problem of the multimedia scalable video streaming is a current topic of interest. There exist many methods for scalable video coding. This paper is focused on the scalable extension of H.264/AVC (H.264/SVC) and distributed video coding (DVC). The paper presents an efficiency comparison of SV...

  4. Scalable Track Detection in SAR CCD Images

    Energy Technology Data Exchange (ETDEWEB)

    Chow, James G [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Quach, Tu-Thach [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-03-01

    Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images ta ken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are often too simple to capture natural track features such as continuity and parallelism. We present a simple convolutional network architecture consisting of a series of 3-by-3 convolutions to detect tracks. The network is trained end-to-end to learn natural track features entirely from data. The network is computationally efficient and improves the F-score on a standard dataset to 0.988, up fr om 0.907 obtained by the current state-of-the-art method.

  5. Heterogeneous scalable framework for multiphase flows

    Energy Technology Data Exchange (ETDEWEB)

    Morris, Karla Vanessa [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2013-09-01

    Two categories of challenges confront the developer of computational spray models: those related to the computation and those related to the physics. Regarding the computation, the trend towards heterogeneous, multi- and many-core platforms will require considerable re-engineering of codes written for the current supercomputing platforms. Regarding the physics, accurate methods for transferring mass, momentum and energy from the dispersed phase onto the carrier fluid grid have so far eluded modelers. Significant challenges also lie at the intersection between these two categories. To be competitive, any physics model must be expressible in a parallel algorithm that performs well on evolving computer platforms. This work created an application based on a software architecture where the physics and software concerns are separated in a way that adds flexibility to both. The develop spray-tracking package includes an application programming interface (API) that abstracts away the platform-dependent parallelization concerns, enabling the scientific programmer to write serial code that the API resolves into parallel processes and threads of execution. The project also developed the infrastructure required to provide similar APIs to other application. The API allow object-oriented Fortran applications direct interaction with Trilinos to support memory management of distributed objects in central processing units (CPU) and graphic processing units (GPU) nodes for applications using C++.

  6. Scalable and Resilient Middleware to Handle Information Exchange during Environment Crisis

    Science.gov (United States)

    Tao, R.; Poslad, S.; Moßgraber, J.; Middleton, S.; Hammitzsch, M.

    2012-04-01

    The EU FP7 TRIDEC project focuses on enabling real-time, intelligent, information management of collaborative, complex, critical decision processes for earth management. A key challenge is to promote a communication infrastructure to facilitate interoperable environment information services during environment events and crises such as tsunamis and drilling, during which increasing volumes and dimensionality of disparate information sources, including sensor-based and human-based ones, can result, and need to be managed. Such a system needs to support: scalable, distributed messaging; asynchronous messaging; open messaging to handling changing clients such as new and retired automated system and human information sources becoming online or offline; flexible data filtering, and heterogeneous access networks (e.g., GSM, WLAN and LAN). In addition, the system needs to be resilient to handle the ICT system failures, e.g. failure, degradation and overloads, during environment events. There are several system middleware choices for TRIDEC based upon a Service-oriented-architecture (SOA), Event-driven-Architecture (EDA), Cloud Computing, and Enterprise Service Bus (ESB). In an SOA, everything is a service (e.g. data access, processing and exchange); clients can request on demand or subscribe to services registered by providers; more often interaction is synchronous. In an EDA system, events that represent significant changes in state can be processed simply, or as streams or more complexly. Cloud computing is a virtualization, interoperable and elastic resource allocation model. An ESB, a fundamental component for enterprise messaging, supports synchronous and asynchronous message exchange models and has inbuilt resilience against ICT failure. Our middleware proposal is an ESB based hybrid architecture model: an SOA extension supports more synchronous workflows; EDA assists the ESB to handle more complex event processing; Cloud computing can be used to increase and

  7. Oceanotron, Scalable Server for Marine Observations

    Science.gov (United States)

    Loubrieu, T.; Bregent, S.; Blower, J. D.; Griffiths, G.

    2013-12-01

    Ifremer, French marine institute, is deeply involved in data management for different ocean in-situ observation programs (ARGO, OceanSites, GOSUD, ...) or other European programs aiming at networking ocean in-situ observation data repositories (myOcean, seaDataNet, Emodnet). To capitalize the effort for implementing advance data dissemination services (visualization, download with subsetting) for these programs and generally speaking water-column observations repositories, Ifremer decided to develop the oceanotron server (2010). Knowing the diversity of data repository formats (RDBMS, netCDF, ODV, ...) and the temperamental nature of the standard interoperability interface profiles (OGC/WMS, OGC/WFS, OGC/SOS, OpeNDAP, ...), the server is designed to manage plugins: - StorageUnits : which enable to read specific data repository formats (netCDF/OceanSites, RDBMS schema, ODV binary format). - FrontDesks : which get external requests and send results for interoperable protocols (OGC/WMS, OGC/SOS, OpenDAP). In between a third type of plugin may be inserted: - TransformationUnits : which enable ocean business related transformation of the features (for example conversion of vertical coordinates from pressure in dB to meters under sea surface). The server is released under open-source license so that partners can develop their own plugins. Within MyOcean project, University of Reading has plugged a WMS implementation as an oceanotron frontdesk. The modules are connected together by sharing the same information model for marine observations (or sampling features: vertical profiles, point series and trajectories), dataset metadata and queries. The shared information model is based on OGC/Observation & Measurement and Unidata/Common Data Model initiatives. The model is implemented in java (http://www.ifremer.fr/isi/oceanotron/javadoc/). This inner-interoperability level enables to capitalize ocean business expertise in software development without being indentured to

  8. Large scalable workshop for innovation and entrepreneurship

    DEFF Research Database (Denmark)

    Tollestrup, Christian

    2011-01-01

    and other technical disciplines. The project is a strategic initiative with the aim of strengthening the university students’ ability to develop new products and business models in relation to societal and environmental needs and challenges. The paper describes tools and methods to handle such projects......This paper describes several years of experience in planning and implementing an interdisciplinary Workshop For Innovation and Entrepreneurship (WOFIE) where design students develop new solutions and business plans in collaboration with graduate students from social sciences, human sciences...... has been done under the following dogmas: 1) Asynchronous process between the groups, 2) A qualified progress outlined for supervisors and Location Leaders. The author of this paper has been part of a development group restructuring the approach into to an activity-based matrix combining a sequential...

  9. Decentralized Control for Scalable Quadcopter Formations

    Directory of Open Access Journals (Sweden)

    Qasim Ali

    2016-01-01

    Full Text Available An innovative framework has been developed for teamwork of two quadcopter formations, each having its specified formation geometry, assigned task, and matching control scheme. Position control for quadcopters in one of the formations has been implemented through a Linear Quadratic Regulator Proportional Integral (LQR PI control scheme based on explicit model following scheme. Quadcopters in the other formation are controlled through LQR PI servomechanism control scheme. These two control schemes are compared in terms of their performance and control effort. Both formations are commanded by respective ground stations through virtual leaders. Quadcopters in formations are able to track desired trajectories as well as hovering at desired points for selected time duration. In case of communication loss between ground station and any of the quadcopters, the neighboring quadcopter provides the command data, received from the ground station, to the affected unit. Proposed control schemes have been validated through extensive simulations using MATLAB®/Simulink® that provided favorable results.

  10. Scientific visualization uncertainty, multifield, biomedical, and scalable visualization

    CERN Document Server

    Chen, Min; Johnson, Christopher; Kaufman, Arie; Hagen, Hans

    2014-01-01

    Based on the seminar that took place in Dagstuhl, Germany in June 2011, this contributed volume studies the four important topics within the scientific visualization field: uncertainty visualization, multifield visualization, biomedical visualization and scalable visualization. • Uncertainty visualization deals with uncertain data from simulations or sampled data, uncertainty due to the mathematical processes operating on the data, and uncertainty in the visual representation, • Multifield visualization addresses the need to depict multiple data at individual locations and the combination of multiple datasets, • Biomedical is a vast field with select subtopics addressed from scanning methodologies to structural applications to biological applications, • Scalability in scientific visualization is critical as data grows and computational devices range from hand-held mobile devices to exascale computational platforms. Scientific Visualization will be useful to practitioners of scientific visualization, ...

  11. Scalable quantum memory in the ultrastrong coupling regime.

    Science.gov (United States)

    Kyaw, T H; Felicetti, S; Romero, G; Solano, E; Kwek, L-C

    2015-03-02

    Circuit quantum electrodynamics, consisting of superconducting artificial atoms coupled to on-chip resonators, represents a prime candidate to implement the scalable quantum computing architecture because of the presence of good tunability and controllability. Furthermore, recent advances have pushed the technology towards the ultrastrong coupling regime of light-matter interaction, where the qubit-resonator coupling strength reaches a considerable fraction of the resonator frequency. Here, we propose a qubit-resonator system operating in that regime, as a quantum memory device and study the storage and retrieval of quantum information in and from the Z2 parity-protected quantum memory, within experimentally feasible schemes. We are also convinced that our proposal might pave a way to realize a scalable quantum random-access memory due to its fast storage and readout performances.

  12. Fast & scalable pattern transfer via block copolymer nanolithography

    DEFF Research Database (Denmark)

    Li, Tao; Wang, Zhongli; Schulte, Lars

    2015-01-01

    A fully scalable and efficient pattern transfer process based on block copolymer (BCP) self-assembling directly on various substrates is demonstrated. PS-rich and PDMS-rich poly(styrene-b-dimethylsiloxane) (PS-b-PDMS) copolymers are used to give monolayer sphere morphology after spin-casting of s......A fully scalable and efficient pattern transfer process based on block copolymer (BCP) self-assembling directly on various substrates is demonstrated. PS-rich and PDMS-rich poly(styrene-b-dimethylsiloxane) (PS-b-PDMS) copolymers are used to give monolayer sphere morphology after spin...... on long range lateral order, including fabrication of substrates for catalysis, solar cells, sensors, ultrafiltration membranes and templating of semiconductors or metals....

  13. Scalability of DL_POLY on High Performance Computing Platform

    Directory of Open Access Journals (Sweden)

    Mabule Samuel Mabakane

    2017-12-01

    Full Text Available This paper presents a case study on the scalability of several versions of the molecular dynamics code (DL_POLY performed on South Africa‘s Centre for High Performance Computing e1350 IBM Linux cluster, Sun system and Lengau supercomputers. Within this study different problem sizes were designed and the same chosen systems were employed in order to test the performance of DL_POLY using weak and strong scalability. It was found that the speed-up results for the small systems were better than large systems on both Ethernet and Infiniband network. However, simulations of large systems in DL_POLY performed well using Infiniband network on Lengau cluster as compared to e1350 and Sun supercomputer.

  14. On the Scalability of Time-predictable Chip-Multiprocessing

    DEFF Research Database (Denmark)

    Puffitsch, Wolfgang; Schoeberl, Martin

    2012-01-01

    Real-time systems need a time-predictable execution platform to be able to determine the worst-case execution time statically. In order to be time-predictable, several advanced processor features, such as out-of-order execution and other forms of speculation, have to be avoided. However, just using...... simple processors is not an option for embedded systems with high demands on computing power. In order to provide high performance and predictability we argue to use multiprocessor systems with a time-predictable memory interface. In this paper we present the scalability of a Java chip......-multiprocessor system that is designed to be time-predictable. Adding time-predictable caches is mandatory to achieve scalability with a shared memory multi-processor system. As Java bytecode retains information about the nature of memory accesses, it is possible to implement a memory hierarchy that takes...

  15. ATLAS Grid Data Processing: system evolution and scalability

    CERN Document Server

    Golubkov, D; The ATLAS collaboration; Klimentov, A; Minaenko, A; Nevski, P; Vaniachine, A; Walker, R

    2012-01-01

    The production system for Grid Data Processing handles petascale ATLAS data reprocessing and Monte Carlo activities. The production system empowered further data processing steps on the Grid performed by dozens of ATLAS physics groups with coordinated access to computing resources worldwide, including additional resources sponsored by regional facilities. The system provides knowledge management of configuration parameters for massive data processing tasks, reproducibility of results, scalable database access, orchestrated workflow and performance monitoring, dynamic workload sharing, automated fault tolerance and petascale data integrity control. The system evolves to accommodate a growing number of users and new requirements from our contacts in ATLAS main areas: Trigger, Physics, Data Preparation and Software & Computing. To assure scalability, the next generation production system architecture development is in progress. We report on scaling up the production system for a growing number of users provi...

  16. Proof of Stake Blockchain: Performance and Scalability for Groupware Communications

    DEFF Research Database (Denmark)

    Spasovski, Jason; Eklund, Peter

    2017-01-01

    A blockchain is a distributed transaction ledger, a disruptive technology that creates new possibilities for digital ecosystems. The blockchain ecosystem maintains an immutable transaction record to support many types of digital services. This paper compares the performance and scalability of a web......-based groupware communication application using both non-blockchain and blockchain technologies. Scalability is measured where message load is synthesized over two typical communication topologies. The first is 1 to n network -- a typical client-server or star-topology with a central vertex (server) receiving all...... messages from the remaining n - 1 vertices (clients). The second is a more naturally occurring scale-free network topology, where multiple communication hubs are distributed throughout the network. System performance is tested with both blockchain and non-blockchain solutions using multiple cloud computing...

  17. Continuity-Aware Scheduling Algorithm for Scalable Video Streaming

    Directory of Open Access Journals (Sweden)

    Atinat Palawan

    2016-05-01

    Full Text Available The consumer demand for retrieving and delivering visual content through consumer electronic devices has increased rapidly in recent years. The quality of video in packet networks is susceptible to certain traffic characteristics: average bandwidth availability, loss, delay and delay variation (jitter. This paper presents a scheduling algorithm that modifies the stream of scalable video to combat jitter. The algorithm provides unequal look-ahead by safeguarding the base layer (without the need for overhead of the scalable video. The results of the experiments show that our scheduling algorithm reduces the number of frames with a violated deadline and significantly improves the continuity of the video stream without compromising the average Y Peek Signal-to-Noise Ratio (PSNR.

  18. Scalable, full-colour and controllable chromotropic plasmonic printing

    Science.gov (United States)

    Xue, Jiancai; Zhou, Zhang-Kai; Wei, Zhiqiang; Su, Rongbin; Lai, Juan; Li, Juntao; Li, Chao; Zhang, Tengwei; Wang, Xue-Hua

    2015-01-01

    Plasmonic colour printing has drawn wide attention as a promising candidate for the next-generation colour-printing technology. However, an efficient approach to realize full colour and scalable fabrication is still lacking, which prevents plasmonic colour printing from practical applications. Here we present a scalable and full-colour plasmonic printing approach by combining conjugate twin-phase modulation with a plasmonic broadband absorber. More importantly, our approach also demonstrates controllable chromotropic capability, that is, the ability of reversible colour transformations. This chromotropic capability affords enormous potentials in building functionalized prints for anticounterfeiting, special label, and high-density data encryption storage. With such excellent performances in functional colour applications, this colour-printing approach could pave the way for plasmonic colour printing in real-world commercial utilization. PMID:26567803

  19. A Scalable Communication Architecture for Advanced Metering Infrastructure

    OpenAIRE

    Ngo Hoang , Giang; Liquori , Luigi; Nguyen Chan , Hung

    2013-01-01

    Advanced Metering Infrastructure (AMI), seen as foundation for overall grid modernization, is an integration of many technologies that provides an intelligent connection between consumers and system operators [ami 2008]. One of the biggest challenge that AMI faces is to scalable collect and manage a huge amount of data from a large number of customers. In our paper, we address this challenge by introducing a mixed peer-to-peer (P2P) and client-server communication architecture for AMI in whic...

  20. Scalable Multi-group Key Management for Advanced Metering Infrastructure

    OpenAIRE

    Benmalek , Mourad; Challal , Yacine; Bouabdallah , Abdelmadjid

    2015-01-01

    International audience; Advanced Metering Infrastructure (AMI) is composed of systems and networks to incorporate changes for modernizing the electricity grid, reduce peak loads, and meet energy efficiency targets. AMI is a privileged target for security attacks with potentially great damage against infrastructures and privacy. For this reason, Key Management has been identified as one of the most challenging topics in AMI development. In this paper, we propose a new Scalable multi-group key ...

  1. Economical and scalable synthesis of 6-amino-2-cyanobenzothiazole

    Directory of Open Access Journals (Sweden)

    Jacob R. Hauser

    2016-09-01

    Full Text Available 2-Cyanobenzothiazoles (CBTs are useful building blocks for: 1 luciferin derivatives for bioluminescent imaging; and 2 handles for bioorthogonal ligations. A particularly versatile CBT is 6-amino-2-cyanobenzothiazole (ACBT, which has an amine handle for straight-forward derivatisation. Here we present an economical and scalable synthesis of ACBT based on a cyanation catalysed by 1,4-diazabicyclo[2.2.2]octane (DABCO, and discuss its advantages for scale-up over previously reported routes.

  2. Space Situational Awareness Data Processing Scalability Utilizing Google Cloud Services

    Science.gov (United States)

    Greenly, D.; Duncan, M.; Wysack, J.; Flores, F.

    Space Situational Awareness (SSA) is a fundamental and critical component of current space operations. The term SSA encompasses the awareness, understanding and predictability of all objects in space. As the population of orbital space objects and debris increases, the number of collision avoidance maneuvers grows and prompts the need for accurate and timely process measures. The SSA mission continually evolves to near real-time assessment and analysis demanding the need for higher processing capabilities. By conventional methods, meeting these demands requires the integration of new hardware to keep pace with the growing complexity of maneuver planning algorithms. SpaceNav has implemented a highly scalable architecture that will track satellites and debris by utilizing powerful virtual machines on the Google Cloud Platform. SpaceNav algorithms for processing CDMs outpace conventional means. A robust processing environment for tracking data, collision avoidance maneuvers and various other aspects of SSA can be created and deleted on demand. Migrating SpaceNav tools and algorithms into the Google Cloud Platform will be discussed and the trials and tribulations involved. Information will be shared on how and why certain cloud products were used as well as integration techniques that were implemented. Key items to be presented are: 1.Scientific algorithms and SpaceNav tools integrated into a scalable architecture a) Maneuver Planning b) Parallel Processing c) Monte Carlo Simulations d) Optimization Algorithms e) SW Application Development/Integration into the Google Cloud Platform 2. Compute Engine Processing a) Application Engine Automated Processing b) Performance testing and Performance Scalability c) Cloud MySQL databases and Database Scalability d) Cloud Data Storage e) Redundancy and Availability

  3. Architectural Techniques to Enable Reliable and Scalable Memory Systems

    OpenAIRE

    Nair, Prashant J.

    2017-01-01

    High capacity and scalable memory systems play a vital role in enabling our desktops, smartphones, and pervasive technologies like Internet of Things (IoT). Unfortunately, memory systems are becoming increasingly prone to faults. This is because we rely on technology scaling to improve memory density, and at small feature sizes, memory cells tend to break easily. Today, memory reliability is seen as the key impediment towards using high-density devices, adopting new technologies, and even bui...

  4. GSKY: A scalable distributed geospatial data server on the cloud

    Science.gov (United States)

    Rozas Larraondo, Pablo; Pringle, Sean; Antony, Joseph; Evans, Ben

    2017-04-01

    Earth systems, environmental and geophysical datasets are an extremely valuable sources of information about the state and evolution of the Earth. Being able to combine information coming from different geospatial collections is in increasing demand by the scientific community, and requires managing and manipulating data with different formats and performing operations such as map reprojections, resampling and other transformations. Due to the large data volume inherent in these collections, storing multiple copies of them is unfeasible and so such data manipulation must be performed on-the-fly using efficient, high performance techniques. Ideally this should be performed using a trusted data service and common system libraries to ensure wide use and reproducibility. Recent developments in distributed computing based on dynamic access to significant cloud infrastructure opens the door for such new ways of processing geospatial data on demand. The National Computational Infrastructure (NCI), hosted at the Australian National University (ANU), has over 10 Petabytes of nationally significant research data collections. Some of these collections, which comprise a variety of observed and modelled geospatial data, are now made available via a highly distributed geospatial data server, called GSKY (pronounced [jee-skee]). GSKY supports on demand processing of large geospatial data products such as satellite earth observation data as well as numerical weather products, allowing interactive exploration and analysis of the data. It dynamically and efficiently distributes the required computations among cloud nodes providing a scalable analysis framework that can adapt to serve large number of concurrent users. Typical geospatial workflows handling different file formats and data types, or blending data in different coordinate projections and spatio-temporal resolutions, is handled transparently by GSKY. This is achieved by decoupling the data ingestion and indexing process as

  5. Superlinearly scalable noise robustness of redundant coupled dynamical systems.

    Science.gov (United States)

    Kohar, Vivek; Kia, Behnam; Lindner, John F; Ditto, William L

    2016-03-01

    We illustrate through theory and numerical simulations that redundant coupled dynamical systems can be extremely robust against local noise in comparison to uncoupled dynamical systems evolving in the same noisy environment. Previous studies have shown that the noise robustness of redundant coupled dynamical systems is linearly scalable and deviations due to noise can be minimized by increasing the number of coupled units. Here, we demonstrate that the noise robustness can actually be scaled superlinearly if some conditions are met and very high noise robustness can be realized with very few coupled units. We discuss these conditions and show that this superlinear scalability depends on the nonlinearity of the individual dynamical units. The phenomenon is demonstrated in discrete as well as continuous dynamical systems. This superlinear scalability not only provides us an opportunity to exploit the nonlinearity of physical systems without being bogged down by noise but may also help us in understanding the functional role of coupled redundancy found in many biological systems. Moreover, engineers can exploit superlinear noise suppression by starting a coupled system near (not necessarily at) the appropriate initial condition.

  6. Event metadata records as a testbed for scalable data mining

    International Nuclear Information System (INIS)

    Gemmeren, P van; Malon, D

    2010-01-01

    At a data rate of 200 hertz, event metadata records ('TAGs,' in ATLAS parlance) provide fertile grounds for development and evaluation of tools for scalable data mining. It is easy, of course, to apply HEP-specific selection or classification rules to event records and to label such an exercise 'data mining,' but our interest is different. Advanced statistical methods and tools such as classification, association rule mining, and cluster analysis are common outside the high energy physics community. These tools can prove useful, not for discovery physics, but for learning about our data, our detector, and our software. A fixed and relatively simple schema makes TAG export to other storage technologies such as HDF5 straightforward. This simplifies the task of exploiting very-large-scale parallel platforms such as Argonne National Laboratory's BlueGene/P, currently the largest supercomputer in the world for open science, in the development of scalable tools for data mining. Using a domain-neutral scientific data format may also enable us to take advantage of existing data mining components from other communities. There is, further, a substantial literature on the topic of one-pass algorithms and stream mining techniques, and such tools may be inserted naturally at various points in the event data processing and distribution chain. This paper describes early experience with event metadata records from ATLAS simulation and commissioning as a testbed for scalable data mining tool development and evaluation.

  7. Scalable force directed graph layout algorithms using fast multipole methods

    KAUST Repository

    Yunis, Enas Abdulrahman

    2012-06-01

    We present an extension to ExaFMM, a Fast Multipole Method library, as a generalized approach for fast and scalable execution of the Force-Directed Graph Layout algorithm. The Force-Directed Graph Layout algorithm is a physics-based approach to graph layout that treats the vertices V as repelling charged particles with the edges E connecting them acting as springs. Traditionally, the amount of work required in applying the Force-Directed Graph Layout algorithm is O(|V|2 + |E|) using direct calculations and O(|V| log |V| + |E|) using truncation, filtering, and/or multi-level techniques. Correct application of the Fast Multipole Method allows us to maintain a lower complexity of O(|V| + |E|) while regaining most of the precision lost in other techniques. Solving layout problems for truly large graphs with millions of vertices still requires a scalable algorithm and implementation. We have been able to leverage the scalability and architectural adaptability of the ExaFMM library to create a Force-Directed Graph Layout implementation that runs efficiently on distributed multicore and multi-GPU architectures. © 2012 IEEE.

  8. The intergroup protocols: Scalable group communication for the internet

    Energy Technology Data Exchange (ETDEWEB)

    Berket, Karlo [Univ. of California, Santa Barbara, CA (United States)

    2000-12-04

    Reliable group ordered delivery of multicast messages in a distributed system is a useful service that simplifies the programming of distributed applications. Such a service helps to maintain the consistency of replicated information and to coordinate the activities of the various processes. With the increasing popularity of the Internet, there is an increasing interest in scaling the protocols that provide this service to the environment of the Internet. The InterGroup protocol suite, described in this dissertation, provides such a service, and is intended for the environment of the Internet with scalability to large numbers of nodes and high latency links. The InterGroup protocols approach the scalability problem from various directions. They redefine the meaning of group membership, allow voluntary membership changes, add a receiver-oriented selection of delivery guarantees that permits heterogeneity of the receiver set, and provide a scalable reliability service. The InterGroup system comprises several components, executing at various sites within the system. Each component provides part of the services necessary to implement a group communication system for the wide-area. The components can be categorized as: (1) control hierarchy, (2) reliable multicast, (3) message distribution and delivery, and (4) process group membership. We have implemented a prototype of the InterGroup protocols in Java, and have tested the system performance in both local-area and wide-area networks.

  9. Scalable Video Coding with Interlayer Signal Decorrelation Techniques

    Directory of Open Access Journals (Sweden)

    Yang Wenxian

    2007-01-01

    Full Text Available Scalability is one of the essential requirements in the compression of visual data for present-day multimedia communications and storage. The basic building block for providing the spatial scalability in the scalable video coding (SVC standard is the well-known Laplacian pyramid (LP. An LP achieves the multiscale representation of the video as a base-layer signal at lower resolution together with several enhancement-layer signals at successive higher resolutions. In this paper, we propose to improve the coding performance of the enhancement layers through efficient interlayer decorrelation techniques. We first show that, with nonbiorthogonal upsampling and downsampling filters, the base layer and the enhancement layers are correlated. We investigate two structures to reduce this correlation. The first structure updates the base-layer signal by subtracting from it the low-frequency component of the enhancement layer signal. The second structure modifies the prediction in order that the low-frequency component in the new enhancement layer is diminished. The second structure is integrated in the JSVM 4.0 codec with suitable modifications in the prediction modes. Experimental results with some standard test sequences demonstrate coding gains up to 1 dB for I pictures and up to 0.7 dB for both I and P pictures.

  10. Scalable Coverage Maintenance for Dense Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Jun Lu

    2007-06-01

    Full Text Available Owing to numerous potential applications, wireless sensor networks have been attracting significant research effort recently. The critical challenge that wireless sensor networks often face is to sustain long-term operation on limited battery energy. Coverage maintenance schemes can effectively prolong network lifetime by selecting and employing a subset of sensors in the network to provide sufficient sensing coverage over a target region. We envision future wireless sensor networks composed of a vast number of miniaturized sensors in exceedingly high density. Therefore, the key issue of coverage maintenance for future sensor networks is the scalability to sensor deployment density. In this paper, we propose a novel coverage maintenance scheme, scalable coverage maintenance (SCOM, which is scalable to sensor deployment density in terms of communication overhead (i.e., number of transmitted and received beacons and computational complexity (i.e., time and space complexity. In addition, SCOM achieves high energy efficiency and load balancing over different sensors. We have validated our claims through both analysis and simulations.

  11. A scalable quantum computer with ions in an array of microtraps

    Science.gov (United States)

    Cirac; Zoller

    2000-04-06

    Quantum computers require the storage of quantum information in a set of two-level systems (called qubits), the processing of this information using quantum gates and a means of final readout. So far, only a few systems have been identified as potentially viable quantum computer models--accurate quantum control of the coherent evolution is required in order to realize gate operations, while at the same time decoherence must be avoided. Examples include quantum optical systems (such as those utilizing trapped ions or neutral atoms, cavity quantum electrodynamics and nuclear magnetic resonance) and solid state systems (using nuclear spins, quantum dots and Josephson junctions). The most advanced candidates are the quantum optical and nuclear magnetic resonance systems, and we expect that they will allow quantum computing with about ten qubits within the next few years. This is still far from the numbers required for useful applications: for example, the factorization of a 200-digit number requires about 3,500 qubits, rising to 100,000 if error correction is implemented. Scalability of proposed quantum computer architectures to many qubits is thus of central importance. Here we propose a model for an ion trap quantum computer that combines scalability (a feature usually associated with solid state proposals) with the advantages of quantum optical systems (in particular, quantum control and long decoherence times).

  12. Data Intensive Architecture for Scalable Cyber Analytics

    Energy Technology Data Exchange (ETDEWEB)

    Olsen, Bryan K.; Johnson, John R.; Critchlow, Terence J.

    2011-11-15

    Cyber analysts are tasked with the identification and mitigation of network exploits and threats. These compromises are difficult to identify due to the characteristics of cyber communication, the volume of traffic, and the duration of possible attack. It is necessary to have analytical tools to help analysts identify anomalies that span seconds, days, and weeks. Unfortunately, providing analytical tools effective access to the volumes of underlying data requires novel architectures, which is often overlooked in operational deployments. Our work is focused on a summary record of communication, called a flow. Flow records are intended to summarize a communication session between a source and a destination, providing a level of aggregation from the base data. Despite this aggregation, many enterprise network perimeter sensors store millions of network flow records per day. The volume of data makes analytics difficult, requiring the development of new techniques to efficiently identify temporal patterns and potential threats. The massive volume makes analytics difficult, but there are other characteristics in the data which compound the problem. Within the billions of records of communication that transact, there are millions of distinct IP addresses involved. Characterizing patterns of entity behavior is very difficult with the vast number of entities that exist in the data. Research has struggled to validate a model for typical network behavior with hopes it will enable the identification of atypical behavior. Complicating matters more, typically analysts are only able to visualize and interact with fractions of data and have the potential to miss long term trends and behaviors. Our analysis approach focuses on aggregate views and visualization techniques to enable flexible and efficient data exploration as well as the capability to view trends over long periods of time. Realizing that interactively exploring summary data allowed analysts to effectively identify

  13. Object-oriented integrated approach for the design of scalable ECG systems.

    Science.gov (United States)

    Boskovic, Dusanka; Besic, Ingmar; Avdagic, Zikrija

    2009-01-01

    The paper presents the implementation of Object-Oriented (OO) integrated approaches to the design of scalable Electro-Cardio-Graph (ECG) Systems. The purpose of this methodology is to preserve real-world structure and relations with the aim to minimize the information loss during the process of modeling, especially for Real-Time (RT) systems. We report on a case study of the design that uses the integration of OO and RT methods and the Unified Modeling Language (UML) standard notation. OO methods identify objects in the real-world domain and use them as fundamental building blocks for the software system. The gained experience based on the strongly defined semantics of the object model is discussed and related problems are analyzed.

  14. Statistical Analysis of Video Frame Size Distribution Originating from Scalable Video Codec (SVC

    Directory of Open Access Journals (Sweden)

    Sima Ahmadpour

    2017-01-01

    Full Text Available Designing an effective and high performance network requires an accurate characterization and modeling of network traffic. The modeling of video frame sizes is normally applied in simulation studies and mathematical analysis and generating streams for testing and compliance purposes. Besides, video traffic assumed as a major source of multimedia traffic in future heterogeneous network. Therefore, the statistical distribution of video data can be used as the inputs for performance modeling of networks. The finding of this paper comprises the theoretical definition of distribution which seems to be relevant to the video trace in terms of its statistical properties and finds the best distribution using both the graphical method and the hypothesis test. The data set used in this article consists of layered video traces generating from Scalable Video Codec (SVC video compression technique of three different movies.

  15. Optimal erasure protection for scalably compressed video streams with limited retransmission.

    Science.gov (United States)

    Taubman, David; Thie, Johnson

    2005-08-01

    This paper shows how the priority encoding transmission (PET) framework may be leveraged to exploit both unequal error protection and limited retransmission for RD-optimized delivery of streaming media. Previous work on scalable media protection with PET has largely ignored the possibility of retransmission. Conversely, the PET framework has not been harnessed by the substantial body of previous work on RD optimized hybrid forward error correction/automatic repeat request schemes. We limit our attention to sources which can be modeled as independently compressed frames (e.g., video frames), where each element in the scalable representation of each frame can be transmitted in one or both of two transmission slots. An optimization algorithm determines the level of protection which should be assigned to each element in each slot, subject to transmission bandwidth constraints. To balance the protection assigned to elements which are being transmitted for the first time with those which are being retransmitted, the proposed algorithm formulates a collection of hypotheses concerning its own behavior in future transmission slots. We show how the PET framework allows for a decoupled optimization algorithm with only modest complexity. Experimental results obtained with Motion JPEG2000 compressed video demonstrate that substantial performance benefits can be obtained using the proposed framework.

  16. Secure and scalable deduplication of horizontally partitioned health data for privacy-preserving distributed statistical computation.

    Science.gov (United States)

    Yigzaw, Kassaye Yitbarek; Michalas, Antonis; Bellika, Johan Gustav

    2017-01-03

    Techniques have been developed to compute statistics on distributed datasets without revealing private information except the statistical results. However, duplicate records in a distributed dataset may lead to incorrect statistical results. Therefore, to increase the accuracy of the statistical analysis of a distributed dataset, secure deduplication is an important preprocessing step. We designed a secure protocol for the deduplication of horizontally partitioned datasets with deterministic record linkage algorithms. We provided a formal security analysis of the protocol in the presence of semi-honest adversaries. The protocol was implemented and deployed across three microbiology laboratories located in Norway, and we ran experiments on the datasets in which the number of records for each laboratory varied. Experiments were also performed on simulated microbiology datasets and data custodians connected through a local area network. The security analysis demonstrated that the protocol protects the privacy of individuals and data custodians under a semi-honest adversarial model. More precisely, the protocol remains secure with the collusion of up to N - 2 corrupt data custodians. The total runtime for the protocol scales linearly with the addition of data custodians and records. One million simulated records distributed across 20 data custodians were deduplicated within 45 s. The experimental results showed that the protocol is more efficient and scalable than previous protocols for the same problem. The proposed deduplication protocol is efficient and scalable for practical uses while protecting the privacy of patients and data custodians.

  17. Programming time-multiplexed reconfigurable hardware using a scalable neuromorphic compiler.

    Science.gov (United States)

    Minkovich, Kirill; Srinivasa, Narayan; Cruz-Albrecht, Jose M; Cho, Youngkwan; Nogin, Aleksey

    2012-06-01

    Scalability and connectivity are two key challenges in designing neuromorphic hardware that can match biological levels. In this paper, we describe a neuromorphic system architecture design that addresses an approach to meet these challenges using traditional complementary metal-oxide-semiconductor (CMOS) hardware. A key requirement in realizing such neural architectures in hardware is the ability to automatically configure the hardware to emulate any neural architecture or model. The focus for this paper is to describe the details of such a programmable front-end. This programmable front-end is composed of a neuromorphic compiler and a digital memory, and is designed based on the concept of synaptic time-multiplexing (STM). The neuromorphic compiler automatically translates any given neural architecture to hardware switch states and these states are stored in digital memory to enable desired neural architectures. STM enables our proposed architecture to address scalability and connectivity using traditional CMOS hardware. We describe the details of the proposed design and the programmable front-end, and provide examples to illustrate its capabilities. We also provide perspectives for future extensions and potential applications.

  18. Space-Filling Supercapacitor Carpets: Highly scalable fractal architecture for energy storage

    Science.gov (United States)

    Tiliakos, Athanasios; Trefilov, Alexandra M. I.; Tanasǎ, Eugenia; Balan, Adriana; Stamatin, Ioan

    2018-04-01

    Revamping ground-breaking ideas from fractal geometry, we propose an alternative micro-supercapacitor configuration realized by laser-induced graphene (LIG) foams produced via laser pyrolysis of inexpensive commercial polymers. The Space-Filling Supercapacitor Carpet (SFSC) architecture introduces the concept of nested electrodes based on the pre-fractal Peano space-filling curve, arranged in a symmetrical equilateral setup that incorporates multiple parallel capacitor cells sharing common electrodes for maximum efficiency and optimal length-to-area distribution. We elucidate on the theoretical foundations of the SFSC architecture, and we introduce innovations (high-resolution vector-mode printing) in the LIG method that allow for the realization of flexible and scalable devices based on low iterations of the Peano algorithm. SFSCs exhibit distributed capacitance properties, leading to capacitance, energy, and power ratings proportional to the number of nested electrodes (up to 4.3 mF, 0.4 μWh, and 0.2 mW for the largest tested model of low iteration using aqueous electrolytes), with competitively high energy and power densities. This can pave the road for full scalability in energy storage, reaching beyond the scale of micro-supercapacitors for incorporating into larger and more demanding applications.

  19. Scalable electrophysiology in intact small animals with nanoscale suspended electrode arrays

    Science.gov (United States)

    Gonzales, Daniel L.; Badhiwala, Krishna N.; Vercosa, Daniel G.; Avants, Benjamin W.; Liu, Zheng; Zhong, Weiwei; Robinson, Jacob T.

    2017-07-01

    Electrical measurements from large populations of animals would help reveal fundamental properties of the nervous system and neurological diseases. Small invertebrates are ideal for these large-scale studies; however, patch-clamp electrophysiology in microscopic animals typically requires invasive dissections and is low-throughput. To overcome these limitations, we present nano-SPEARs: suspended electrodes integrated into a scalable microfluidic device. Using this technology, we have made the first extracellular recordings of body-wall muscle electrophysiology inside an intact roundworm, Caenorhabditis elegans. We can also use nano-SPEARs to record from multiple animals in parallel and even from other species, such as Hydra littoralis. Furthermore, we use nano-SPEARs to establish the first electrophysiological phenotypes for C. elegans models for amyotrophic lateral sclerosis and Parkinson's disease, and show a partial rescue of the Parkinson's phenotype through drug treatment. These results demonstrate that nano-SPEARs provide the core technology for microchips that enable scalable, in vivo studies of neurobiology and neurological diseases.

  20. VPLS: an effective technology for building scalable transparent LAN services

    Science.gov (United States)

    Dong, Ximing; Yu, Shaohua

    2005-02-01

    Virtual Private LAN Service (VPLS) is generating considerable interest with enterprises and service providers as it offers multipoint transparent LAN service (TLS) over MPLS networks. This paper describes an effective technology - VPLS, which links virtual switch instances (VSIs) through MPLS to form an emulated Ethernet switch and build Scalable Transparent Lan Services. It first focuses on the architecture of VPLS with Ethernet bridging technique at the edge and MPLS at the core, then it tries to elucidate the data forwarding mechanism within VPLS domain, including learning and aging MAC addresses on a per LSP basis, flooding of unknown frames and replication for unknown, multicast, and broadcast frames. The loop-avoidance mechanism, known as split horizon forwarding, is also analyzed. Another important aspect of VPLS service is its basic operation, including autodiscovery and signaling, is discussed. From the perspective of efficiency and scalability the paper compares two important signaling mechanism, BGP and LDP, which are used to set up a PW between the PEs and bind the PWs to a particular VSI. With the extension of VPLS and the increase of full mesh of PWs between PE devices (n*(n-1)/2 PWs in all, a n2 complete problem), VPLS instance could have a large number of remote PE associations, resulting in an inefficient use of network bandwidth and system resources as the ingress PE has to replicate each frame and append MPLS labels for remote PE. So the latter part of this paper focuses on the scalability issue: the Hierarchical VPLS. Within the architecture of HVPLS, this paper addresses two ways to cope with a possibly large number of MAC addresses, which make VPLS operate more efficiently.

  1. A scalable lock-free hash table with open addressing

    DEFF Research Database (Denmark)

    Nielsen, Jesper Puge; Karlsson, Sven

    2016-01-01

    and concurrent operations without any locks. In this paper, we present a new fully lock-free open addressed hash table with a simpler design than prior published work. We split hash table insertions into two atomic phases: first inserting a value ignoring other concurrent operations, then in the second phase......Concurrent data structures synchronized with locks do not scale well with the number of threads. As more scalable alternatives, concurrent data structures and algorithms based on widely available, however advanced, atomic operations have been proposed. These data structures allow for correct...

  2. Highly Scalable Trip Grouping for Large Scale Collective Transportation Systems

    DEFF Research Database (Denmark)

    Gidofalvi, Gyozo; Pedersen, Torben Bach; Risch, Tore

    2008-01-01

    Transportation-related problems, like road congestion, parking, and pollution, are increasing in most cities. In order to reduce traffic, recent work has proposed methods for vehicle sharing, for example for sharing cabs by grouping "closeby" cab requests and thus minimizing transportation cost...... and utilizing cab space. However, the methods published so far do not scale to large data volumes, which is necessary to facilitate large-scale collective transportation systems, e.g., ride-sharing systems for large cities. This paper presents highly scalable trip grouping algorithms, which generalize previous...

  3. pcircle - A Suite of Scalable Parallel File System Tools

    Energy Technology Data Exchange (ETDEWEB)

    2015-10-01

    Most of the software related to file system are written for conventional local file system, they are serialized and can't take advantage of the benefit of a large scale parallel file system. "pcircle" software builds on top of ubiquitous MPI in cluster computing environment and "work-stealing" pattern to provide a scalable, high-performance suite of file system tools. In particular - it implemented parallel data copy and parallel data checksumming, with advanced features such as async progress report, checkpoint and restart, as well as integrity checking.

  4. Scalable video on demand adaptive Internet-based distribution

    CERN Document Server

    Zink, Michael

    2013-01-01

    In recent years, the proliferation of available video content and the popularity of the Internet have encouraged service providers to develop new ways of distributing content to clients. Increasing video scaling ratios and advanced digital signal processing techniques have led to Internet Video-on-Demand applications, but these currently lack efficiency and quality. Scalable Video on Demand: Adaptive Internet-based Distribution examines how current video compression and streaming can be used to deliver high-quality applications over the Internet. In addition to analysing the problems

  5. Scalable web services for the PSIPRED Protein Analysis Workbench.

    Science.gov (United States)

    Buchan, Daniel W A; Minneci, Federico; Nugent, Tim C O; Bryson, Kevin; Jones, David T

    2013-07-01

    Here, we present the new UCL Bioinformatics Group's PSIPRED Protein Analysis Workbench. The Workbench unites all of our previously available analysis methods into a single web-based framework. The new web portal provides a greatly streamlined user interface with a number of new features to allow users to better explore their results. We offer a number of additional services to enable computationally scalable execution of our prediction methods; these include SOAP and XML-RPC web server access and new HADOOP packages. All software and services are available via the UCL Bioinformatics Group website at http://bioinf.cs.ucl.ac.uk/.

  6. A Scalable Architecture of a Structured LDPC Decoder

    Science.gov (United States)

    Lee, Jason Kwok-San; Lee, Benjamin; Thorpe, Jeremy; Andrews, Kenneth; Dolinar, Sam; Hamkins, Jon

    2004-01-01

    We present a scalable decoding architecture for a certain class of structured LDPC codes. The codes are designed using a small (n,r) protograph that is replicated Z times to produce a decoding graph for a (Z x n, Z x r) code. Using this architecture, we have implemented a decoder for a (4096,2048) LDPC code on a Xilinx Virtex-II 2000 FPGA, and achieved decoding speeds of 31 Mbps with 10 fixed iterations. The implemented message-passing algorithm uses an optimized 3-bit non-uniform quantizer that operates with 0.2dB implementation loss relative to a floating point decoder.

  7. Interactive segmentation: a scalable superpixel-based method

    Science.gov (United States)

    Mathieu, Bérengère; Crouzil, Alain; Puel, Jean-Baptiste

    2017-11-01

    This paper addresses the problem of interactive multiclass segmentation of images. We propose a fast and efficient new interactive segmentation method called superpixel α fusion (SαF). From a few strokes drawn by a user over an image, this method extracts relevant semantic objects. To get a fast calculation and an accurate segmentation, SαF uses superpixel oversegmentation and support vector machine classification. We compare SαF with competing algorithms by evaluating its performances on reference benchmarks. We also suggest four new datasets to evaluate the scalability of interactive segmentation methods, using images from some thousand to several million pixels. We conclude with two applications of SαF.

  8. Robust and scalable optical one-way quantum computation

    International Nuclear Information System (INIS)

    Wang Hefeng; Yang Chuiping; Nori, Franco

    2010-01-01

    We propose an efficient approach for deterministically generating scalable cluster states with photons. This approach involves unitary transformations performed on atoms coupled to optical cavities. Its operation cost scales linearly with the number of qubits in the cluster state, and photon qubits are encoded such that single-qubit operations can be easily implemented by using linear optics. Robust optical one-way quantum computation can be performed since cluster states can be stored in atoms and then transferred to photons that can be easily operated and measured. Therefore, this proposal could help in performing robust large-scale optical one-way quantum computation.

  9. Scalable Brain Network Construction on White Matter Fibers.

    Science.gov (United States)

    Chung, Moo K; Adluru, Nagesh; Dalton, Kim M; Alexander, Andrew L; Davidson, Richard J

    2011-02-12

    DTI offers a unique opportunity to characterize the structural connectivity of the human brain non-invasively by tracing white matter fiber tracts. Whole brain tractography studies routinely generate up to half million tracts per brain, which serves as edges in an extremely large 3D graph with up to half million edges. Currently there is no agreed-upon method for constructing the brain structural network graphs out of large number of white matter tracts. In this paper, we present a scalable iterative framework called the ε-neighbor method for building a network graph and apply it to testing abnormal connectivity in autism.

  10. Parallelism and Scalability in an Image Processing Application

    DEFF Research Database (Denmark)

    Rasmussen, Morten Sleth; Stuart, Matthias Bo; Karlsson, Sven

    2008-01-01

    parallel programs. This paper investigates parallelism and scalability of an embedded image processing application. The major challenges faced when parallelizing the application were to extract enough parallelism from the application and to reduce load imbalance. The application has limited immediately......The recent trends in processor architecture show that parallel processing is moving into new areas of computing in the form of many-core desktop processors and multi-processor system-on-chip. This means that parallel processing is required in application areas that traditionally have not used...

  11. Parallelism and Scalability in an Image Processing Application

    DEFF Research Database (Denmark)

    Rasmussen, Morten Sleth; Stuart, Matthias Bo; Karlsson, Sven

    2009-01-01

    parallel programs. This paper investigates parallelism and scalability of an embedded image processing application. The major challenges faced when parallelizing the application were to extract enough parallelism from the application and to reduce load imbalance. The application has limited immediately......The recent trends in processor architecture show that parallel processing is moving into new areas of computing in the form of many-core desktop processors and multi-processor system-on-chips. This means that parallel processing is required in application areas that traditionally have not used...

  12. Scalable error correction in distributed ion trap computers

    International Nuclear Information System (INIS)

    Oi, Daniel K. L.; Devitt, Simon J.; Hollenberg, Lloyd C. L.

    2006-01-01

    A major challenge for quantum computation in ion trap systems is scalable integration of error correction and fault tolerance. We analyze a distributed architecture with rapid high-fidelity local control within nodes and entangled links between nodes alleviating long-distance transport. We demonstrate fault-tolerant operator measurements which are used for error correction and nonlocal gates. This scheme is readily applied to linear ion traps which cannot be scaled up beyond a few ions per individual trap but which have access to a probabilistic entanglement mechanism. A proof-of-concept system is presented which is within the reach of current experiment

  13. Focal plane array with modular pixel array components for scalability

    Science.gov (United States)

    Kay, Randolph R; Campbell, David V; Shinde, Subhash L; Rienstra, Jeffrey L; Serkland, Darwin K; Holmes, Michael L

    2014-12-09

    A modular, scalable focal plane array is provided as an array of integrated circuit dice, wherein each die includes a given amount of modular pixel array circuitry. The array of dice effectively multiplies the amount of modular pixel array circuitry to produce a larger pixel array without increasing die size. Desired pixel pitch across the enlarged pixel array is preserved by forming die stacks with each pixel array circuitry die stacked on a separate die that contains the corresponding signal processing circuitry. Techniques for die stack interconnections and die stack placement are implemented to ensure that the desired pixel pitch is preserved across the enlarged pixel array.

  14. A scalable parallel algorithm for multiple objective linear programs

    Science.gov (United States)

    Wiecek, Malgorzata M.; Zhang, Hong

    1994-01-01

    This paper presents an ADBASE-based parallel algorithm for solving multiple objective linear programs (MOLP's). Job balance, speedup and scalability are of primary interest in evaluating efficiency of the new algorithm. Implementation results on Intel iPSC/2 and Paragon multiprocessors show that the algorithm significantly speeds up the process of solving MOLP's, which is understood as generating all or some efficient extreme points and unbounded efficient edges. The algorithm gives specially good results for large and very large problems. Motivation and justification for solving such large MOLP's are also included.

  15. Empirical Evaluation of Superposition Coded Multicasting for Scalable Video

    KAUST Repository

    Chun Pong Lau

    2013-03-01

    In this paper we investigate cross-layer superposition coded multicast (SCM). Previous studies have proven its effectiveness in exploiting better channel capacity and service granularities via both analytical and simulation approaches. However, it has never been practically implemented using a commercial 4G system. This paper demonstrates our prototype in achieving the SCM using a standard 802.16 based testbed for scalable video transmissions. In particular, to implement the superposition coded (SPC) modulation, we take advantage a novel software approach, namely logical SPC (L-SPC), which aims to mimic the physical layer superposition coded modulation. The emulation results show improved throughput comparing with generic multicast method.

  16. Scalable and Hybrid Radio Resource Management for Future Wireless Networks

    DEFF Research Database (Denmark)

    Mino, E.; Luo, Jijun; Tragos, E.

    2007-01-01

    The concept of ubiquitous and scalable system is applied in the IST WINNER II [1] project to deliver optimum performance for different deployment scenarios, from local area to wide area wireless networks. The integration in a unique radio system of a cellular and local area type networks supposes...... a great advantage for the final user and for the operator, compared with the current situation, with disconnected systems, usually with different subscriptions, radio interfaces and terminals. To be a ubiquitous wireless system, the IST project WINNER II has defined three system modes. This contribution...

  17. Scalability of Ferroelectric Tunnel Junctions to Sub-100 nm Dimensions

    Science.gov (United States)

    Abuwasib, Mohammad

    The ferroelectric tunnel junction (FTJ) is an emerging low-power device that has potential application as a non-volatile memory and logic element in beyond-CMOS circuits. As a beyond- CMOS device, it is necessary to investigate the device scaling limit of FTJs to sub-50 nm dimensions. In addition to the fabrication of scaled FTJs, the integration challenges and CMOS compatibility of the device needs to be addressed. FTJ device performance including ON/OFF ratio, memory retention time, switching endurance, write /read speed and power dissipation need to be characterized for benchmarking of this emerging device, compared to its charge-based counterparts such as DRAM, NAND/NOR flash, as well as to other emerging memory devices. In this dissertation, a detailed investigation of scaling of BaTiO3 (BTO) based FTJs was performed, from full-scale integration to electrical characterization. Two types of FTJs with La0.67Sr0.33MnO3 (LSMO) and SrRuO3 (SRO) bottom electrodes were investigated in this work namely; Co/BTO/LSMO and Co/BTO/SRO. A CMOS compatible fabrication process for integration of Co/BTO/LSMO FTJ devices ( 3x3 microm 2) was demonstrated for the first time using standard photolithography and self-aligned RIE technique. The fabricated FTJ device showed switching behavior, however, degradation of the LSMO contact was observed during the fabrication process. A detailed investigation of the contact properties of bottom electrode materials (LSMO, SRO) for BTO-based FTJs was performed. The process and thermal stability of different contact overlayers (Ti, Pt) was explained to understand the nature of the ohmic contacts for metal to SRO and LSMO layers. Noble metals-to-SRO was found to form the most stable contacts for FTJs. Based on this study, a systematic scalability study of Co/BTO/SRO FTJs was carried out from micron ( 3x3 microm2) to submicron ( 200x200 nm2) dimensions. Positive UP Negative Down (PUND) measurement confirms the ferroelectric properties of the BTO

  18. WIFIRE: A Scalable Data-Driven Monitoring, Dynamic Prediction and Resilience Cyberinfrastructure for Wildfires

    Science.gov (United States)

    Altintas, I.; Block, J.; Braun, H.; de Callafon, R. A.; Gollner, M. J.; Smarr, L.; Trouve, A.

    2013-12-01

    Recent studies confirm that climate change will cause wildfires to increase in frequency and severity in the coming decades especially for California and in much of the North American West. The most critical sustainability issue in the midst of these ever-changing dynamics is how to achieve a new social-ecological equilibrium of this fire ecology. Wildfire wind speeds and directions change in an instant, and first responders can only be effective when they take action as quickly as the conditions change. To deliver information needed for sustainable policy and management in this dynamically changing fire regime, we must capture these details to understand the environmental processes. We are building an end-to-end cyberinfrastructure (CI), called WIFIRE, for real-time and data-driven simulation, prediction and visualization of wildfire behavior. The WIFIRE integrated CI system supports social-ecological resilience to the changing fire ecology regime in the face of urban dynamics and climate change. Networked observations, e.g., heterogeneous satellite data and real-time remote sensor data is integrated with computational techniques in signal processing, visualization, modeling and data assimilation to provide a scalable, technological, and educational solution to monitor weather patterns to predict a wildfire's Rate of Spread. Our collaborative WIFIRE team of scientists, engineers, technologists, government policy managers, private industry, and firefighters architects implement CI pathways that enable joint innovation for wildfire management. Scientific workflows are used as an integrative distributed programming model and simplify the implementation of engineering modules for data-driven simulation, prediction and visualization while allowing integration with large-scale computing facilities. WIFIRE will be scalable to users with different skill-levels via specialized web interfaces and user-specified alerts for environmental events broadcasted to receivers before

  19. Neutron generators with size scalability, ease of fabrication and multiple ion source functionalities

    Science.gov (United States)

    Elizondo-Decanini, Juan M

    2014-11-18

    A neutron generator is provided with a flat, rectilinear geometry and surface mounted metallizations. This construction provides scalability and ease of fabrication, and permits multiple ion source functionalities.

  20. Traffic and Quality Characterization of the H.264/AVC Scalable Video Coding Extension

    Directory of Open Access Journals (Sweden)

    Geert Van der Auwera

    2008-01-01

    Full Text Available The recent scalable video coding (SVC extension to the H.264/AVC video coding standard has unprecedented compression efficiency while supporting a wide range of scalability modes, including temporal, spatial, and quality (SNR scalability, as well as combined spatiotemporal SNR scalability. The traffic characteristics, especially the bit rate variabilities, of the individual layer streams critically affect their network transport. We study the SVC traffic statistics, including the bit rate distortion and bit rate variability distortion, with long CIF resolution video sequences and compare them with the corresponding MPEG-4 Part 2 traffic statistics. We consider (i temporal scalability with three temporal layers, (ii spatial scalability with a QCIF base layer and a CIF enhancement layer, as well as (iii quality scalability modes FGS and MGS. We find that the significant improvement in RD efficiency of SVC is accompanied by substantially higher traffic variabilities as compared to the equivalent MPEG-4 Part 2 streams. We find that separately analyzing the traffic of temporal-scalability only encodings gives reasonable estimates of the traffic statistics of the temporal layers embedded in combined spatiotemporal encodings and in the base layer of combined FGS-temporal encodings. Overall, we find that SVC achieves significantly higher compression ratios than MPEG-4 Part 2, but produces unprecedented levels of traffic variability, thus presenting new challenges for the network transport of scalable video.

  1. SCALABLE TIME SERIES CHANGE DETECTION FOR BIOMASS MONITORING USING GAUSSIAN PROCESS

    Data.gov (United States)

    National Aeronautics and Space Administration — SCALABLE TIME SERIES CHANGE DETECTION FOR BIOMASS MONITORING USING GAUSSIAN PROCESS VARUN CHANDOLA AND RANGA RAJU VATSAVAI Abstract. Biomass monitoring,...

  2. On Scalability and Replicability of Smart Grid Projects—A Case Study

    Directory of Open Access Journals (Sweden)

    Lukas Sigrist

    2016-03-01

    Full Text Available This paper studies the scalability and replicability of smart grid projects. Currently, most smart grid projects are still in the R&D or demonstration phases. The full roll-out of the tested solutions requires a suitable degree of scalability and replicability to prevent project demonstrators from remaining local experimental exercises. Scalability and replicability are the preliminary requisites to perform scaling-up and replication successfully; therefore, scalability and replicability allow for or at least reduce barriers for the growth and reuse of the results of project demonstrators. The paper proposes factors that influence and condition a project’s scalability and replicability. These factors involve technical, economic, regulatory and stakeholder acceptance related aspects, and they describe requirements for scalability and replicability. In order to assess and evaluate the identified scalability and replicability factors, data has been collected from European and national smart grid projects by means of a survey, reflecting the projects’ view and results. The evaluation of the factors allows quantifying the status quo of on-going projects with respect to the scalability and replicability, i.e., they provide a feedback on to what extent projects take into account these factors and on whether the projects’ results and solutions are actually scalable and replicable.

  3. Ultracold molecules: vehicles to scalable quantum information processing

    International Nuclear Information System (INIS)

    Brickman Soderberg, Kathy-Anne; Gemelke, Nathan; Chin Cheng

    2009-01-01

    In this paper, we describe a novel scheme to implement scalable quantum information processing using Li-Cs molecular states to entangle 6 Li and 133 Cs ultracold atoms held in independent optical lattices. The 6 Li atoms will act as quantum bits to store information and 133 Cs atoms will serve as messenger bits that aid in quantum gate operations and mediate entanglement between distant qubit atoms. Each atomic species is held in a separate optical lattice and the atoms can be overlapped by translating the lattices with respect to each other. When the messenger and qubit atoms are overlapped, targeted single-spin operations and entangling operations can be performed by coupling the atomic states to a molecular state with radio-frequency pulses. By controlling the frequency and duration of the radio-frequency pulses, entanglement can be either created or swapped between a qubit messenger pair. We estimate operation fidelities for entangling two distant qubits and discuss scalability of this scheme and constraints on the optical lattice lasers. Finally we demonstrate experimental control of the optical potentials sufficient to translate atoms in the lattice.

  4. Scalable Nernst thermoelectric power using a coiled galfenol wire

    Science.gov (United States)

    Yang, Zihao; Codecido, Emilio A.; Marquez, Jason; Zheng, Yuanhua; Heremans, Joseph P.; Myers, Roberto C.

    2017-09-01

    The Nernst thermopower usually is considered far too weak in most metals for waste heat recovery. However, its transverse orientation gives it an advantage over the Seebeck effect on non-flat surfaces. Here, we experimentally demonstrate the scalable generation of a Nernst voltage in an air-cooled metal wire coiled around a hot cylinder. In this geometry, a radial temperature gradient generates an azimuthal electric field in the coil. A Galfenol (Fe0.85Ga0.15) wire is wrapped around a cartridge heater, and the voltage drop across the wire is measured as a function of axial magnetic field. As expected, the Nernst voltage scales linearly with the length of the wire. Based on heat conduction and fluid dynamic equations, finite-element method is used to calculate the temperature gradient across the Galfenol wire and determine the Nernst coefficient. A giant Nernst coefficient of -2.6 μV/KT at room temperature is estimated, in agreement with measurements on bulk Galfenol. We expect that the giant Nernst effect in Galfenol arises from its magnetostriction, presumably through enhanced magnon-phonon coupling. Our results demonstrate the feasibility of a transverse thermoelectric generator capable of scalable output power from non-flat heat sources.

  5. Scalable manufacturing of biomimetic moldable hydrogels for industrial applications

    Science.gov (United States)

    Yu, Anthony C.; Chen, Haoxuan; Chan, Doreen; Agmon, Gillie; Stapleton, Lyndsay M.; Sevit, Alex M.; Tibbitt, Mark W.; Acosta, Jesse D.; Zhang, Tony; Franzia, Paul W.; Langer, Robert; Appel, Eric A.

    2016-12-01

    Hydrogels are a class of soft material that is exploited in many, often completely disparate, industrial applications, on account of their unique and tunable properties. Advances in soft material design are yielding next-generation moldable hydrogels that address engineering criteria in several industrial settings such as complex viscosity modifiers, hydraulic or injection fluids, and sprayable carriers. Industrial implementation of these viscoelastic materials requires extreme volumes of material, upwards of several hundred million gallons per year. Here, we demonstrate a paradigm for the scalable fabrication of self-assembled moldable hydrogels using rationally engineered, biomimetic polymer-nanoparticle interactions. Cellulose derivatives are linked together by selective adsorption to silica nanoparticles via dynamic and multivalent interactions. We show that the self-assembly process for gel formation is easily scaled in a linear fashion from 0.5 mL to over 15 L without alteration of the mechanical properties of the resultant materials. The facile and scalable preparation of these materials leveraging self-assembly of inexpensive, renewable, and environmentally benign starting materials, coupled with the tunability of their properties, make them amenable to a range of industrial applications. In particular, we demonstrate their utility as injectable materials for pipeline maintenance and product recovery in industrial food manufacturing as well as their use as sprayable carriers for robust application of fire retardants in preventing wildland fires.

  6. A highly scalable peptide-based assay system for proteomics.

    Directory of Open Access Journals (Sweden)

    Igor A Kozlov

    Full Text Available We report a scalable and cost-effective technology for generating and screening high-complexity customizable peptide sets. The peptides are made as peptide-cDNA fusions by in vitro transcription/translation from pools of DNA templates generated by microarray-based synthesis. This approach enables large custom sets of peptides to be designed in silico, manufactured cost-effectively in parallel, and assayed efficiently in a multiplexed fashion. The utility of our peptide-cDNA fusion pools was demonstrated in two activity-based assays designed to discover protease and kinase substrates. In the protease assay, cleaved peptide substrates were separated from uncleaved and identified by digital sequencing of their cognate cDNAs. We screened the 3,011 amino acid HCV proteome for susceptibility to cleavage by the HCV NS3/4A protease and identified all 3 known trans cleavage sites with high specificity. In the kinase assay, peptide substrates phosphorylated by tyrosine kinases were captured and identified by sequencing of their cDNAs. We screened a pool of 3,243 peptides against Abl kinase and showed that phosphorylation events detected were specific and consistent with the known substrate preferences of Abl kinase. Our approach is scalable and adaptable to other protein-based assays.

  7. Scalable parallel prefix solvers for discrete ordinates transport

    International Nuclear Information System (INIS)

    Pautz, S.; Pandya, T.; Adams, M.

    2009-01-01

    The well-known 'sweep' algorithm for inverting the streaming-plus-collision term in first-order deterministic radiation transport calculations has some desirable numerical properties. However, it suffers from parallel scaling issues caused by a lack of concurrency. The maximum degree of concurrency, and thus the maximum parallelism, grows more slowly than the problem size for sweeps-based solvers. We investigate a new class of parallel algorithms that involves recasting the streaming-plus-collision problem in prefix form and solving via cyclic reduction. This method, although computationally more expensive at low levels of parallelism than the sweep algorithm, offers better theoretical scalability properties. Previous work has demonstrated this approach for one-dimensional calculations; we show how to extend it to multidimensional calculations. Notably, for multiple dimensions it appears that this approach is limited to long-characteristics discretizations; other discretizations cannot be cast in prefix form. We implement two variants of the algorithm within the radlib/SCEPTRE transport code library at Sandia National Laboratories and show results on two different massively parallel systems. Both the 'forward' and 'symmetric' solvers behave similarly, scaling well to larger degrees of parallelism then sweeps-based solvers. We do observe some issues at the highest levels of parallelism (relative to the system size) and discuss possible causes. We conclude that this approach shows good potential for future parallel systems, but the parallel scalability will depend heavily on the architecture of the communication networks of these systems. (authors)

  8. Scalable privacy-preserving big data aggregation mechanism

    Directory of Open Access Journals (Sweden)

    Dapeng Wu

    2016-08-01

    Full Text Available As the massive sensor data generated by large-scale Wireless Sensor Networks (WSNs recently become an indispensable part of ‘Big Data’, the collection, storage, transmission and analysis of the big sensor data attract considerable attention from researchers. Targeting the privacy requirements of large-scale WSNs and focusing on the energy-efficient collection of big sensor data, a Scalable Privacy-preserving Big Data Aggregation (Sca-PBDA method is proposed in this paper. Firstly, according to the pre-established gradient topology structure, sensor nodes in the network are divided into clusters. Secondly, sensor data is modified by each node according to the privacy-preserving configuration message received from the sink. Subsequently, intra- and inter-cluster data aggregation is employed during the big sensor data reporting phase to reduce energy consumption. Lastly, aggregated results are recovered by the sink to complete the privacy-preserving big data aggregation. Simulation results validate the efficacy and scalability of Sca-PBDA and show that the big sensor data generated by large-scale WSNs is efficiently aggregated to reduce network resource consumption and the sensor data privacy is effectively protected to meet the ever-growing application requirements.

  9. The Node Monitoring Component of a Scalable Systems Software Environment

    Energy Technology Data Exchange (ETDEWEB)

    Miller, Samuel James [Iowa State Univ., Ames, IA (United States)

    2006-01-01

    This research describes Fountain, a suite of programs used to monitor the resources of a cluster. A cluster is a collection of individual computers that are connected via a high speed communication network. They are traditionally used by users who desire more resources, such as processing power and memory, than any single computer can provide. A common drawback to effectively utilizing such a large-scale system is the management infrastructure, which often does not often scale well as the system grows. Large-scale parallel systems provide new research challenges in the area of systems software, the programs or tools that manage the system from boot-up to running a parallel job. The approach presented in this thesis utilizes a collection of separate components that communicate with each other to achieve a common goal. While systems software comprises a broad array of components, this thesis focuses on the design choices for a node monitoring component. We will describe Fountain, an implementation of the Scalable Systems Software (SSS) node monitor specification. It is targeted at aggregate node monitoring for clusters, focusing on both scalability and fault tolerance as its design goals. It leverages widely used technologies such as XML and HTTP to present an interface to other components in the SSS environment.

  10. Scalable fast multipole methods for vortex element methods

    KAUST Repository

    Hu, Qi

    2012-11-01

    We use a particle-based method to simulate incompressible flows, where the Fast Multipole Method (FMM) is used to accelerate the calculation of particle interactions. The most time-consuming kernelsâ\\'the Biot-Savart equation and stretching term of the vorticity equationâ\\'are mathematically reformulated so that only two Laplace scalar potentials are used instead of six, while automatically ensuring divergence-free far-field computation. Based on this formulation, and on our previous work for a scalar heterogeneous FMM algorithm, we develop a new FMM-based vortex method capable of simulating general flows including turbulence on heterogeneous architectures, which distributes the work between multi-core CPUs and GPUs to best utilize the hardware resources and achieve excellent scalability. The algorithm also uses new data structures which can dynamically manage inter-node communication and load balance efficiently but with only a small parallel construction overhead. This algorithm can scale to large-sized clusters showing both strong and weak scalability. Careful error and timing trade-off analysis are also performed for the cutoff functions induced by the vortex particle method. Our implementation can perform one time step of the velocity+stretching for one billion particles on 32 nodes in 55.9 seconds, which yields 49.12 Tflop/s. © 2012 IEEE.

  11. The TOTEM DAQ based on the Scalable Readout System (SRS)

    Science.gov (United States)

    Quinto, Michele; Cafagna, Francesco S.; Fiergolski, Adrian; Radicioni, Emilio

    2018-02-01

    The TOTEM (TOTal cross section, Elastic scattering and diffraction dissociation Measurement at the LHC) experiment at LHC, has been designed to measure the total proton-proton cross-section and study the elastic and diffractive scattering at the LHC energies. In order to cope with the increased machine luminosity and the higher statistic required by the extension of the TOTEM physics program, approved for the LHC's Run Two phase, the previous VME based data acquisition system has been replaced with a new one based on the Scalable Readout System. The system features an aggregated data throughput of 2GB / s towards the online storage system. This makes it possible to sustain a maximum trigger rate of ˜ 24kHz, to be compared with the 1KHz rate of the previous system. The trigger rate is further improved by implementing zero-suppression and second-level hardware algorithms in the Scalable Readout System. The new system fulfils the requirements for an increased efficiency, providing higher bandwidth, and increasing the purity of the data recorded. Moreover full compatibility has been guaranteed with the legacy front-end hardware, as well as with the DAQ interface of the CMS experiment and with the LHC's Timing, Trigger and Control distribution system. In this contribution we describe in detail the architecture of full system and its performance measured during the commissioning phase at the LHC Interaction Point.

  12. ENDEAVOUR: A Scalable SDN Architecture for Real-World IXPs

    KAUST Repository

    Antichi, Gianni

    2017-10-25

    Innovation in interdomain routing has remained stagnant for over a decade. Recently, IXPs have emerged as economically-advantageous interconnection points for reducing path latencies and exchanging ever increasing traffic volumes among, possibly, hundreds of networks. Given their far-reaching implications on interdomain routing, IXPs are the ideal place to foster network innovation and extend the benefits of SDN to the interdomain level. In this paper, we present, evaluate, and demonstrate ENDEAVOUR, an SDN platform for IXPs. ENDEAVOUR can be deployed on a multi-hop IXP fabric, supports a large number of use cases, and is highly-scalable while avoiding broadcast storms. Our evaluation with real data from one of the largest IXPs, demonstrates the benefits and scalability of our solution: ENDEAVOUR requires around 70% fewer rules than alternative SDN solutions thanks to our rule partitioning mechanism. In addition, by providing an open source solution, we invite everyone from the community to experiment (and improve) our implementation as well as adapt it to new use cases.

  13. Scalable Nernst thermoelectric power using a coiled galfenol wire

    Directory of Open Access Journals (Sweden)

    Zihao Yang

    2017-09-01

    Full Text Available The Nernst thermopower usually is considered far too weak in most metals for waste heat recovery. However, its transverse orientation gives it an advantage over the Seebeck effect on non-flat surfaces. Here, we experimentally demonstrate the scalable generation of a Nernst voltage in an air-cooled metal wire coiled around a hot cylinder. In this geometry, a radial temperature gradient generates an azimuthal electric field in the coil. A Galfenol (Fe0.85Ga0.15 wire is wrapped around a cartridge heater, and the voltage drop across the wire is measured as a function of axial magnetic field. As expected, the Nernst voltage scales linearly with the length of the wire. Based on heat conduction and fluid dynamic equations, finite-element method is used to calculate the temperature gradient across the Galfenol wire and determine the Nernst coefficient. A giant Nernst coefficient of -2.6 μV/KT at room temperature is estimated, in agreement with measurements on bulk Galfenol. We expect that the giant Nernst effect in Galfenol arises from its magnetostriction, presumably through enhanced magnon-phonon coupling. Our results demonstrate the feasibility of a transverse thermoelectric generator capable of scalable output power from non-flat heat sources.

  14. Performance-scalable volumetric data classification for online industrial inspection

    Science.gov (United States)

    Abraham, Aby J.; Sadki, Mustapha; Lea, R. M.

    2002-03-01

    Non-intrusive inspection and non-destructive testing of manufactured objects with complex internal structures typically requires the enhancement, analysis and visualization of high-resolution volumetric data. Given the increasing availability of fast 3D scanning technology (e.g. cone-beam CT), enabling on-line detection and accurate discrimination of components or sub-structures, the inherent complexity of classification algorithms inevitably leads to throughput bottlenecks. Indeed, whereas typical inspection throughput requirements range from 1 to 1000 volumes per hour, depending on density and resolution, current computational capability is one to two orders-of-magnitude less. Accordingly, speeding up classification algorithms requires both reduction of algorithm complexity and acceleration of computer performance. A shape-based classification algorithm, offering algorithm complexity reduction, by using ellipses as generic descriptors of solids-of-revolution, and supporting performance-scalability, by exploiting the inherent parallelism of volumetric data, is presented. A two-stage variant of the classical Hough transform is used for ellipse detection and correlation of the detected ellipses facilitates position-, scale- and orientation-invariant component classification. Performance-scalability is achieved cost-effectively by accelerating a PC host with one or more COTS (Commercial-Off-The-Shelf) PCI multiprocessor cards. Experimental results are reported to demonstrate the feasibility and cost-effectiveness of the data-parallel classification algorithm for on-line industrial inspection applications.

  15. Scalable Predictive Analysis in Critically Ill Patients Using a Visual Open Data Analysis Platform.

    Directory of Open Access Journals (Sweden)

    Sven Van Poucke

    Full Text Available With the accumulation of large amounts of health related data, predictive analytics could stimulate the transformation of reactive medicine towards Predictive, Preventive and Personalized (PPPM Medicine, ultimately affecting both cost and quality of care. However, high-dimensionality and high-complexity of the data involved, prevents data-driven methods from easy translation into clinically relevant models. Additionally, the application of cutting edge predictive methods and data manipulation require substantial programming skills, limiting its direct exploitation by medical domain experts. This leaves a gap between potential and actual data usage. In this study, the authors address this problem by focusing on open, visual environments, suited to be applied by the medical community. Moreover, we review code free applications of big data technologies. As a showcase, a framework was developed for the meaningful use of data from critical care patients by integrating the MIMIC-II database in a data mining environment (RapidMiner supporting scalable predictive analytics using visual tools (RapidMiner's Radoop extension. Guided by the CRoss-Industry Standard Process for Data Mining (CRISP-DM, the ETL process (Extract, Transform, Load was initiated by retrieving data from the MIMIC-II tables of interest. As use case, correlation of platelet count and ICU survival was quantitatively assessed. Using visual tools for ETL on Hadoop and predictive modeling in RapidMiner, we developed robust processes for automatic building, parameter optimization and evaluation of various predictive models, under different feature selection schemes. Because these processes can be easily adopted in other projects, this environment is attractive for scalable predictive analytics in health research.

  16. Scalable Predictive Analysis in Critically Ill Patients Using a Visual Open Data Analysis Platform.

    Science.gov (United States)

    Van Poucke, Sven; Zhang, Zhongheng; Schmitz, Martin; Vukicevic, Milan; Laenen, Margot Vander; Celi, Leo Anthony; De Deyne, Cathy

    2016-01-01

    With the accumulation of large amounts of health related data, predictive analytics could stimulate the transformation of reactive medicine towards Predictive, Preventive and Personalized (PPPM) Medicine, ultimately affecting both cost and quality of care. However, high-dimensionality and high-complexity of the data involved, prevents data-driven methods from easy translation into clinically relevant models. Additionally, the application of cutting edge predictive methods and data manipulation require substantial programming skills, limiting its direct exploitation by medical domain experts. This leaves a gap between potential and actual data usage. In this study, the authors address this problem by focusing on open, visual environments, suited to be applied by the medical community. Moreover, we review code free applications of big data technologies. As a showcase, a framework was developed for the meaningful use of data from critical care patients by integrating the MIMIC-II database in a data mining environment (RapidMiner) supporting scalable predictive analytics using visual tools (RapidMiner's Radoop extension). Guided by the CRoss-Industry Standard Process for Data Mining (CRISP-DM), the ETL process (Extract, Transform, Load) was initiated by retrieving data from the MIMIC-II tables of interest. As use case, correlation of platelet count and ICU survival was quantitatively assessed. Using visual tools for ETL on Hadoop and predictive modeling in RapidMiner, we developed robust processes for automatic building, parameter optimization and evaluation of various predictive models, under different feature selection schemes. Because these processes can be easily adopted in other projects, this environment is attractive for scalable predictive analytics in health research.

  17. Development of the GEM-TPC X-ray Polarimeter with the Scalable Readout System

    Directory of Open Access Journals (Sweden)

    Kitaguchi Takao

    2018-01-01

    Full Text Available We have developed a gaseous Time Projection Chamber (TPC containing a single-layered foil of a gas electron multiplier (GEM to open up a new window on cosmic X-ray polarimetry in the 2–10 keV band. The micro-pattern TPC polarimeter in combination with the Scalable Readout System produced by the RD51 collaboration has been built as an engineering model to optimize detector parameters and improve polarimeter sensitivity. The polarimeter was characterized with unpolarized X-rays from an X-ray generator in a laboratory and polarized X-rays on the BL32B2 beamline at the SPring-8 synchrotron radiation facility. Preliminary results show that the polarimeter has a comparable modulation factor to a prototype of the flight one.

  18. Frontier: High Performance Database Access Using Standard Web Components in a Scalable Multi-Tier Architecture

    International Nuclear Information System (INIS)

    Kosyakov, S.; Kowalkowski, J.; Litvintsev, D.; Lueking, L.; Paterno, M.; White, S.P.; Autio, Lauri; Blumenfeld, B.; Maksimovic, P.; Mathis, M.

    2004-01-01

    A high performance system has been assembled using standard web components to deliver database information to a large number of broadly distributed clients. The CDF Experiment at Fermilab is establishing processing centers around the world imposing a high demand on their database repository. For delivering read-only data, such as calibrations, trigger information, and run conditions data, we have abstracted the interface that clients use to retrieve data objects. A middle tier is deployed that translates client requests into database specific queries and returns the data to the client as XML datagrams. The database connection management, request translation, and data encoding are accomplished in servlets running under Tomcat. Squid Proxy caching layers are deployed near the Tomcat servers, as well as close to the clients, to significantly reduce the load on the database and provide a scalable deployment model. Details the system's construction and use are presented, including its architecture, design, interfaces, administration, performance measurements, and deployment plan

  19. Scalable High Performance Message Passing over InfiniBand for Open MPI

    Energy Technology Data Exchange (ETDEWEB)

    Friedley, A; Hoefler, T; Leininger, M L; Lumsdaine, A

    2007-10-24

    InfiniBand (IB) is a popular network technology for modern high-performance computing systems. MPI implementations traditionally support IB using a reliable, connection-oriented (RC) transport. However, per-process resource usage that grows linearly with the number of processes, makes this approach prohibitive for large-scale systems. IB provides an alternative in the form of a connectionless unreliable datagram transport (UD), which allows for near-constant resource usage and initialization overhead as the process count increases. This paper describes a UD-based implementation for IB in Open MPI as a scalable alternative to existing RC-based schemes. We use the software reliability capabilities of Open MPI to provide the guaranteed delivery semantics required by MPI. Results show that UD not only requires fewer resources at scale, but also allows for shorter MPI startup times. A connectionless model also improves performance for applications that tend to send small messages to many different processes.

  20. On-chip, photon-number-resolving, telecommunication-band detectors for scalable photonic information processing

    Energy Technology Data Exchange (ETDEWEB)

    Gerrits, Thomas; Lita, Adriana E.; Calkins, Brice; Tomlin, Nathan A.; Fox, Anna E.; Linares, Antia Lamas; Mirin, Richard P.; Nam, Sae Woo [National Institute of Standards and Technology, Boulder, Colorado, 80305 (United States); Thomas-Peter, Nicholas; Metcalf, Benjamin J.; Spring, Justin B.; Langford, Nathan K.; Walmsley, Ian A. [Clarendon Laboratory, University of Oxford, Parks Road, Oxford OX1 3PU (United Kingdom); Gates, James C.; Smith, Peter G. R. [Optoelectronics Research Centre, University of Southampton, Highfield SO17 1BJ (United Kingdom)

    2011-12-15

    Integration is currently the only feasible route toward scalable photonic quantum processing devices that are sufficiently complex to be genuinely useful in computing, metrology, and simulation. Embedded on-chip detection will be critical to such devices. We demonstrate an integrated photon-number-resolving detector, operating in the telecom band at 1550 nm, employing an evanescently coupled design that allows it to be placed at arbitrary locations within a planar circuit. Up to five photons are resolved in the guided optical mode via absorption from the evanescent field into a tungsten transition-edge sensor. The detection efficiency is 7.2{+-}0.5 %. The polarization sensitivity of the detector is also demonstrated. Detailed modeling of device designs shows a clear and feasible route to reaching high detection efficiencies.

  1. Scalable Quantum Information Transfer between Individual Nitrogen-Vacancy Centers by a Hybrid Quantum Interface

    International Nuclear Information System (INIS)

    Pei Pei; He-Fei Huang; Yan-Qing Guo; He-Shan Song

    2016-01-01

    We develop a design of a hybrid quantum interface for quantum information transfer (QIT), adopting a nanomechanical resonator as the intermedium, which is magnetically coupled with individual nitrogen-vacancy centers as the solid qubits, while capacitively coupled with a coplanar waveguide resonator as the quantum data bus. We describe the Hamiltonian of the model, and analytically demonstrate the QIT for both the resonant interaction and large detuning cases. The hybrid quantum interface allows for QIT between arbitrarily selected individual nitrogen-vacancy centers, and has advantages of the scalability and controllability. Our methods open an alternative perspective for implementing QIT, which is important during quantum storing or processing procedures in quantum computing. (paper)

  2. Scalable graphene production: perspectives and challenges of plasma applications

    Science.gov (United States)

    Levchenko, Igor; Ostrikov, Kostya (Ken); Zheng, Jie; Li, Xingguo; Keidar, Michael; B. K. Teo, Kenneth

    2016-05-01

    Graphene, a newly discovered and extensively investigated material, has many unique and extraordinary properties which promise major technological advances in fields ranging from electronics to mechanical engineering and food production. Unfortunately, complex techniques and high production costs hinder commonplace applications. Scaling of existing graphene production techniques to the industrial level without compromising its properties is a current challenge. This article focuses on the perspectives and challenges of scalability, equipment, and technological perspectives of the plasma-based techniques which offer many unique possibilities for the synthesis of graphene and graphene-containing products. The plasma-based processes are amenable for scaling and could also be useful to enhance the controllability of the conventional chemical vapour deposition method and some other techniques, and to ensure a good quality of the produced graphene. We examine the unique features of the plasma-enhanced graphene production approaches, including the techniques based on inductively-coupled and arc discharges, in the context of their potential scaling to mass production following the generic scaling approaches applicable to the existing processes and systems. This work analyses a large amount of the recent literature on graphene production by various techniques and summarizes the results in a tabular form to provide a simple and convenient comparison of several available techniques. Our analysis reveals a significant potential of scalability for plasma-based technologies, based on the scaling-related process characteristics. Among other processes, a greater yield of 1 g × h-1 m-2 was reached for the arc discharge technology, whereas the other plasma-based techniques show process yields comparable to the neutral-gas based methods. Selected plasma-based techniques show lower energy consumption than in thermal CVD processes, and the ability to produce graphene flakes of various

  3. Towards scalable quantum communication and computation: Novel approaches and realizations

    Science.gov (United States)

    Jiang, Liang

    Quantum information science involves exploration of fundamental laws of quantum mechanics for information processing tasks. This thesis presents several new approaches towards scalable quantum information processing. First, we consider a hybrid approach to scalable quantum computation, based on an optically connected network of few-qubit quantum registers. Specifically, we develop a novel scheme for scalable quantum computation that is robust against various imperfections. To justify that nitrogen-vacancy (NV) color centers in diamond can be a promising realization of the few-qubit quantum register, we show how to isolate a few proximal nuclear spins from the rest of the environment and use them for the quantum register. We also demonstrate experimentally that the nuclear spin coherence is only weakly perturbed under optical illumination, which allows us to implement quantum logical operations that use the nuclear spins to assist the repetitive-readout of the electronic spin. Using this technique, we demonstrate more than two-fold improvement in signal-to-noise ratio. Apart from direct application to enhance the sensitivity of the NV-based nano-magnetometer, this experiment represents an important step towards the realization of robust quantum information processors using electronic and nuclear spin qubits. We then study realizations of quantum repeaters for long distance quantum communication. Specifically, we develop an efficient scheme for quantum repeaters based on atomic ensembles. We use dynamic programming to optimize various quantum repeater protocols. In addition, we propose a new protocol of quantum repeater with encoding, which efficiently uses local resources (about 100 qubits) to identify and correct errors, to achieve fast one-way quantum communication over long distances. Finally, we explore quantum systems with topological order. Such systems can exhibit remarkable phenomena such as quasiparticles with anyonic statistics and have been proposed as

  4. Scalable graphene production: perspectives and challenges of plasma applications.

    Science.gov (United States)

    Levchenko, Igor; Ostrikov, Kostya Ken; Zheng, Jie; Li, Xingguo; Keidar, Michael; B K Teo, Kenneth

    2016-05-19

    Graphene, a newly discovered and extensively investigated material, has many unique and extraordinary properties which promise major technological advances in fields ranging from electronics to mechanical engineering and food production. Unfortunately, complex techniques and high production costs hinder commonplace applications. Scaling of existing graphene production techniques to the industrial level without compromising its properties is a current challenge. This article focuses on the perspectives and challenges of scalability, equipment, and technological perspectives of the plasma-based techniques which offer many unique possibilities for the synthesis of graphene and graphene-containing products. The plasma-based processes are amenable for scaling and could also be useful to enhance the controllability of the conventional chemical vapour deposition method and some other techniques, and to ensure a good quality of the produced graphene. We examine the unique features of the plasma-enhanced graphene production approaches, including the techniques based on inductively-coupled and arc discharges, in the context of their potential scaling to mass production following the generic scaling approaches applicable to the existing processes and systems. This work analyses a large amount of the recent literature on graphene production by various techniques and summarizes the results in a tabular form to provide a simple and convenient comparison of several available techniques. Our analysis reveals a significant potential of scalability for plasma-based technologies, based on the scaling-related process characteristics. Among other processes, a greater yield of 1 g × h(-1) m(-2) was reached for the arc discharge technology, whereas the other plasma-based techniques show process yields comparable to the neutral-gas based methods. Selected plasma-based techniques show lower energy consumption than in thermal CVD processes, and the ability to produce graphene flakes of

  5. BAMSI: a multi-cloud service for scalable distributed filtering of massive genome data.

    Science.gov (United States)

    Ausmees, Kristiina; John, Aji; Toor, Salman Z; Hellander, Andreas; Nettelblad, Carl

    2018-06-26

    The advent of next-generation sequencing (NGS) has made whole-genome sequencing of cohorts of individuals a reality. Primary datasets of raw or aligned reads of this sort can get very large. For scientific questions where curated called variants are not sufficient, the sheer size of the datasets makes analysis prohibitively expensive. In order to make re-analysis of such data feasible without the need to have access to a large-scale computing facility, we have developed a highly scalable, storage-agnostic framework, an associated API and an easy-to-use web user interface to execute custom filters on large genomic datasets. We present BAMSI, a Software as-a Service (SaaS) solution for filtering of the 1000 Genomes phase 3 set of aligned reads, with the possibility of extension and customization to other sets of files. Unique to our solution is the capability of simultaneously utilizing many different mirrors of the data to increase the speed of the analysis. In particular, if the data is available in private or public clouds - an increasingly common scenario for both academic and commercial cloud providers - our framework allows for seamless deployment of filtering workers close to data. We show results indicating that such a setup improves the horizontal scalability of the system, and present a possible use case of the framework by performing an analysis of structural variation in the 1000 Genomes data set. BAMSI constitutes a framework for efficient filtering of large genomic data sets that is flexible in the use of compute as well as storage resources. The data resulting from the filter is assumed to be greatly reduced in size, and can easily be downloaded or routed into e.g. a Hadoop cluster for subsequent interactive analysis using Hive, Spark or similar tools. In this respect, our framework also suggests a general model for making very large datasets of high scientific value more accessible by offering the possibility for organizations to share the cost of

  6. A Scalable Framework to Detect Personal Health Mentions on Twitter.

    Science.gov (United States)

    Yin, Zhijun; Fabbri, Daniel; Rosenbloom, S Trent; Malin, Bradley

    2015-06-05

    Biomedical research has traditionally been conducted via surveys and the analysis of medical records. However, these resources are limited in their content, such that non-traditional domains (eg, online forums and social media) have an opportunity to supplement the view of an individual's health. The objective of this study was to develop a scalable framework to detect personal health status mentions on Twitter and assess the extent to which such information is disclosed. We collected more than 250 million tweets via the Twitter streaming API over a 2-month period in 2014. The corpus was filtered down to approximately 250,000 tweets, stratified across 34 high-impact health issues, based on guidance from the Medical Expenditure Panel Survey. We created a labeled corpus of several thousand tweets via a survey, administered over Amazon Mechanical Turk, that documents when terms correspond to mentions of personal health issues or an alternative (eg, a metaphor). We engineered a scalable classifier for personal health mentions via feature selection and assessed its potential over the health issues. We further investigated the utility of the tweets by determining the extent to which Twitter users disclose personal health status. Our investigation yielded several notable findings. First, we find that tweets from a small subset of the health issues can train a scalable classifier to detect health mentions. Specifically, training on 2000 tweets from four health issues (cancer, depression, hypertension, and leukemia) yielded a classifier with precision of 0.77 on all 34 health issues. Second, Twitter users disclosed personal health status for all health issues. Notably, personal health status was disclosed over 50% of the time for 11 out of 34 (33%) investigated health issues. Third, the disclosure rate was dependent on the health issue in a statistically significant manner (P<.001). For instance, more than 80% of the tweets about migraines (83/100) and allergies (85

  7. Scalable quantum information processing with atomic ensembles and flying photons

    International Nuclear Information System (INIS)

    Mei Feng; Yu Yafei; Feng Mang; Zhang Zhiming

    2009-01-01

    We present a scheme for scalable quantum information processing with atomic ensembles and flying photons. Using the Rydberg blockade, we encode the qubits in the collective atomic states, which could be manipulated fast and easily due to the enhanced interaction in comparison to the single-atom case. We demonstrate that our proposed gating could be applied to generation of two-dimensional cluster states for measurement-based quantum computation. Moreover, the atomic ensembles also function as quantum repeaters useful for long-distance quantum state transfer. We show the possibility of our scheme to work in bad cavity or in weak coupling regime, which could much relax the experimental requirement. The efficient coherent operations on the ensemble qubits enable our scheme to be switchable between quantum computation and quantum communication using atomic ensembles.

  8. Final Report. Center for Scalable Application Development Software

    Energy Technology Data Exchange (ETDEWEB)

    Mellor-Crummey, John [Rice Univ., Houston, TX (United States)

    2014-10-26

    The Center for Scalable Application Development Software (CScADS) was established as a part- nership between Rice University, Argonne National Laboratory, University of California Berkeley, University of Tennessee – Knoxville, and University of Wisconsin – Madison. CScADS pursued an integrated set of activities with the aim of increasing the productivity of DOE computational scientists by catalyzing the development of systems software, libraries, compilers, and tools for leadership computing platforms. Principal Center activities were workshops to engage the research community in the challenges of leadership computing, research and development of open-source software, and work with computational scientists to help them develop codes for leadership computing platforms. This final report summarizes CScADS activities at Rice University in these areas.

  9. Scalable Task Assignment for Heterogeneous Multi-Robot Teams

    Directory of Open Access Journals (Sweden)

    Paula García

    2013-02-01

    Full Text Available This work deals with the development of a dynamic task assignment strategy for heterogeneous multi-robot teams in typical real world scenarios. The strategy must be efficiently scalable to support problems of increasing complexity with minimum designer intervention. To this end, we have selected a very simple auction-based strategy, which has been implemented and analysed in a multi-robot cleaning problem that requires strong coordination and dynamic complex subtask organization. We will show that the selection of a simple auction strategy provides a linear computational cost increase with the number of robots that make up the team and allows the solving of highly complex assignment problems in dynamic conditions by means of a hierarchical sub-auction policy. To coordinate and control the team, a layered behaviour-based architecture has been applied that allows the reusing of the auction-based strategy to achieve different coordination levels.

  10. A Practical and Scalable Tool to Find Overlaps between Sequences

    Directory of Open Access Journals (Sweden)

    Maan Haj Rachid

    2015-01-01

    Full Text Available The evolution of the next generation sequencing technology increases the demand for efficient solutions, in terms of space and time, for several bioinformatics problems. This paper presents a practical and easy-to-implement solution for one of these problems, namely, the all-pairs suffix-prefix problem, using a compact prefix tree. The paper demonstrates an efficient construction of this time-efficient and space-economical tree data structure. The paper presents techniques for parallel implementations of the proposed solution. Experimental evaluation indicates superior results in terms of space and time over existing solutions. Results also show that the proposed technique is highly scalable in a parallel execution environment.

  11. A Software and Hardware IPTV Architecture for Scalable DVB Distribution

    Directory of Open Access Journals (Sweden)

    Georg Acher

    2009-01-01

    Full Text Available Many standards and even more proprietary technologies deal with IP-based television (IPTV. But none of them can transparently map popular public broadcast services such as DVB or ATSC to IPTV with acceptable effort. In this paper we explain why we believe that such a mapping using a light weight framework is an important step towards all-IP multimedia. We then present the NetCeiver architecture: it is based on well-known standards such as IPv6, and it allows zero configuration. The use of multicast streaming makes NetCeiver highly scalable. We also describe a low cost FPGA implementation of the proposed NetCeiver architecture, which can concurrently stream services from up to six full transponders.

  12. Smartphone based scalable reverse engineering by digital image correlation

    Science.gov (United States)

    Vidvans, Amey; Basu, Saurabh

    2018-03-01

    There is a need for scalable open source 3D reconstruction systems for reverse engineering. This is because most commercially available reconstruction systems are capital and resource intensive. To address this, a novel reconstruction technique is proposed. The technique involves digital image correlation based characterization of surface speeds followed by normalization with respect to angular speed during rigid body rotational motion of the specimen. Proof of concept of the same is demonstrated and validated using simulation and empirical characterization. Towards this, smart-phone imaging and inexpensive off the shelf components along with those fabricated additively using poly-lactic acid polymer with a standard 3D printer are used. Some sources of error in this reconstruction methodology are discussed. It is seen that high curvatures on the surface suppress accuracy of reconstruction. Reasons behind this are delineated in the nature of the correlation function. Theoretically achievable resolution during smart-phone based 3D reconstruction by digital image correlation is derived.

  13. Optimization of Hierarchical Modulation for Use of Scalable Media

    Directory of Open Access Journals (Sweden)

    Heneghan Conor

    2010-01-01

    Full Text Available This paper studies the Hierarchical Modulation, a transmission strategy of the approaching scalable multimedia over frequency-selective fading channel for improving the perceptible quality. An optimization strategy for Hierarchical Modulation and convolutional encoding, which can achieve the target bit error rates with minimum global signal-to-noise ratio in a single-user scenario, is suggested. This strategy allows applications to make a free choice of relationship between Higher Priority (HP and Lower Priority (LP stream delivery. The similar optimization can be used in multiuser scenario. An image transport task and a transport task of an H.264/MPEG4 AVC video embedding both QVGA and VGA resolutions are simulated as the implementation example of this optimization strategy, and demonstrate savings in SNR and improvement in Peak Signal-to-Noise Ratio (PSNR for the particular examples shown.

  14. A Scalable Policy and SNMP Based Network Management Framework

    Institute of Scientific and Technical Information of China (English)

    LIU Su-ping; DING Yong-sheng

    2009-01-01

    Traditional SNMP-based network management can not deal with the task of managing large-scaled distributed network,while policy-based management is one of the effective solutions in network and distributed systems management. However,cross-vendor hardware compatibility is one of the limitations in policy-based management. Devices existing in current network mostly support SNMP rather than Common Open Policy Service (COPS) protocol. By analyzing traditional network management and policy-based network management, a scalable network management framework is proposed. It is combined with Internet Engineering Task Force (IETF) framework for policybased management and SNMP-based network management. By interpreting and translating policy decision to SNMP message,policy can be executed in traditional SNMP-based device.

  15. MOSDEN: A Scalable Mobile Collaborative Platform for Opportunistic Sensing Applications

    Directory of Open Access Journals (Sweden)

    Prem Prakash Jayaraman

    2014-05-01

    Full Text Available Mobile smartphones along with embedded sensors have become an efficient enabler for various mobile applications including opportunistic sensing. The hi-tech advances in smartphones are opening up a world of possibilities. This paper proposes a mobile collaborative platform called MOSDEN that enables and supports opportunistic sensing at run time. MOSDEN captures and shares sensor data acrossmultiple apps, smartphones and users. MOSDEN supports the emerging trend of separating sensors from application-specific processing, storing and sharing. MOSDEN promotes reuse and re-purposing of sensor data hence reducing the efforts in developing novel opportunistic sensing applications. MOSDEN has been implemented on Android-based smartphones and tablets. Experimental evaluations validate the scalability and energy efficiency of MOSDEN and its suitability towards real world applications. The results of evaluation and lessons learned are presented and discussed in this paper.

  16. Photonic Architecture for Scalable Quantum Information Processing in Diamond

    Directory of Open Access Journals (Sweden)

    Kae Nemoto

    2014-08-01

    Full Text Available Physics and information are intimately connected, and the ultimate information processing devices will be those that harness the principles of quantum mechanics. Many physical systems have been identified as candidates for quantum information processing, but none of them are immune from errors. The challenge remains to find a path from the experiments of today to a reliable and scalable quantum computer. Here, we develop an architecture based on a simple module comprising an optical cavity containing a single negatively charged nitrogen vacancy center in diamond. Modules are connected by photons propagating in a fiber-optical network and collectively used to generate a topological cluster state, a robust substrate for quantum information processing. In principle, all processes in the architecture can be deterministic, but current limitations lead to processes that are probabilistic but heralded. We find that the architecture enables large-scale quantum information processing with existing technology.

  17. Neuromorphic adaptive plastic scalable electronics: analog learning systems.

    Science.gov (United States)

    Srinivasa, Narayan; Cruz-Albrecht, Jose

    2012-01-01

    Decades of research to build programmable intelligent machines have demonstrated limited utility in complex, real-world environments. Comparing their performance with biological systems, these machines are less efficient by a factor of 1 million1 billion in complex, real-world environments. The Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE) program is a multifaceted Defense Advanced Research Projects Agency (DARPA) project that seeks to break the programmable machine paradigm and define a new path for creating useful, intelligent machines. Since real-world systems exhibit infinite combinatorial complexity, electronic neuromorphic machine technology would be preferable in a host of applications, but useful and practical implementations still do not exist. HRL Laboratories LLC has embarked on addressing these challenges, and, in this article, we provide an overview of our project and progress made thus far.

  18. Implementation of the Timepix ASIC in the Scalable Readout System

    Energy Technology Data Exchange (ETDEWEB)

    Lupberger, M., E-mail: lupberger@physik.uni-bonn.de; Desch, K.; Kaminski, J.

    2016-09-11

    We report on the development of electronics hardware, FPGA firmware and software to provide a flexible multi-chip readout of the Timepix ASIC within the framework of the Scalable Readout System (SRS). The system features FPGA-based zero-suppression and the possibility to read out up to 4×8 chips with a single Front End Concentrator (FEC). By operating several FECs in parallel, in principle an arbitrary number of chips can be read out, exploiting the scaling features of SRS. Specifically, we tested the system with a setup consisting of 160 Timepix ASICs, operated as GridPix devices in a large TPC field cage in a 1 T magnetic field at a DESY test beam facility providing an electron beam of up to 6 GeV. We discuss the design choices, the dedicated hardware components, the FPGA firmware as well as the performance of the system in the test beam.

  19. Scalable Domain Decomposition Preconditioners for Heterogeneous Elliptic Problems

    Directory of Open Access Journals (Sweden)

    Pierre Jolivet

    2014-01-01

    Full Text Available Domain decomposition methods are, alongside multigrid methods, one of the dominant paradigms in contemporary large-scale partial differential equation simulation. In this paper, a lightweight implementation of a theoretically and numerically scalable preconditioner is presented in the context of overlapping methods. The performance of this work is assessed by numerical simulations executed on thousands of cores, for solving various highly heterogeneous elliptic problems in both 2D and 3D with billions of degrees of freedom. Such problems arise in computational science and engineering, in solid and fluid mechanics. While focusing on overlapping domain decomposition methods might seem too restrictive, it will be shown how this work can be applied to a variety of other methods, such as non-overlapping methods and abstract deflation based preconditioners. It is also presented how multilevel preconditioners can be used to avoid communication during an iterative process such as a Krylov method.

  20. A Secure and Scalable Data Communication Scheme in Smart Grids

    Directory of Open Access Journals (Sweden)

    Chunqiang Hu

    2018-01-01

    Full Text Available The concept of smart grid gained tremendous attention among researchers and utility providers in recent years. How to establish a secure communication among smart meters, utility companies, and the service providers is a challenging issue. In this paper, we present a communication architecture for smart grids and propose a scheme to guarantee the security and privacy of data communications among smart meters, utility companies, and data repositories by employing decentralized attribute based encryption. The architecture is highly scalable, which employs an access control Linear Secret Sharing Scheme (LSSS matrix to achieve a role-based access control. The security analysis demonstrated that the scheme ensures security and privacy. The performance analysis shows that the scheme is efficient in terms of computational cost.

  1. A scalable implementation of RI-SCF on parallel computers

    International Nuclear Information System (INIS)

    Fruechtl, H.A.; Kendall, R.A.; Harrison, R.J.

    1996-01-01

    In order to avoid the integral bottleneck of conventional SCF calculations, the Resolution of the Identity (RI) method is used to obtain an approximate solution to the Hartree-Fock equations. In this approximation only three-center integrals are needed to build the Fock matrix. It has been implemented as part of the NWChem package of portable and scalable ab initio programs for parallel computers. Utilizing the V-approximation, both the Coulomb and exchange contribution to the Fock matrix can be calculated from a transformed set of three-center integrals which have to be precalculated and stored. A distributed in-core method as well as a disk based implementation have been programmed. Details of the implementation as well as the parallel programming tools used are described. We also give results and timings from benchmark calculations

  2. Scalable Lunar Surface Networks and Adaptive Orbit Access

    Science.gov (United States)

    Wang, Xudong

    2015-01-01

    Teranovi Technologies, Inc., has developed innovative network architecture, protocols, and algorithms for both lunar surface and orbit access networks. A key component of the overall architecture is a medium access control (MAC) protocol that includes a novel mechanism of overlaying time division multiple access (TDMA) and carrier sense multiple access with collision avoidance (CSMA/CA), ensuring scalable throughput and quality of service. The new MAC protocol is compatible with legacy Institute of Electrical and Electronics Engineers (IEEE) 802.11 networks. Advanced features include efficiency power management, adaptive channel width adjustment, and error control capability. A hybrid routing protocol combines the advantages of ad hoc on-demand distance vector (AODV) routing and disruption/delay-tolerant network (DTN) routing. Performance is significantly better than AODV or DTN and will be particularly effective for wireless networks with intermittent links, such as lunar and planetary surface networks and orbit access networks.

  3. Scalable Creation of Long-Lived Multipartite Entanglement

    Science.gov (United States)

    Kaufmann, H.; Ruster, T.; Schmiegelow, C. T.; Luda, M. A.; Kaushal, V.; Schulz, J.; von Lindenfels, D.; Schmidt-Kaler, F.; Poschinger, U. G.

    2017-10-01

    We demonstrate the deterministic generation of multipartite entanglement based on scalable methods. Four qubits are encoded in 40Ca+, stored in a microstructured segmented Paul trap. These qubits are sequentially entangled by laser-driven pairwise gate operations. Between these, the qubit register is dynamically reconfigured via ion shuttling operations, where ion crystals are separated and merged, and ions are moved in and out of a fixed laser interaction zone. A sequence consisting of three pairwise entangling gates yields a four-ion Greenberger-Horne-Zeilinger state |ψ ⟩=(1 /√{2 })(|0000 ⟩+|1111 ⟩) , and full quantum state tomography reveals a state fidelity of 94.4(3)%. We analyze the decoherence of this state and employ dynamic decoupling on the spatially distributed constituents to maintain 69(5)% coherence at a storage time of 1.1 sec.

  4. Extending JPEG-LS for low-complexity scalable video coding

    DEFF Research Database (Denmark)

    Ukhanova, Anna; Sergeev, Anton; Forchhammer, Søren

    2011-01-01

    JPEG-LS, the well-known international standard for lossless and near-lossless image compression, was originally designed for non-scalable applications. In this paper we propose a scalable modification of JPEG-LS and compare it with the leading image and video coding standards JPEG2000 and H.264/SVC...

  5. CloudTPS: Scalable Transactions for Web Applications in the Cloud

    NARCIS (Netherlands)

    Zhou, W.; Pierre, G.E.O.; Chi, C.-H.

    2010-01-01

    NoSQL Cloud data services provide scalability and high availability properties for web applications but at the same time they sacrifice data consistency. However, many applications cannot afford any data inconsistency. CloudTPS is a scalable transaction manager to allow cloud database services to

  6. Scalable Integrated Region-Based Image Retrieval Using IRM and Statistical Clustering.

    Science.gov (United States)

    Wang, James Z.; Du, Yanping

    Statistical clustering is critical in designing scalable image retrieval systems. This paper presents a scalable algorithm for indexing and retrieving images based on region segmentation. The method uses statistical clustering on region features and IRM (Integrated Region Matching), a measure developed to evaluate overall similarity between images…

  7. Building a scalable event-level metadata service for ATLAS

    International Nuclear Information System (INIS)

    Cranshaw, J; Malon, D; Goosens, L; Viegas, F T A; McGlone, H

    2008-01-01

    The ATLAS TAG Database is a multi-terabyte event-level metadata selection system, intended to allow discovery, selection of and navigation to events of interest to an analysis. The TAG Database encompasses file- and relational-database-resident event-level metadata, distributed across all ATLAS Tiers. An oracle hosted global TAG relational database, containing all ATLAS events, implemented in Oracle, will exist at Tier O. Implementing a system that is both performant and manageable at this scale is a challenge. A 1 TB relational TAG Database has been deployed at Tier 0 using simulated tag data. The database contains one billion events, each described by two hundred event metadata attributes, and is currently undergoing extensive testing in terms of queries, population and manageability. These 1 TB tests aim to demonstrate and optimise the performance and scalability of an Oracle TAG Database on a global scale. Partitioning and indexing strategies are crucial to well-performing queries and manageability of the database and have implications for database population and distribution, so these are investigated. Physics query patterns are anticipated, but a crucial feature of the system must be to support a broad range of queries across all attributes. Concurrently, event tags from ATLAS Computing System Commissioning distributed simulations are accumulated in an Oracle-hosted database at CERN, providing an event-level selection service valuable for user experience and gathering information about physics query patterns. In this paper we describe the status of the Global TAG relational database scalability work and highlight areas of future direction

  8. A lightweight scalable agarose-gel-synthesized thermoelectric composite

    Science.gov (United States)

    Kim, Jin Ho; Fernandes, Gustavo E.; Lee, Do-Joong; Hirst, Elizabeth S.; Osgood, Richard M., III; Xu, Jimmy

    2018-03-01

    Electronic devices are now advancing beyond classical, rigid systems and moving into lighweight flexible regimes, enabling new applications such as body-wearables and ‘e-textiles’. To support this new electronic platform, composite materials that are highly conductive yet scalable, flexible, and wearable are needed. Materials with high electrical conductivity often have poor thermoelectric properties because their thermal transport is made greater by the same factors as their electronic conductivity. We demonstrate, in proof-of-principle experiments, that a novel binary composite can disrupt thermal (phononic) transport, while maintaining high electrical conductivity, thus yielding promising thermoelectric properties. Highly conductive Multi-Wall Carbon Nanotube (MWCNT) composites are combined with a low-band gap semiconductor, PbS. The work functions of the two materials are closely matched, minimizing the electrical contact resistance within the composite. Disparities in the speed of sound in MWCNTs and PbS help to inhibit phonon propagation, and boundary layer scattering at interfaces between these two materials lead to large Seebeck coefficient (> 150 μV/K) (Mott N F and Davis E A 1971 Electronic Processes in Non-crystalline Materials (Oxford: Clarendon), p 47) and a power factor as high as 10 μW/(K2 m). The overall fabrication process is not only scalable but also conformal and compatible with large-area flexible hosts including metal sheets, films, coatings, possibly arrays of fibers, textiles and fabrics. We explain the behavior of this novel thermoelectric material platform in terms of differing length scales for electrical conductivity and phononic heat transfer, and explore new material configurations for potentially lightweight and flexible thermoelectric devices that could be networked in a textile.

  9. Joint-layer encoder optimization for HEVC scalable extensions

    Science.gov (United States)

    Tsai, Chia-Ming; He, Yuwen; Dong, Jie; Ye, Yan; Xiu, Xiaoyu; He, Yong

    2014-09-01

    Scalable video coding provides an efficient solution to support video playback on heterogeneous devices with various channel conditions in heterogeneous networks. SHVC is the latest scalable video coding standard based on the HEVC standard. To improve enhancement layer coding efficiency, inter-layer prediction including texture and motion information generated from the base layer is used for enhancement layer coding. However, the overall performance of the SHVC reference encoder is not fully optimized because rate-distortion optimization (RDO) processes in the base and enhancement layers are independently considered. It is difficult to directly extend the existing joint-layer optimization methods to SHVC due to the complicated coding tree block splitting decisions and in-loop filtering process (e.g., deblocking and sample adaptive offset (SAO) filtering) in HEVC. To solve those problems, a joint-layer optimization method is proposed by adjusting the quantization parameter (QP) to optimally allocate the bit resource between layers. Furthermore, to make more proper resource allocation, the proposed method also considers the viewing probability of base and enhancement layers according to packet loss rate. Based on the viewing probability, a novel joint-layer RD cost function is proposed for joint-layer RDO encoding. The QP values of those coding tree units (CTUs) belonging to lower layers referenced by higher layers are decreased accordingly, and the QP values of those remaining CTUs are increased to keep total bits unchanged. Finally the QP values with minimal joint-layer RD cost are selected to match the viewing probability. The proposed method was applied to the third temporal level (TL-3) pictures in the Random Access configuration. Simulation results demonstrate that the proposed joint-layer optimization method can improve coding performance by 1.3% for these TL-3 pictures compared to the SHVC reference encoder without joint-layer optimization.

  10. Models, More Models, and Then A Lot More

    OpenAIRE

    Babur, O.; Cleophas, L.; Brand, van den, M.; Tekinerdogan, B.; Aksit, M.

    2017-01-01

    With increased adoption of Model-Driven Engineering, the number of related artefacts in use, such as models, greatly increase. To be able to tackle this dimension of scalability in MDE, we propose to treat the artefacts as data, and applyvarious techniques ranging from information retrieval to machine learning to analyse and manage them in a scalable and efficient way.

  11. A Scalable Gaussian Process Analysis Algorithm for Biomass Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Chandola, Varun [ORNL; Vatsavai, Raju [ORNL

    2011-01-01

    Biomass monitoring is vital for studying the carbon cycle of earth's ecosystem and has several significant implications, especially in the context of understanding climate change and its impacts. Recently, several change detection methods have been proposed to identify land cover changes in temporal profiles (time series) of vegetation collected using remote sensing instruments, but do not satisfy one or both of the two requirements of the biomass monitoring problem, i.e., {\\em operating in online mode} and {\\em handling periodic time series}. In this paper, we adapt Gaussian process regression to detect changes in such time series in an online fashion. While Gaussian process (GP) have been widely used as a kernel based learning method for regression and classification, their applicability to massive spatio-temporal data sets, such as remote sensing data, has been limited owing to the high computational costs involved. We focus on addressing the scalability issues associated with the proposed GP based change detection algorithm. This paper makes several significant contributions. First, we propose a GP based online time series change detection algorithm and demonstrate its effectiveness in detecting different types of changes in {\\em Normalized Difference Vegetation Index} (NDVI) data obtained from a study area in Iowa, USA. Second, we propose an efficient Toeplitz matrix based solution which significantly improves the computational complexity and memory requirements of the proposed GP based method. Specifically, the proposed solution can analyze a time series of length $t$ in $O(t^2)$ time while maintaining a $O(t)$ memory footprint, compared to the $O(t^3)$ time and $O(t^2)$ memory requirement of standard matrix manipulation based methods. Third, we describe a parallel version of the proposed solution which can be used to simultaneously analyze a large number of time series. We study three different parallel implementations: using threads, MPI, and a

  12. Towards Reliable, Scalable, and Energy Efficient Cognitive Radio Systems

    KAUST Repository

    Sboui, Lokman

    2017-11-01

    The cognitive radio (CR) concept is expected to be adopted along with many technologies to meet the requirements of the next generation of wireless and mobile systems, the 5G. Consequently, it is important to determine the performance of the CR systems with respect to these requirements. In this thesis, after briefly describing the 5G requirements, we present three main directions in which we aim to enhance the CR performance. The first direction is the reliability. We study the achievable rate of a multiple-input multiple-output (MIMO) relay-assisted CR under two scenarios; an unmanned aerial vehicle (UAV) one-way relaying (OWR) and a fixed two-way relaying (TWR). We propose special linear precoding schemes that enable the secondary user (SU) to take advantage of the primary-free channel eigenmodes. We study the SU rate sensitivity to the relay power, the relay gain, the UAV altitude, the number of antennas and the line of sight availability. The second direction is the scalability. We first study a multiple access channel (MAC) with multiple SUs scenario. We propose a particular linear precoding and SUs selection scheme maximizing their sum-rate. We show that the proposed scheme provides a significant sum-rate improvement as the number of SUs increases. Secondly, we expand our scalability study to cognitive cellular networks. We propose a low-complexity algorithm for base station activation/deactivation and dynamic spectrum management maximizing the profits of primary and secondary networks subject to green constraints. We show that our proposed algorithms achieve performance close to those obtained with the exhaustive search method. The third direction is the energy efficiency (EE). We present a novel power allocation scheme based on maximizing the EE of both single-input and single-output (SISO) and MIMO systems. We solve a non-convex problem and derive explicit expressions of the corresponding optimal power. When the instantaneous channel is not available, we

  13. High-performance, scalable optical network-on-chip architectures

    Science.gov (United States)

    Tan, Xianfang

    The rapid advance of technology enables a large number of processing cores to be integrated into a single chip which is called a Chip Multiprocessor (CMP) or a Multiprocessor System-on-Chip (MPSoC) design. The on-chip interconnection network, which is the communication infrastructure for these processing cores, plays a central role in a many-core system. With the continuously increasing complexity of many-core systems, traditional metallic wired electronic networks-on-chip (NoC) became a bottleneck because of the unbearable latency in data transmission and extremely high energy consumption on chip. Optical networks-on-chip (ONoC) has been proposed as a promising alternative paradigm for electronic NoC with the benefits of optical signaling communication such as extremely high bandwidth, negligible latency, and low power consumption. This dissertation focus on the design of high-performance and scalable ONoC architectures and the contributions are highlighted as follow: 1. A micro-ring resonator (MRR)-based Generic Wavelength-routed Optical Router (GWOR) is proposed. A method for developing any sized GWOR is introduced. GWOR is a scalable non-blocking ONoC architecture with simple structure, low cost and high power efficiency compared to existing ONoC designs. 2. To expand the bandwidth and improve the fault tolerance of the GWOR, a redundant GWOR architecture is designed by cascading different type of GWORs into one network. 3. The redundant GWOR built with MRR-based comb switches is proposed. Comb switches can expand the bandwidth while keep the topology of GWOR unchanged by replacing the general MRRs with comb switches. 4. A butterfly fat tree (BFT)-based hybrid optoelectronic NoC (HONoC) architecture is developed in which GWORs are used for global communication and electronic routers are used for local communication. The proposed HONoC uses less numbers of electronic routers and links than its counterpart of electronic BFT-based NoC. It takes the advantages of

  14. SINDBAD: a realistic multi-purpose and scalable X-ray simulation tool for NDT applications

    International Nuclear Information System (INIS)

    Tabary, J.; Hugonnard, P.; Mathy, F.

    2007-01-01

    The X-ray radiographic simulation software SINDBAD, has been developed to help the design stage of radiographic systems or to evaluate the efficiency of image processing techniques, in both medical imaging and Non-Destructive Evaluation (NDE) industrial fields. This software can model any radiographic set-up, including the X-ray source, the beam interaction inside the object represented by its Computed Aided Design (CAD) model, and the imaging process in the detector. For each step of the virtual experimental bench, SINDBAD combines different modelling modules, accessed via Graphical User Interfaces (GUI), to provide realistic synthetic images. In this paper, we present an overview of all the functionalities which are available in SINDBAD, with a complete description of all the physics taken into account in models as well as the CAD and GUI facilities available in many computing platforms. We underline the different modules usable for different applications which make SINDBAD a multi-purposed and scalable X-ray simulation tool. (authors)

  15. Study on scalable Coulombic degradation for estimating the lifetime of organic light-emitting devices

    International Nuclear Information System (INIS)

    Zhang Wenwen; Hou Xun; Wu Zhaoxin; Liang Shixiong; Jiao Bo; Zhang Xinwen; Wang Dawei; Chen Zhijian; Gong Qihuang

    2011-01-01

    The luminance decays of organic light-emitting diodes (OLEDs) are investigated with initial luminance of 1000 to 20 000 cd m -2 through a scalable Coulombic degradation and a stretched exponential decay. We found that the estimated lifetime by scalable Coulombic degradation deviates from the experimental results when the OLEDs work with high initial luminance. By measuring the temperature of the device during degradation, we found that the higher device temperatures will lead to instabilities of organic materials in devices, which is expected to result in the difference between the experimental results and estimation using the scalable Coulombic degradation.

  16. A practical multilayered conducting polymer actuator with scalable work output

    International Nuclear Information System (INIS)

    Ikushima, Kimiya; John, Stephen; Yokoyama, Kazuo; Nagamitsu, Sachio

    2009-01-01

    Household assistance robots are expected to become more prominent in the future and will require inherently safe design. Conducting polymer-based artificial muscle actuators are one potential option for achieving this safety, as they are flexible, lightweight and can be driven using low input voltages, unlike electromagnetic motors; however, practical implementation also requires a scalable structure and stability in air. In this paper we propose and practically implement a multilayer conducting polymer actuator which could achieve these targets using polypyrrole film and ionic liquid-soaked separators. The practical work density of a nine-layer multilayer actuator was 1.4 kJ m −3 at 0.5 Hz, when the volumes of the electrolyte and counter electrodes were included, which approaches the performance of mammalian muscle. To achieve air stability, we analyzed the effect of air-stable ionic liquid gels on actuator displacement using finite element simulation and it was found that the majority of strain could be retained when the elastic modulus of the gel was kept below 3 kPa. As a result of this work, we have shown that multilayered conducting polymer actuators are a feasible idea for household robotics, as they provide a substantial practical work density in a compact structure and can be easily scaled as required

  17. Scalable global grid catalogue for Run3 and beyond

    Science.gov (United States)

    Martinez Pedreira, M.; Grigoras, C.; ALICE Collaboration

    2017-10-01

    The AliEn (ALICE Environment) file catalogue is a global unique namespace providing mapping between a UNIX-like logical name structure and the corresponding physical files distributed over 80 storage elements worldwide. Powerful search tools and hierarchical metadata information are integral parts of the system and are used by the Grid jobs as well as local users to store and access all files on the Grid storage elements. The catalogue has been in production since 2005 and over the past 11 years has grown to more than 2 billion logical file names. The backend is a set of distributed relational databases, ensuring smooth growth and fast access. Due to the anticipated fast future growth, we are looking for ways to enhance the performance and scalability by simplifying the catalogue schema while keeping the functionality intact. We investigated different backend solutions, such as distributed key value stores, as replacement for the relational database. This contribution covers the architectural changes in the system, together with the technology evaluation, benchmark results and conclusions.

  18. Scalable bonding of nanofibrous polytetrafluoroethylene (PTFE) membranes on microstructures

    Science.gov (United States)

    Mortazavi, Mehdi; Fazeli, Abdolreza; Moghaddam, Saeed

    2018-01-01

    Expanded polytetrafluoroethylene (ePTFE) nanofibrous membranes exhibit high porosity (80%-90%), high gas permeability, chemical inertness, and superhydrophobicity, which makes them a suitable choice in many demanding fields including industrial filtration, medical implants, bio-/nano- sensors/actuators and microanalysis (i.e. lab-on-a-chip). However, one of the major challenges that inhibit implementation of such membranes is their inability to bond to other materials due to their intrinsic low surface energy and chemical inertness. Prior attempts to improve adhesion of ePTFE membranes to other surfaces involved surface chemical treatments which have not been successful due to degradation of the mechanical integrity and the breakthrough pressure of the membrane. Here, we report a simple and scalable method of bonding ePTFE membranes to different surfaces via the introduction of an intermediate adhesive layer. While a variety of adhesives can be used with this technique, the highest bonding performance is obtained for adhesives that have moderate contact angles with the substrate and low contact angles with the membrane. A thin layer of an adhesive can be uniformly applied onto micro-patterned substrates with feature sizes down to 5 µm using a roll-coating process. Membrane-based microchannel and micropillar devices with burst pressures of up to 200 kPa have been successfully fabricated and tested. A thin layer of the membrane remains attached to the substrate after debonding, suggesting that mechanical interlocking through nanofiber engagement is the main mechanism of adhesion.

  19. SVOPME: A Scalable Virtual Organization Privileges Management Environment

    International Nuclear Information System (INIS)

    Garzoglio, Gabriele; Sfiligoi, Igor; Levshina, Tanya; Wang, Nanbor; Ananthan, Balamurali

    2010-01-01

    Grids enable uniform access to resources by implementing standard interfaces to resource gateways. In the Open Science Grid (OSG), privileges are granted on the basis of the user's membership to a Virtual Organization (VO). However, Grid sites are solely responsible to determine and control access privileges to resources using users' identity and personal attributes, which are available through Grid credentials. While this guarantees full control on access rights to the sites, it makes VO privileges heterogeneous throughout the Grid and hardly fits with the Grid paradigm of uniform access to resources. To address these challenges, we are developing the Scalable Virtual Organization Privileges Management Environment (SVOPME), which provides tools for VOs to define and publish desired privileges and assists sites to provide the appropriate access policies. Moreover, SVOPME provides tools for Grid sites to analyze site access policies for various resources, verify compliance with preferred VO policies, and generate directives for site administrators on how the local access policies can be amended to achieve such compliance without taking control of local configurations away from site administrators. This paper discusses what access policies are of interest to the OSG community and how SVOPME implements privilege management for OSG.

  20. High-performance scalable Information Service for the ATLAS experiment

    CERN Document Server

    Kolos, S; The ATLAS collaboration; Hauser, R

    2012-01-01

    The ATLAS experiment is being operated by highly distributed computing system which is constantly producing a lot of status information which is used to monitor the experiment operational conditions as well as to access the quality of the physics data being taken. For example the ATLAS High Level Trigger(HLT) algorithms are executed on the online computing farm consisting from about 1500 nodes. Each HLT algorithm is producing few thousands histograms, which have to be integrated over the whole farm and carefully analyzed in order to properly tune the event rejection. In order to handle such non-physics data the Information Service (IS) facility has been developed in the scope of the ATLAS TDAQ project. The IS provides high-performance scalable solution for information exchange in distributed environment. In the course of an ATLAS data taking session the IS handles about hundred gigabytes of information which is being constantly updated with the update interval varying from a second to few tens of seconds. IS ...

  1. Scalable and cost-effective NGS genotyping in the cloud.

    Science.gov (United States)

    Souilmi, Yassine; Lancaster, Alex K; Jung, Jae-Yoon; Rizzo, Ettore; Hawkins, Jared B; Powles, Ryan; Amzazi, Saaïd; Ghazal, Hassan; Tonellato, Peter J; Wall, Dennis P

    2015-10-15

    While next-generation sequencing (NGS) costs have plummeted in recent years, cost and complexity of computation remain substantial barriers to the use of NGS in routine clinical care. The clinical potential of NGS will not be realized until robust and routine whole genome sequencing data can be accurately rendered to medically actionable reports within a time window of hours and at scales of economy in the 10's of dollars. We take a step towards addressing this challenge, by using COSMOS, a cloud-enabled workflow management system, to develop GenomeKey, an NGS whole genome analysis workflow. COSMOS implements complex workflows making optimal use of high-performance compute clusters. Here we show that the Amazon Web Service (AWS) implementation of GenomeKey via COSMOS provides a fast, scalable, and cost-effective analysis of both public benchmarking and large-scale heterogeneous clinical NGS datasets. Our systematic benchmarking reveals important new insights and considerations to produce clinical turn-around of whole genome analysis optimization and workflow management including strategic batching of individual genomes and efficient cluster resource configuration.

  2. A Platform for Scalable Satellite and Geospatial Data Analysis

    Science.gov (United States)

    Beneke, C. M.; Skillman, S.; Warren, M. S.; Kelton, T.; Brumby, S. P.; Chartrand, R.; Mathis, M.

    2017-12-01

    At Descartes Labs, we use the commercial cloud to run global-scale machine learning applications over satellite imagery. We have processed over 5 Petabytes of public and commercial satellite imagery, including the full Landsat and Sentinel archives. By combining open-source tools with a FUSE-based filesystem for cloud storage, we have enabled a scalable compute platform that has demonstrated reading over 200 GB/s of satellite imagery into cloud compute nodes. In one application, we generated global 15m Landsat-8, 20m Sentinel-1, and 10m Sentinel-2 composites from 15 trillion pixels, using over 10,000 CPUs. We recently created a public open-source Python client library that can be used to query and access preprocessed public satellite imagery from within our platform, and made this platform available to researchers for non-commercial projects. In this session, we will describe how you can use the Descartes Labs Platform for rapid prototyping and scaling of geospatial analyses and demonstrate examples in land cover classification.

  3. An open, interoperable, and scalable prehospital information technology network architecture.

    Science.gov (United States)

    Landman, Adam B; Rokos, Ivan C; Burns, Kevin; Van Gelder, Carin M; Fisher, Roger M; Dunford, James V; Cone, David C; Bogucki, Sandy

    2011-01-01

    Some of the most intractable challenges in prehospital medicine include response time optimization, inefficiencies at the emergency medical services (EMS)-emergency department (ED) interface, and the ability to correlate field interventions with patient outcomes. Information technology (IT) can address these and other concerns by ensuring that system and patient information is received when and where it is needed, is fully integrated with prior and subsequent patient information, and is securely archived. Some EMS agencies have begun adopting information technologies, such as wireless transmission of 12-lead electrocardiograms, but few agencies have developed a comprehensive plan for management of their prehospital information and integration with other electronic medical records. This perspective article highlights the challenges and limitations of integrating IT elements without a strategic plan, and proposes an open, interoperable, and scalable prehospital information technology (PHIT) architecture. The two core components of this PHIT architecture are 1) routers with broadband network connectivity to share data between ambulance devices and EMS system information services and 2) an electronic patient care report to organize and archive all electronic prehospital data. To successfully implement this comprehensive PHIT architecture, data and technology requirements must be based on best available evidence, and the system must adhere to health data standards as well as privacy and security regulations. Recent federal legislation prioritizing health information technology may position federal agencies to help design and fund PHIT architectures.

  4. Scalable transfer of vertical graphene nanosheets for flexible supercapacitor applications

    Science.gov (United States)

    Sahoo, Gopinath; Ghosh, Subrata; Polaki, S. R.; Mathews, Tom; Kamruddin, M.

    2017-10-01

    Vertical graphene nanosheets (VGN) are the material of choice for application in next-generation electronic devices. The growing demand for VGN-based flexible devices for the electronics industry brings in restriction on VGN growth temperature. The difficulty associated with the direct growth of VGN on flexible substrates can be overcome by adopting an effective strategy of transferring the well-grown VGN onto arbitrary flexible substrates through a soft chemistry route. In the present study, we report an inexpensive and scalable technique for the polymer-free transfer of VGN onto arbitrary substrates without disrupting its morphology, structure, and properties. After transfer, the morphology, chemical structure, and electrical properties are analyzed by scanning electron microscopy, Raman spectroscopy, x-ray photoelectron spectroscopy, and four-probe resistive methods, respectively. The wetting properties are studied from the water contact angle measurements. The observed results indicate the retention of morphology, surface chemistry, structure, and electronic properties. Furthermore, the storage capacity of the transferred VGN-based binder-free and current collector-free flexible symmetric supercapacitor device is studied. A very low sheet resistance of 670 Ω/□ and excellent supercapacitance of 158 μF cm-2 with 86% retention after 10 000 cycles show the prospect of the damage-free VGN transfer approach for the fabrication of flexible nanoelectronic devices.

  5. Nano-islands Based Charge Trapping Memory: A Scalability Study

    KAUST Repository

    Elatab, Nazek; Saadat, Irfan; Saraswat, Krishna; Nayfeh, Ammar

    2017-01-01

    Zinc-oxide (ZnO) and zirconia (ZrO2) metal oxides have been studied extensively in the past few decades with several potential applications including memory devices. In this work, a scalability study, based on the ITRS roadmap, is conducted on memory devices with ZnO and ZrO2 nano-islands charge trapping layer. Both nano-islands are deposited using atomic layer deposition (ALD), however, the different sizes, distribution and properties of the materials result in different memory performance. The results show that at the 32-nm node charge trapping memory with 127 ZrO2 nano-islands can provide a 9.4 V memory window. However, with ZnO only 31 nano-islands can provide a window of 2.5 V. The results indicate that ZrO2 nano-islands are more promising than ZnO in scaled down devices due to their higher density, higher-k, and absence of quantum confinement effects.

  6. Scalable Production of Graphene-Based Wearable E-Textiles.

    Science.gov (United States)

    Karim, Nazmul; Afroj, Shaila; Tan, Sirui; He, Pei; Fernando, Anura; Carr, Chris; Novoselov, Kostya S

    2017-12-26

    Graphene-based wearable e-textiles are considered to be promising due to their advantages over traditional metal-based technology. However, the manufacturing process is complex and currently not suitable for industrial scale application. Here we report a simple, scalable, and cost-effective method of producing graphene-based wearable e-textiles through the chemical reduction of graphene oxide (GO) to make stable reduced graphene oxide (rGO) dispersion which can then be applied to the textile fabric using a simple pad-dry technique. This application method allows the potential manufacture of conductive graphene e-textiles at commercial production rates of ∼150 m/min. The graphene e-textile materials produced are durable and washable with acceptable softness/hand feel. The rGO coating enhanced the tensile strength of cotton fabric and also the flexibility due to the increase in strain% at maximum load. We demonstrate the potential application of these graphene e-textiles for wearable electronics with activity monitoring sensor. This could potentially lead to a multifunctional single graphene e-textile garment that can act both as sensors and flexible heating elements powered by the energy stored in graphene textile supercapacitors.

  7. Scalability Issues for Remote Sensing Infrastructure: A Case Study

    Directory of Open Access Journals (Sweden)

    Yang Liu

    2017-04-01

    Full Text Available For the past decade, a team of University of Calgary researchers has operated a large “sensor Web” to collect, analyze, and share scientific data from remote measurement instruments across northern Canada. This sensor Web receives real-time data streams from over a thousand Internet-connected sensors, with a particular emphasis on environmental data (e.g., space weather, auroral phenomena, atmospheric imaging. Through research collaborations, we had the opportunity to evaluate the performance and scalability of their remote sensing infrastructure. This article reports the lessons learned from our study, which considered both data collection and data dissemination aspects of their system. On the data collection front, we used benchmarking techniques to identify and fix a performance bottleneck in the system’s memory management for TCP data streams, while also improving system efficiency on multi-core architectures. On the data dissemination front, we used passive and active network traffic measurements to identify and reduce excessive network traffic from the Web robots and JavaScript techniques used for data sharing. While our results are from one specific sensor Web system, the lessons learned may apply to other scientific Web sites with remote sensing infrastructure.

  8. Scalable Photogrammetric Motion Capture System "mosca": Development and Application

    Science.gov (United States)

    Knyaz, V. A.

    2015-05-01

    Wide variety of applications (from industrial to entertainment) has a need for reliable and accurate 3D information about motion of an object and its parts. Very often the process of movement is rather fast as in cases of vehicle movement, sport biomechanics, animation of cartoon characters. Motion capture systems based on different physical principles are used for these purposes. The great potential for obtaining high accuracy and high degree of automation has vision-based system due to progress in image processing and analysis. Scalable inexpensive motion capture system is developed as a convenient and flexible tool for solving various tasks requiring 3D motion analysis. It is based on photogrammetric techniques of 3D measurements and provides high speed image acquisition, high accuracy of 3D measurements and highly automated processing of captured data. Depending on the application the system can be easily modified for different working areas from 100 mm to 10 m. The developed motion capture system uses from 2 to 4 technical vision cameras for video sequences of object motion acquisition. All cameras work in synchronization mode at frame rate up to 100 frames per second under the control of personal computer providing the possibility for accurate calculation of 3D coordinates of interest points. The system was used for a set of different applications fields and demonstrated high accuracy and high level of automation.

  9. TDCCREC: AN EFFICIENT AND SCALABLE WEB-BASED RECOMMENDATION SYSTEM

    Directory of Open Access Journals (Sweden)

    K.Latha

    2010-10-01

    Full Text Available Web browsers are provided with complex information space where the volume of information available to them is huge. There comes the Recommender system which effectively recommends web pages that are related to the current webpage, to provide the user with further customized reading material. To enhance the performance of the recommender systems, we include an elegant proposed web based recommendation system; Truth Discovery based Content and Collaborative RECommender (TDCCREC which is capable of addressing scalability. Existing approaches such as Learning automata deals with usage and navigational patterns of users. On the other hand, Weighted Association Rule is applied for recommending web pages by assigning weights to each page in all the transactions. Both of them have their own disadvantages. The websites recommended by the search engines have no guarantee for information correctness and often delivers conflicting information. To solve them, content based filtering and collaborative filtering techniques are introduced for recommending web pages to the active user along with the trustworthiness of the website and confidence of facts which outperforms the existing methods. Our results show how the proposed recommender system performs better in predicting the next request of web users.

  10. Highly scalable and robust rule learner: performance evaluation and comparison.

    Science.gov (United States)

    Kurgan, Lukasz A; Cios, Krzysztof J; Dick, Scott

    2006-02-01

    Business intelligence and bioinformatics applications increasingly require the mining of datasets consisting of millions of data points, or crafting real-time enterprise-level decision support systems for large corporations and drug companies. In all cases, there needs to be an underlying data mining system, and this mining system must be highly scalable. To this end, we describe a new rule learner called DataSqueezer. The learner belongs to the family of inductive supervised rule extraction algorithms. DataSqueezer is a simple, greedy, rule builder that generates a set of production rules from labeled input data. In spite of its relative simplicity, DataSqueezer is a very effective learner. The rules generated by the algorithm are compact, comprehensible, and have accuracy comparable to rules generated by other state-of-the-art rule extraction algorithms. The main advantages of DataSqueezer are very high efficiency, and missing data resistance. DataSqueezer exhibits log-linear asymptotic complexity with the number of training examples, and it is faster than other state-of-the-art rule learners. The learner is also robust to large quantities of missing data, as verified by extensive experimental comparison with the other learners. DataSqueezer is thus well suited to modern data mining and business intelligence tasks, which commonly involve huge datasets with a large fraction of missing data.

  11. Elastic pointer directory organization for scalable shared memory multiprocessors

    Institute of Scientific and Technical Information of China (English)

    Yuhang Liu; Mingfa Zhu; Limin Xiao

    2014-01-01

    In the field of supercomputing, one key issue for scal-able shared-memory multiprocessors is the design of the directory which denotes the sharing state for a cache block. A good direc-tory design intends to achieve three key attributes: reasonable memory overhead, sharer position precision and implementation complexity. However, researchers often face the problem that gain-ing one attribute may result in losing another. The paper proposes an elastic pointer directory (EPD) structure based on the analysis of shared-memory applications, taking the fact that the number of sharers for each directory entry is typical y smal . Analysis re-sults show that for 4 096 nodes, the ratio of memory overhead to the ful-map directory is 2.7%. Theoretical analysis and cycle-accurate execution-driven simulations on a 16 and 64-node cache coherence non uniform memory access (CC-NUMA) multiproces-sor show that the corresponding pointer overflow probability is reduced significantly. The performance is observed to be better than that of a limited pointers directory and almost identical to the ful-map directory, except for the slight implementation complex-ity. Using the directory cache to explore directory access locality is also studied. The experimental result shows that this is a promis-ing approach to be used in the state-of-the-art high performance computing domain.

  12. Highly scalable parallel processing of extracellular recordings of Multielectrode Arrays.

    Science.gov (United States)

    Gehring, Tiago V; Vasilaki, Eleni; Giugliano, Michele

    2015-01-01

    Technological advances of Multielectrode Arrays (MEAs) used for multisite, parallel electrophysiological recordings, lead to an ever increasing amount of raw data being generated. Arrays with hundreds up to a few thousands of electrodes are slowly seeing widespread use and the expectation is that more sophisticated arrays will become available in the near future. In order to process the large data volumes resulting from MEA recordings there is a pressing need for new software tools able to process many data channels in parallel. Here we present a new tool for processing MEA data recordings that makes use of new programming paradigms and recent technology developments to unleash the power of modern highly parallel hardware, such as multi-core CPUs with vector instruction sets or GPGPUs. Our tool builds on and complements existing MEA data analysis packages. It shows high scalability and can be used to speed up some performance critical pre-processing steps such as data filtering and spike detection, helping to make the analysis of larger data sets tractable.

  13. Nano-islands Based Charge Trapping Memory: A Scalability Study

    KAUST Repository

    Elatab, Nazek

    2017-10-19

    Zinc-oxide (ZnO) and zirconia (ZrO2) metal oxides have been studied extensively in the past few decades with several potential applications including memory devices. In this work, a scalability study, based on the ITRS roadmap, is conducted on memory devices with ZnO and ZrO2 nano-islands charge trapping layer. Both nano-islands are deposited using atomic layer deposition (ALD), however, the different sizes, distribution and properties of the materials result in different memory performance. The results show that at the 32-nm node charge trapping memory with 127 ZrO2 nano-islands can provide a 9.4 V memory window. However, with ZnO only 31 nano-islands can provide a window of 2.5 V. The results indicate that ZrO2 nano-islands are more promising than ZnO in scaled down devices due to their higher density, higher-k, and absence of quantum confinement effects.

  14. Mindfulness and compassion: an examination of mechanism and scalability.

    Directory of Open Access Journals (Sweden)

    Daniel Lim

    Full Text Available Emerging evidence suggests that meditation engenders prosocial behaviors meant to benefit others. However, the robustness, underlying mechanisms, and potential scalability of such effects remain open to question. The current experiment employed an ecologically valid situation that exposed participants to a person in visible pain. Following three-week, mobile-app based training courses in mindfulness meditation or cognitive skills (i.e., an active control condition, participants arrived at a lab individually to complete purported measures of cognitive ability. Upon entering a public waiting area outside the lab that contained three chairs, participants seated themselves in the last remaining unoccupied chair; confederates occupied the other two. As the participant sat and waited, a third confederate using crutches and a large walking boot entered the waiting area while displaying discomfort. Compassionate responding was assessed by whether participants gave up their seat to allow the uncomfortable confederate to sit, thereby relieving her pain. Participants' levels of empathic accuracy was also assessed. As predicted, participants assigned to the mindfulness meditation condition gave up their seats more frequently than did those assigned to the active control group. In addition, empathic accuracy was not increased by mindfulness practice, suggesting that mindfulness-enhanced compassionate behavior does not stem from associated increases in the ability to decode the emotional experiences of others.

  15. Interactive and Animated Scalable Vector Graphics and R Data Displays

    Directory of Open Access Journals (Sweden)

    Deborah Nolan

    2012-01-01

    Full Text Available We describe an approach to creating interactive and animated graphical displays using R's graphics engine and Scalable Vector Graphics, an XML vocabulary for describing two-dimensional graphical displays. We use the svg( graphics device in R and then post-process the resulting XML documents. The post-processing identities the elements in the SVG that correspond to the different components of the graphical display, e.g., points, axes, labels, lines. One can then annotate these elements to add interactivity and animation effects. One can also use JavaScript to provide dynamic interactive effects to the plot, enabling rich user interactions and compelling visualizations. The resulting SVG documents can be embedded withinHTML documents and can involve JavaScript code that integrates the SVG and HTML objects. The functionality is provided via the SVGAnnotation package and makes static plots generated via R graphics functions available as stand-alone, interactive and animated plots for the Web and other venues.

  16. Parallel peak pruning for scalable SMP contour tree computation

    Energy Technology Data Exchange (ETDEWEB)

    Carr, Hamish A. [Univ. of Leeds (United Kingdom); Weber, Gunther H. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Davis, CA (United States); Sewell, Christopher M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Ahrens, James P. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-03-09

    As data sets grow to exascale, automated data analysis and visualisation are increasingly important, to intermediate human understanding and to reduce demands on disk storage via in situ analysis. Trends in architecture of high performance computing systems necessitate analysis algorithms to make effective use of combinations of massively multicore and distributed systems. One of the principal analytic tools is the contour tree, which analyses relationships between contours to identify features of more than local importance. Unfortunately, the predominant algorithms for computing the contour tree are explicitly serial, and founded on serial metaphors, which has limited the scalability of this form of analysis. While there is some work on distributed contour tree computation, and separately on hybrid GPU-CPU computation, there is no efficient algorithm with strong formal guarantees on performance allied with fast practical performance. Here in this paper, we report the first shared SMP algorithm for fully parallel contour tree computation, withfor-mal guarantees of O(lgnlgt) parallel steps and O(n lgn) work, and implementations with up to 10x parallel speed up in OpenMP and up to 50x speed up in NVIDIA Thrust.

  17. Microwave assisted scalable synthesis of titanium ferrite nanomaterials

    Science.gov (United States)

    Shukla, Abhishek; Bhardwaj, Abhishek K.; Singh, S. C.; Uttam, K. N.; Gautam, Nisha; Himanshu, A. K.; Shah, Jyoti; Kotnala, R. K.; Gopal, R.

    2018-04-01

    Titanium ferrite magnetic nanomaterials are synthesized by one-step, one pot, and scalable method assisted by microwave radiation. Effects of titanium content and microwave exposure time on size, shape, morphology, yield, bonding nature, crystalline structure, and magnetic properties of titanium ferrite nanomaterials are studied. As-synthesized nanomaterials are characterized by X-ray diffraction (XRD), ultraviolet-visible absorption spectroscopy (UV-Vis), attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR), Raman spectroscopy, transmission electron microscopy (TEM), and vibrating sample magnetometer measurements. XRD measurements depict the presence of two phases of titanium ferrite into the same sample, where crystallite size increases from ˜33 nm to 37 nm with the increase in titanium concentration. UV-Vis measurement showed broad spectrum in the spectral range of 250-600 nm which reveals that its characteristic peaks lie between ultraviolet and visible region; ATR-FTIR and Raman measurements predict iron-titanium oxide structures that are consistent with XRD results. The micrographs of TEM and selected area electron diffraction patterns show formation of hexagonal shaped particles with a high degree of crystallinity and presence of multi-phase. Energy dispersive spectroscopy measurements confirm that Ti:Fe compositional mass ratio can be controlled by tuning synthesis conditions. Increase of Ti defects into titanium ferrite lattice, either by increasing titanium precursor or by increasing exposure time, enhances its magnetic properties.

  18. A Scalable proxy cache for Grid Data Access

    International Nuclear Information System (INIS)

    Cristian Cirstea, Traian; Just Keijser, Jan; Arthur Koeroo, Oscar; Starink, Ronald; Alan Templon, Jeffrey

    2012-01-01

    We describe a prototype grid proxy cache system developed at Nikhef, motivated by a desire to construct the first building block of a future https-based Content Delivery Network for grid infrastructures. Two goals drove the project: firstly to provide a “native view” of the grid for desktop-type users, and secondly to improve performance for physics-analysis type use cases, where multiple passes are made over the same set of data (residing on the grid). We further constrained the design by requiring that the system should be made of standard components wherever possible. The prototype that emerged from this exercise is a horizontally-scalable, cooperating system of web server / cache nodes, fronted by a customized webDAV server. The webDAV server is custom only in the sense that it supports http redirects (providing horizontal scaling) and that the authentication module has, as back end, a proxy delegation chain that can be used by the cache nodes to retrieve files from the grid. The prototype was deployed at Nikhef and tested at a scale of several terabytes of data and approximately one hundred fast cores of computing. Both small and large files were tested, in a number of scenarios, and with various numbers of cache nodes, in order to understand the scaling properties of the system. For properly-dimensioned cache-node hardware, the system showed speedup of several integer factors for the analysis-type use cases. These results and others are presented and discussed.

  19. Dynamic superhydrophobic behavior in scalable random textured polymeric surfaces

    Science.gov (United States)

    Moreira, David; Park, Sung-hoon; Lee, Sangeui; Verma, Neil; Bandaru, Prabhakar R.

    2016-03-01

    Superhydrophobic (SH) surfaces, created from hydrophobic materials with micro- or nano- roughness, trap air pockets in the interstices of the roughness, leading, in fluid flow conditions, to shear-free regions with finite interfacial fluid velocity and reduced resistance to flow. Significant attention has been given to SH conditions on ordered, periodic surfaces. However, in practical terms, random surfaces are more applicable due to their relative ease of fabrication. We investigate SH behavior on a novel durable polymeric rough surface created through a scalable roll-coating process with varying micro-scale roughness through velocity and pressure drop measurements. We introduce a new method to construct the velocity profile over SH surfaces with significant roughness in microchannels. Slip length was measured as a function of differing roughness and interstitial air conditions, with roughness and air fraction parameters obtained through direct visualization. The slip length was matched to scaling laws with good agreement. Roughness at high air fractions led to a reduced pressure drop and higher velocities, demonstrating the effectiveness of the considered surface in terms of reduced resistance to flow. We conclude that the observed air fraction under flow conditions is the primary factor determining the response in fluid flow. Such behavior correlated well with the hydrophobic or superhydrophobic response, indicating significant potential for practical use in enhancing fluid flow efficiency.

  20. A scalable coevolutionary multi-objective particle swarm optimizer

    Directory of Open Access Journals (Sweden)

    Xiangwei Zheng

    2010-11-01

    Full Text Available Multi-Objective Particle Swarm Optimizers (MOPSOs are easily trapped in local optima, cost more function evaluations and suffer from the curse of dimensionality. A scalable cooperative coevolution and ?-dominance based MOPSO (CEPSO is proposed to address these issues. In CEPSO, Multi-objective Optimization Problems (MOPs are decomposed in terms of their decision variables and are optimized by cooperative coevolutionary subswarms, and a uniform distribution mutation operator is adopted to avoid premature convergence. All subswarms share an external archive based on ?-dominance, which is also used as a leader set. Collaborators are selected from the archive and used to construct context vectors in order to evaluate particles in a subswarm. CEPSO is tested on several classical MOP benchmark functions and experimental results show that CEPSO can readily escape from local optima and optimize both low and high dimensional problems, but the number of function evaluations only increases linearly with respect to the number of decision variables. Therefore, CEPSO is competitive in solving various MOPs.

  1. Scalable, ultra-resistant structural colors based on network metamaterials

    KAUST Repository

    Galinski, Henning

    2017-05-05

    Structural colors have drawn wide attention for their potential as a future printing technology for various applications, ranging from biomimetic tissues to adaptive camouflage materials. However, an efficient approach to realize robust colors with a scalable fabrication technique is still lacking, hampering the realization of practical applications with this platform. Here, we develop a new approach based on large-scale network metamaterials that combine dealloyed subwavelength structures at the nanoscale with lossless, ultra-thin dielectric coatings. By using theory and experiments, we show how subwavelength dielectric coatings control a mechanism of resonant light coupling with epsilon-near-zero regions generated in the metallic network, generating the formation of saturated structural colors that cover a wide portion of the spectrum. Ellipsometry measurements support the efficient observation of these colors, even at angles of 70°. The network-like architecture of these nanomaterials allows for high mechanical resistance, which is quantified in a series of nano-scratch tests. With such remarkable properties, these metastructures represent a robust design technology for real-world, large-scale commercial applications.

  2. CX: A Scalable, Robust Network for Parallel Computing

    Directory of Open Access Journals (Sweden)

    Peter Cappello

    2002-01-01

    Full Text Available CX, a network-based computational exchange, is presented. The system's design integrates variations of ideas from other researchers, such as work stealing, non-blocking tasks, eager scheduling, and space-based coordination. The object-oriented API is simple, compact, and cleanly separates application logic from the logic that supports interprocess communication and fault tolerance. Computations, of course, run to completion in the presence of computational hosts that join and leave the ongoing computation. Such hosts, or producers, use task caching and prefetching to overlap computation with interprocessor communication. To break a potential task server bottleneck, a network of task servers is presented. Even though task servers are envisioned as reliable, the self-organizing, scalable network of n- servers, described as a sibling-connected height-balanced fat tree, tolerates a sequence of n-1 server failures. Tasks are distributed throughout the server network via a simple "diffusion" process. CX is intended as a test bed for research on automated silent auctions, reputation services, authentication services, and bonding services. CX also provides a test bed for algorithm research into network-based parallel computation.

  3. Scalable Fault-Tolerant Location Management Scheme for Mobile IP

    Directory of Open Access Journals (Sweden)

    JinHo Ahn

    2001-11-01

    Full Text Available As the number of mobile nodes registering with a network rapidly increases in Mobile IP, multiple mobility (home of foreign agents can be allocated to a network in order to improve performance and availability. Previous fault tolerant schemes (denoted by PRT schemes to mask failures of the mobility agents use passive replication techniques. However, they result in high failure-free latency during registration process if the number of mobility agents in the same network increases, and force each mobility agent to manage bindings of all the mobile nodes registering with its network. In this paper, we present a new fault-tolerant scheme (denoted by CML scheme using checkpointing and message logging techniques. The CML scheme achieves low failure-free latency even if the number of mobility agents in a network increases, and improves scalability to a large number of mobile nodes registering with each network compared with the PRT schemes. Additionally, the CML scheme allows each failed mobility agent to recover bindings of the mobile nodes registering with the mobility agent when it is repaired even if all the other mobility agents in the same network concurrently fail.

  4. A Scalable Architecture for VoIP Conferencing

    Directory of Open Access Journals (Sweden)

    R Venkatesha Prasad

    2003-10-01

    Full Text Available Real-Time services are traditionally supported on circuit switched network. However, there is a need to port these services on packet switched network. Architecture for audio conferencing application over the Internet in the light of ITU-T H.323 recommendations is considered. In a conference, considering packets only from a set of selected clients can reduce speech quality degradation because mixing packets from all clients can lead to lack of speech clarity. A distributed algorithm and architecture for selecting clients for mixing is suggested here based on a new quantifier of the voice activity called "Loudness Number" (LN. The proposed system distributes the computation load and reduces the load on client terminals. The highlights of this architecture are scalability, bandwidth saving and speech quality enhancement. Client selection for playing out tries to mimic a physical conference where the most vocal participants attract more attention. The contributions of the paper are expected to aid H.323 recommendations implementations for Multipoint Processors (MP. A working prototype based on the proposed architecture is already functional.

  5. Think 500, not 50! A scalable approach to student success in STEM.

    Science.gov (United States)

    LaCourse, William R; Sutphin, Kathy Lee; Ott, Laura E; Maton, Kenneth I; McDermott, Patrice; Bieberich, Charles; Farabaugh, Philip; Rous, Philip

    2017-01-01

    UMBC, a diverse public research university, "builds" upon its reputation in producing highly capable undergraduate scholars to create a comprehensive new model, STEM BUILD at UMBC. This program is designed to help more students develop the skills, experience and motivation to excel in science, technology, engineering, and mathematics (STEM). This article provides an in-depth description of STEM BUILD at UMBC and provides the context of this initiative within UMBC's vision and mission. The STEM BUILD model targets promising STEM students who enter as freshmen or transfer students and do not qualify for significant university or other scholarship support. Of primary importance to this initiative are capacity, scalability, and institutional sustainability, as we distill the advantages and opportunities of UMBC's successful scholars programs and expand their application to more students. The general approach is to infuse the mentoring and training process into the fabric of the undergraduate experience while fostering community, scientific identity, and resilience. At the heart of STEM BUILD at UMBC is the development of BUILD Group Research (BGR), a sequence of experiences designed to overcome the challenges that undergraduates without programmatic support often encounter (e.g., limited internship opportunities, mentorships, and research positions for which top STEM students are favored). BUILD Training Program (BTP) Trainees serve as pioneers in this initiative, which is potentially a national model for universities as they address the call to retain and graduate more students in STEM disciplines - especially those from underrepresented groups. As such, BTP is a research study using random assignment trial methodology that focuses on the scalability and eventual incorporation of successful measures into the traditional format of the academy. Critical measures to transform institutional culture include establishing an extensive STEM Living and Learning Community to

  6. A Secure, Scalable and Elastic Autonomic Computing Systems Paradigm: Supporting Dynamic Adaptation of Self-* Services from an Autonomic Cloud

    Directory of Open Access Journals (Sweden)

    Abdul Jaleel

    2018-05-01

    Full Text Available Autonomic computing embeds self-management features in software systems using external feedback control loops, i.e., autonomic managers. In existing models of autonomic computing, adaptive behaviors are defined at the design time, autonomic managers are statically configured, and the running system has a fixed set of self-* capabilities. An autonomic computing design should accommodate autonomic capability growth by allowing the dynamic configuration of self-* services, but this causes security and integrity issues. A secure, scalable and elastic autonomic computing system (SSE-ACS paradigm is proposed to address the runtime inclusion of autonomic managers, ensuring secure communication between autonomic managers and managed resources. Applying the SSE-ACS concept, a layered approach for the dynamic adaptation of self-* services is presented with an online ‘Autonomic_Cloud’ working as the middleware between Autonomic Managers (offering the self-* services and Autonomic Computing System (requiring the self-* services. A stock trading and forecasting system is used for simulation purposes. The security impact of the SSE-ACS paradigm is verified by testing possible attack cases over the autonomic computing system with single and multiple autonomic managers running on the same and different machines. The common vulnerability scoring system (CVSS metric shows a decrease in the vulnerability severity score from high (8.8 for existing ACS to low (3.9 for SSE-ACS. Autonomic managers are introduced into the system at runtime from the Autonomic_Cloud to test the scalability and elasticity. With elastic AMs, the system optimizes the Central Processing Unit (CPU share resulting in an improved execution time for business logic. For computing systems requiring the continuous support of self-management services, the proposed system achieves a significant improvement in security, scalability, elasticity, autonomic efficiency, and issue resolving time

  7. MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME.

    Science.gov (United States)

    Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

    2016-01-01

    Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments.

  8. Scalable and near-optimal design space exploration for embedded systems

    CERN Document Server

    Kritikakou, Angeliki; Goutis, Costas

    2014-01-01

    This book describes scalable and near-optimal, processor-level design space exploration (DSE) methodologies.  The authors present design methodologies for data storage and processing in real-time, cost-sensitive data-dominated embedded systems.  Readers will be enabled to reduce time-to-market, while satisfying system requirements for performance, area, and energy consumption, thereby minimizing the overall cost of the final design.   • Describes design space exploration (DSE) methodologies for data storage and processing in embedded systems, which achieve near-optimal solutions with scalable exploration time; • Presents a set of principles and the processes which support the development of the proposed scalable and near-optimal methodologies; • Enables readers to apply scalable and near-optimal methodologies to the intra-signal in-place optimization step for both regular and irregular memory accesses.

  9. Temporal Scalability through Adaptive -Band Filter Banks for Robust H.264/MPEG-4 AVC Video Coding

    Directory of Open Access Journals (Sweden)

    Pau G

    2006-01-01

    Full Text Available This paper presents different structures that use adaptive -band hierarchical filter banks for temporal scalability. Open-loop and closed-loop configurations are introduced and illustrated using existing video codecs. In particular, it is shown that the H.264/MPEG-4 AVC codec allows us to introduce scalability by frame shuffling operations, thus keeping backward compatibility with the standard. The large set of shuffling patterns introduced here can be exploited to adapt the encoding process to the video content features, as well as to the user equipment and transmission channel characteristics. Furthermore, simulation results show that this scalability is obtained with no degradation in terms of subjective and objective quality in error-free environments, while in error-prone channels the scalable versions provide increased robustness.

  10. SuperLU{_}DIST: A scalable distributed-memory sparse direct solver for unsymmetric linear systems

    Energy Technology Data Exchange (ETDEWEB)

    Li, Xiaoye S.; Demmel, James W.

    2002-03-27

    In this paper, we present the main algorithmic features in the software package SuperLU{_}DIST, a distributed-memory sparse direct solver for large sets of linear equations. We give in detail our parallelization strategies, with focus on scalability issues, and demonstrate the parallel performance and scalability on current machines. The solver is based on sparse Gaussian elimination, with an innovative static pivoting strategy proposed earlier by the authors. The main advantage of static pivoting over classical partial pivoting is that it permits a priori determination of data structures and communication pattern for sparse Gaussian elimination, which makes it more scalable on distributed memory machines. Based on this a priori knowledge, we designed highly parallel and scalable algorithms for both LU decomposition and triangular solve and we show that they are suitable for large-scale distributed memory machines.

  11. Continuous flow photocyclization of stilbenes – scalable synthesis of functionalized phenanthrenes and helicenes

    Directory of Open Access Journals (Sweden)

    Quentin Lefebvre

    2013-09-01

    Full Text Available A continuous flow oxidative photocyclization of stilbene derivatives has been developed which allows the scalable synthesis of backbone functionalized phenanthrenes and helicenes of various sizes in good yields.

  12. Investigation on Reliability and Scalability of an FBG-Based Hierarchical AOFSN

    Directory of Open Access Journals (Sweden)

    Li-Mei Peng

    2010-03-01

    Full Text Available The reliability and scalability of large-scale based optical fiber sensor networks (AOFSN are considered in this paper. The AOFSN network consists of three-level hierarchical sensor network architectures. The first two levels consist of active interrogation and remote nodes (RNs and the third level, called the sensor subnet (SSN, consists of passive Fiber Bragg Gratings (FBGs and a few switches. The switch architectures in the RN and various SSNs to improve the reliability and scalability of AOFSN are studied. Two SSNs with a regular topology are proposed to support simple routing and scalability in AOFSN: square-based sensor cells (SSC and pentagon-based sensor cells (PSC. The reliability and scalability are evaluated in terms of the available sensing coverage in the case of one or multiple link failures.

  13. Epitaxial Growth of Two-Dimensional Layered Transition-Metal Dichalcogenides: Growth Mechanism, Controllability, and Scalability

    KAUST Repository

    Li, Henan; Li, Ying; Aljarb, Areej; Shi, Yumeng; Li, Lain-Jong

    2017-01-01

    to generate high-quality TMDC layers with scalable size, controllable thickness, and excellent electronic properties suitable for both technological applications and fundamental sciences. The capability to precisely engineer 2D materials by chemical approaches

  14. Scalable Metadata Management for a Large Multi-Source Seismic Data Repository

    Energy Technology Data Exchange (ETDEWEB)

    Gaylord, J. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Dodge, D. A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Magana-Zook, S. A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Barno, J. G. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Knapp, D. R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Thomas, J. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sullivan, D. S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Ruppert, S. D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Mellors, R. J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2017-05-26

    In this work, we implemented the key metadata management components of a scalable seismic data ingestion framework to address limitations in our existing system, and to position it for anticipated growth in volume and complexity.

  15. Application of response surface methodology to maximize the productivity of scalable automated human embryonic stem cell manufacture.

    Science.gov (United States)

    Ratcliffe, Elizabeth; Hourd, Paul; Guijarro-Leach, Juan; Rayment, Erin; Williams, David J; Thomas, Robert J

    2013-01-01

    Commercial regenerative medicine will require large quantities of clinical-specification human cells. The cost and quality of manufacture is notoriously difficult to control due to highly complex processes with poorly defined tolerances. As a step to overcome this, we aimed to demonstrate the use of 'quality-by-design' tools to define the operating space for economic passage of a scalable human embryonic stem cell production method with minimal cell loss. Design of experiments response surface methodology was applied to generate empirical models to predict optimal operating conditions for a unit of manufacture of a previously developed automatable and scalable human embryonic stem cell production method. Two models were defined to predict cell yield and cell recovery rate postpassage, in terms of the predictor variables of media volume, cell seeding density, media exchange and length of passage. Predicted operating conditions for maximized productivity were successfully validated. Such 'quality-by-design' type approaches to process design and optimization will be essential to reduce the risk of product failure and patient harm, and to build regulatory confidence in cell therapy manufacturing processes.

  16. LOGISTIC NETWORK REGRESSION FOR SCALABLE ANALYSIS OF NETWORKS WITH JOINT EDGE/VERTEX DYNAMICS.

    Science.gov (United States)

    Almquist, Zack W; Butts, Carter T

    2014-08-01

    Change in group size and composition has long been an important area of research in the social sciences. Similarly, interest in interaction dynamics has a long history in sociology and social psychology. However, the effects of endogenous group change on interaction dynamics are a surprisingly understudied area. One way to explore these relationships is through social network models. Network dynamics may be viewed as a process of change in the edge structure of a network, in the vertex set on which edges are defined, or in both simultaneously. Although early studies of such processes were primarily descriptive, recent work on this topic has increasingly turned to formal statistical models. Although showing great promise, many of these modern dynamic models are computationally intensive and scale very poorly in the size of the network under study and/or the number of time points considered. Likewise, currently used models focus on edge dynamics, with little support for endogenously changing vertex sets. Here, the authors show how an existing approach based on logistic network regression can be extended to serve as a highly scalable framework for modeling large networks with dynamic vertex sets. The authors place this approach within a general dynamic exponential family (exponential-family random graph modeling) context, clarifying the assumptions underlying the framework (and providing a clear path for extensions), and they show how model assessment methods for cross-sectional networks can be extended to the dynamic case. Finally, the authors illustrate this approach on a classic data set involving interactions among windsurfers on a California beach.

  17. GoFFish: Graph-Oriented Framework for Foresight and Insight Using Scalable Heuristics

    Science.gov (United States)

    2015-09-01

    A. Biem, E. Bouillet, H. Feng, A. Ranganathan , A. Riabov, O. Verscheure, H. Koutsopoulos, and C. Moran, “Ibm infos- phere streams for scalable, real...Systems and Software. Elsevier, 2013, vol. 86, no. 1, pp. 2–11. [5] A. Biem, E. Bouillet, H. Feng, A. Ranganathan , A. Riabov, O. Verscheure, H...Feng, A. Ranganathan , A. Riabov, O. Verscheure, H. Koutsopoulos, and C. Moran. Ibm infosphere streams for scalable, real-time, intelligent

  18. Scalable Coating and Properties of Transparent, Flexible, Silver Nanowire Electrodes

    KAUST Repository

    Hu, Liangbing

    2010-05-25

    We report a comprehensive study of transparent and conductive silver nanowire (Ag NW) electrodes, including a scalable fabrication process, morphologies, and optical, mechanical adhesion, and flexibility properties, and various routes to improve the performance. We utilized a synthesis specifically designed for long and thin wires for improved performance in terms of sheet resistance and optical transmittance. Twenty Ω/sq and ∼ 80% specular transmittance, and 8 ohms/sq and 80% diffusive transmittance in the visible range are achieved, which fall in the same range as the best indium tin oxide (ITO) samples on plastic substrates for flexible electronics and solar cells. The Ag NW electrodes show optical transparencies superior to ITO for near-infrared wavelengths (2-fold higher transmission). Owing to light scattering effects, the Ag NW network has the largest difference between diffusive transmittance and specular transmittance when compared with ITO and carbon nanotube electrodes, a property which could greatly enhance solar cell performance. A mechanical study shows that Ag NW electrodes on flexible substrates show excellent robustness when subjected to bending. We also study the electrical conductance of Ag nanowires and their junctions and report a facile electrochemical method for a Au coating to reduce the wire-to-wire junction resistance for better overall film conductance. Simple mechanical pressing was also found to increase the NW film conductance due to the reduction of junction resistance. The overall properties of transparent Ag NW electrodes meet the requirements of transparent electrodes for many applications and could be an immediate ITO replacement for flexible electronics and solar cells. © 2010 American Chemical Society.

  19. Hierarchical sets: analyzing pangenome structure through scalable set visualizations

    Science.gov (United States)

    2017-01-01

    Abstract Motivation: The increase in available microbial genome sequences has resulted in an increase in the size of the pangenomes being analyzed. Current pangenome visualizations are not intended for the pangenome sizes possible today and new approaches are necessary in order to convert the increase in available information to increase in knowledge. As the pangenome data structure is essentially a collection of sets we explore the potential for scalable set visualization as a tool for pangenome analysis. Results: We present a new hierarchical clustering algorithm based on set arithmetics that optimizes the intersection sizes along the branches. The intersection and union sizes along the hierarchy are visualized using a composite dendrogram and icicle plot, which, in pangenome context, shows the evolution of pangenome and core size along the evolutionary hierarchy. Outlying elements, i.e. elements whose presence pattern do not correspond with the hierarchy, can be visualized using hierarchical edge bundles. When applied to pangenome data this plot shows putative horizontal gene transfers between the genomes and can highlight relationships between genomes that is not represented by the hierarchy. We illustrate the utility of hierarchical sets by applying it to a pangenome based on 113 Escherichia and Shigella genomes and find it provides a powerful addition to pangenome analysis. Availability and Implementation: The described clustering algorithm and visualizations are implemented in the hierarchicalSets R package available from CRAN (https://cran.r-project.org/web/packages/hierarchicalSets) Contact: thomasp85@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28130242

  20. Scalable Coating and Properties of Transparent, Flexible, Silver Nanowire Electrodes

    KAUST Repository

    Hu, Liangbing; Kim, Han Sun; Lee, Jung-Yong; Peumans, Peter; Cui, Yi

    2010-01-01

    We report a comprehensive study of transparent and conductive silver nanowire (Ag NW) electrodes, including a scalable fabrication process, morphologies, and optical, mechanical adhesion, and flexibility properties, and various routes to improve the performance. We utilized a synthesis specifically designed for long and thin wires for improved performance in terms of sheet resistance and optical transmittance. Twenty Ω/sq and ∼ 80% specular transmittance, and 8 ohms/sq and 80% diffusive transmittance in the visible range are achieved, which fall in the same range as the best indium tin oxide (ITO) samples on plastic substrates for flexible electronics and solar cells. The Ag NW electrodes show optical transparencies superior to ITO for near-infrared wavelengths (2-fold higher transmission). Owing to light scattering effects, the Ag NW network has the largest difference between diffusive transmittance and specular transmittance when compared with ITO and carbon nanotube electrodes, a property which could greatly enhance solar cell performance. A mechanical study shows that Ag NW electrodes on flexible substrates show excellent robustness when subjected to bending. We also study the electrical conductance of Ag nanowires and their junctions and report a facile electrochemical method for a Au coating to reduce the wire-to-wire junction resistance for better overall film conductance. Simple mechanical pressing was also found to increase the NW film conductance due to the reduction of junction resistance. The overall properties of transparent Ag NW electrodes meet the requirements of transparent electrodes for many applications and could be an immediate ITO replacement for flexible electronics and solar cells. © 2010 American Chemical Society.

  1. Scalable electro-photonic integration concept based on polymer waveguides

    Science.gov (United States)

    Bosman, E.; Van Steenberge, G.; Boersma, A.; Wiegersma, S.; Harmsma, P.; Karppinen, M.; Korhonen, T.; Offrein, B. J.; Dangel, R.; Daly, A.; Ortsiefer, M.; Justice, J.; Corbett, B.; Dorrestein, S.; Duis, J.

    2016-03-01

    A novel method for fabricating a single mode optical interconnection platform is presented. The method comprises the miniaturized assembly of optoelectronic single dies, the scalable fabrication of polymer single mode waveguides and the coupling to glass fiber arrays providing the I/O's. The low cost approach for the polymer waveguide fabrication is based on the nano-imprinting of a spin-coated waveguide core layer. The assembly of VCSELs and photodiodes is performed before waveguide layers are applied. By embedding these components in deep reactive ion etched pockets in the silicon substrate, the planarity of the substrate for subsequent layer processing is guaranteed and the thermal path of chip-to-substrate is minimized. Optical coupling of the embedded devices to the nano-imprinted waveguides is performed by laser ablating 45 degree trenches which act as optical mirror for 90 degree deviation of the light from VCSEL to waveguide. Laser ablation is also implemented for removing parts of the polymer stack in order to mount a custom fabricated connector containing glass fiber arrays. A demonstration device was built to show the proof of principle of the novel fabrication, packaging and optical coupling principles as described above, combined with a set of sub-demonstrators showing the functionality of the different techniques separately. The paper represents a significant part of the electro-photonic integration accomplishments in the European 7th Framework project "Firefly" and not only discusses the development of the different assembly processes described above, but the efforts on the complete integration of all process approaches into the single device demonstrator.

  2. Rate control scheme for consistent video quality in scalable video codec.

    Science.gov (United States)

    Seo, Chan-Won; Han, Jong-Ki; Nguyen, Truong Q

    2011-08-01

    Multimedia data delivered to mobile devices over wireless channels or the Internet are complicated by bandwidth fluctuation and the variety of mobile devices. Scalable video coding has been developed as an extension of H.264/AVC to solve this problem. Since scalable video codec provides various scalabilities to adapt the bitstream for the channel conditions and terminal types, scalable codec is one of the useful codecs for wired or wireless multimedia communication systems, such as IPTV and streaming services. In such scalable multimedia communication systems, video quality fluctuation degrades the visual perception significantly. It is important to efficiently use the target bits in order to maintain a consistent video quality or achieve a small distortion variation throughout the whole video sequence. The scheme proposed in this paper provides a useful function to control video quality in applications supporting scalability, whereas conventional schemes have been proposed to control video quality in the H.264 and MPEG-4 systems. The proposed algorithm decides the quantization parameter of the enhancement layer to maintain a consistent video quality throughout the entire sequence. The video quality of the enhancement layer is controlled based on a closed-form formula which utilizes the residual data and quantization error of the base layer. The simulation results show that the proposed algorithm controls the frame quality of the enhancement layer in a simple operation, where the parameter decision algorithm is applied to each frame.

  3. A scalable healthcare information system based on a service-oriented architecture.

    Science.gov (United States)

    Yang, Tzu-Hsiang; Sun, Yeali S; Lai, Feipei

    2011-06-01

    Many existing healthcare information systems are composed of a number of heterogeneous systems and face the important issue of system scalability. This paper first describes the comprehensive healthcare information systems used in National Taiwan University Hospital (NTUH) and then presents a service-oriented architecture (SOA)-based healthcare information system (HIS) based on the service standard HL7. The proposed architecture focuses on system scalability, in terms of both hardware and software. Moreover, we describe how scalability is implemented in rightsizing, service groups, databases, and hardware scalability. Although SOA-based systems sometimes display poor performance, through a performance evaluation of our HIS based on SOA, the average response time for outpatient, inpatient, and emergency HL7Central systems are 0.035, 0.04, and 0.036 s, respectively. The outpatient, inpatient, and emergency WebUI average response times are 0.79, 1.25, and 0.82 s. The scalability of the rightsizing project and our evaluation results show that the SOA HIS we propose provides evidence that SOA can provide system scalability and sustainability in a highly demanding healthcare information system.

  4. CORAL Server and CORAL Server Proxy: Scalable Access to Relational Databases from CORAL Applications

    CERN Document Server

    Valassi, A; Kalkhof, A; Salnikov, A; Wache, M

    2011-01-01

    The CORAL software is widely used at CERN for accessing the data stored by the LHC experiments using relational database technologies. CORAL provides a C++ abstraction layer that supports data persistency for several backends and deployment models, including local access to SQLite files, direct client access to Oracle and MySQL servers, and read-only access to Oracle through the FroNTier web server and cache. Two new components have recently been added to CORAL to implement a model involving a middle tier "CORAL server" deployed close to the database and a tree of "CORAL server proxy" instances, with data caching and multiplexing functionalities, deployed close to the client. The new components are meant to provide advantages for read-only and read-write data access, in both offline and online use cases, in the areas of scalability and performance (multiplexing for several incoming connections, optional data caching) and security (authentication via proxy certificates). A first implementation of the two new c...

  5. A scalable fully implicit framework for reservoir simulation on parallel computers

    KAUST Repository

    Yang, Haijian

    2017-11-10

    The modeling of multiphase fluid flow in porous medium is of interest in the field of reservoir simulation. The promising numerical methods in the literature are mostly based on the explicit or semi-implicit approach, which both have certain stability restrictions on the time step size. In this work, we introduce and study a scalable fully implicit solver for the simulation of two-phase flow in a porous medium with capillarity, gravity and compressibility, which is free from the limitations of the conventional methods. In the fully implicit framework, a mixed finite element method is applied to discretize the model equations for the spatial terms, and the implicit Backward Euler scheme with adaptive time stepping is used for the temporal integration. The resultant nonlinear system arising at each time step is solved in a monolithic way by using a Newton–Krylov type method. The corresponding linear system from the Newton iteration is large sparse, nonsymmetric and ill-conditioned, consequently posing a significant challenge to the fully implicit solver. To address this issue, the family of additive Schwarz preconditioners is taken into account to accelerate the convergence of the linear system, and thereby improves the robustness of the outer Newton method. Several test cases in one, two and three dimensions are used to validate the correctness of the scheme and examine the performance of the newly developed algorithm on parallel computers.

  6. A scalable fully implicit framework for reservoir simulation on parallel computers

    KAUST Repository

    Yang, Haijian; Sun, Shuyu; Li, Yiteng; Yang, Chao

    2017-01-01

    The modeling of multiphase fluid flow in porous medium is of interest in the field of reservoir simulation. The promising numerical methods in the literature are mostly based on the explicit or semi-implicit approach, which both have certain stability restrictions on the time step size. In this work, we introduce and study a scalable fully implicit solver for the simulation of two-phase flow in a porous medium with capillarity, gravity and compressibility, which is free from the limitations of the conventional methods. In the fully implicit framework, a mixed finite element method is applied to discretize the model equations for the spatial terms, and the implicit Backward Euler scheme with adaptive time stepping is used for the temporal integration. The resultant nonlinear system arising at each time step is solved in a monolithic way by using a Newton–Krylov type method. The corresponding linear system from the Newton iteration is large sparse, nonsymmetric and ill-conditioned, consequently posing a significant challenge to the fully implicit solver. To address this issue, the family of additive Schwarz preconditioners is taken into account to accelerate the convergence of the linear system, and thereby improves the robustness of the outer Newton method. Several test cases in one, two and three dimensions are used to validate the correctness of the scheme and examine the performance of the newly developed algorithm on parallel computers.

  7. Massive optimal data compression and density estimation for scalable, likelihood-free inference in cosmology

    Science.gov (United States)

    Alsing, Justin; Wandelt, Benjamin; Feeney, Stephen

    2018-03-01

    Many statistical models in cosmology can be simulated forwards but have intractable likelihood functions. Likelihood-free inference methods allow us to perform Bayesian inference from these models using only forward simulations, free from any likelihood assumptions or approximations. Likelihood-free inference generically involves simulating mock data and comparing to the observed data; this comparison in data-space suffers from the curse of dimensionality and requires compression of the data to a small number of summary statistics to be tractable. In this paper we use massive asymptotically-optimal data compression to reduce the dimensionality of the data-space to just one number per parameter, providing a natural and optimal framework for summary statistic choice for likelihood-free inference. Secondly, we present the first cosmological application of Density Estimation Likelihood-Free Inference (DELFI), which learns a parameterized model for joint distribution of data and parameters, yielding both the parameter posterior and the model evidence. This approach is conceptually simple, requires less tuning than traditional Approximate Bayesian Computation approaches to likelihood-free inference and can give high-fidelity posteriors from orders of magnitude fewer forward simulations. As an additional bonus, it enables parameter inference and Bayesian model comparison simultaneously. We demonstrate Density Estimation Likelihood-Free Inference with massive data compression on an analysis of the joint light-curve analysis supernova data, as a simple validation case study. We show that high-fidelity posterior inference is possible for full-scale cosmological data analyses with as few as ˜104 simulations, with substantial scope for further improvement, demonstrating the scalability of likelihood-free inference to large and complex cosmological datasets.

  8. StagBL : A Scalable, Portable, High-Performance Discretization and Solver Layer for Geodynamic Simulation

    Science.gov (United States)

    Sanan, P.; Tackley, P. J.; Gerya, T.; Kaus, B. J. P.; May, D.

    2017-12-01

    StagBL is an open-source parallel solver and discretization library for geodynamic simulation,encapsulating and optimizing operations essential to staggered-grid finite volume Stokes flow solvers.It provides a parallel staggered-grid abstraction with a high-level interface in C and Fortran.On top of this abstraction, tools are available to define boundary conditions and interact with particle systems.Tools and examples to efficiently solve Stokes systems defined on the grid are provided in small (direct solver), medium (simple preconditioners), and large (block factorization and multigrid) model regimes.By working directly with leading application codes (StagYY, I3ELVIS, and LaMEM) and providing an API and examples to integrate with others, StagBL aims to become a community tool supplying scalable, portable, reproducible performance toward novel science in regional- and planet-scale geodynamics and planetary science.By implementing kernels used by many research groups beneath a uniform abstraction layer, the library will enable optimization for modern hardware, thus reducing community barriers to large- or extreme-scale parallel simulation on modern architectures. In particular, the library will include CPU-, Manycore-, and GPU-optimized variants of matrix-free operators and multigrid components.The common layer provides a framework upon which to introduce innovative new tools.StagBL will leverage p4est to provide distributed adaptive meshes, and incorporate a multigrid convergence analysis tool.These options, in addition to a wealth of solver options provided by an interface to PETSc, will make the most modern solution techniques available from a common interface. StagBL in turn provides a PETSc interface, DMStag, to its central staggered grid abstraction.We present public version 0.5 of StagBL, including preliminary integration with application codes and demonstrations with its own demonstration application, StagBLDemo. Central to StagBL is the notion of an

  9. Content Adaptive Lagrange Multiplier Selection for Rate-Distortion Optimization in 3-D Wavelet-Based Scalable Video Coding

    Directory of Open Access Journals (Sweden)

    Ying Chen

    2018-03-01

    Full Text Available Rate-distortion optimization (RDO plays an essential role in substantially enhancing the coding efficiency. Currently, rate-distortion optimized mode decision is widely used in scalable video coding (SVC. Among all the possible coding modes, it aims to select the one which has the best trade-off between bitrate and compression distortion. Specifically, this tradeoff is tuned through the choice of the Lagrange multiplier. Despite the prevalence of conventional method for Lagrange multiplier selection in hybrid video coding, the underlying formulation is not applicable to 3-D wavelet-based SVC where the explicit values of the quantization step are not available, with on consideration of the content features of input signal. In this paper, an efficient content adaptive Lagrange multiplier selection algorithm is proposed in the context of RDO for 3-D wavelet-based SVC targeting quality scalability. Our contributions are two-fold. First, we introduce a novel weighting method, which takes account of the mutual information, gradient per pixel, and texture homogeneity to measure the temporal subband characteristics after applying the motion-compensated temporal filtering (MCTF technique. Second, based on the proposed subband weighting factor model, we derive the optimal Lagrange multiplier. Experimental results demonstrate that the proposed algorithm enables more satisfactory video quality with negligible additional computational complexity.

  10. High-Performance Scalable Information Service for the ATLAS Experiment

    International Nuclear Information System (INIS)

    Kolos, S; Boutsioukis, G; Hauser, R

    2012-01-01

    The ATLAS[1] experiment is operated by a highly distributed computing system which is constantly producing a lot of status information which is used to monitor the experiment operational conditions as well as to assess the quality of the physics data being taken. For example the ATLAS High Level Trigger(HLT) algorithms are executed on the online computing farm consisting from about 1500 nodes. Each HLT algorithm is producing few thousands histograms, which have to be integrated over the whole farm and carefully analyzed in order to properly tune the event rejection. In order to handle such non-physics data the Information Service (IS) facility has been developed in the scope of the ATLAS Trigger and Data Acquisition (TDAQ)[2] project. The IS provides a high-performance scalable solution for information exchange in distributed environment. In the course of an ATLAS data taking session the IS handles about a hundred gigabytes of information which is being constantly updated with the update interval varying from a second to a few tens of seconds. IS provides access to any information item on request as well as distributing notification to all the information subscribers. In the latter case IS subscribers receive information within a few milliseconds after it was updated. IS can handle arbitrary types of information, including histograms produced by the HLT applications, and provides C++, Java and Python API. The Information Service is a unique source of information for the majority of the online monitoring analysis and GUI applications used to control and monitor the ATLAS experiment. Information Service provides streaming functionality allowing efficient replication of all or part of the managed information. This functionality is used to duplicate the subset of the ATLAS monitoring data to the CERN public network with a latency of a few milliseconds, allowing efficient real-time monitoring of the data taking from outside the protected ATLAS network. Each information

  11. Scalable quantum information processing with photons and atoms

    Science.gov (United States)

    Pan, Jian-Wei

    Over the past three decades, the promises of super-fast quantum computing and secure quantum cryptography have spurred a world-wide interest in quantum information, generating fascinating quantum technologies for coherent manipulation of individual quantum systems. However, the distance of fiber-based quantum communications is limited due to intrinsic fiber loss and decreasing of entanglement quality. Moreover, probabilistic single-photon source and entanglement source demand exponentially increased overheads for scalable quantum information processing. To overcome these problems, we are taking two paths in parallel: quantum repeaters and through satellite. We used the decoy-state QKD protocol to close the loophole of imperfect photon source, and used the measurement-device-independent QKD protocol to close the loophole of imperfect photon detectors--two main loopholes in quantum cryptograph. Based on these techniques, we are now building world's biggest quantum secure communication backbone, from Beijing to Shanghai, with a distance exceeding 2000 km. Meanwhile, we are developing practically useful quantum repeaters that combine entanglement swapping, entanglement purification, and quantum memory for the ultra-long distance quantum communication. The second line is satellite-based global quantum communication, taking advantage of the negligible photon loss and decoherence in the atmosphere. We realized teleportation and entanglement distribution over 100 km, and later on a rapidly moving platform. We are also making efforts toward the generation of multiphoton entanglement and its use in teleportation of multiple properties of a single quantum particle, topological error correction, quantum algorithms for solving systems of linear equations and machine learning. Finally, I will talk about our recent experiments on quantum simulations on ultracold atoms. On the one hand, by applying an optical Raman lattice technique, we realized a two-dimensional spin-obit (SO

  12. Scalable and portable visualization of large atomistic datasets

    Science.gov (United States)

    Sharma, Ashish; Kalia, Rajiv K.; Nakano, Aiichiro; Vashishta, Priya

    2004-10-01

    A scalable and portable code named Atomsviewer has been developed to interactively visualize a large atomistic dataset consisting of up to a billion atoms. The code uses a hierarchical view frustum-culling algorithm based on the octree data structure to efficiently remove atoms outside of the user's field-of-view. Probabilistic and depth-based occlusion-culling algorithms then select atoms, which have a high probability of being visible. Finally a multiresolution algorithm is used to render the selected subset of visible atoms at varying levels of detail. Atomsviewer is written in C++ and OpenGL, and it has been tested on a number of architectures including Windows, Macintosh, and SGI. Atomsviewer has been used to visualize tens of millions of atoms on a standard desktop computer and, in its parallel version, up to a billion atoms. Program summaryTitle of program: Atomsviewer Catalogue identifier: ADUM Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADUM Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Computer for which the program is designed and others on which it has been tested: 2.4 GHz Pentium 4/Xeon processor, professional graphics card; Apple G4 (867 MHz)/G5, professional graphics card Operating systems under which the program has been tested: Windows 2000/XP, Mac OS 10.2/10.3, SGI IRIX 6.5 Programming languages used: C++, C and OpenGL Memory required to execute with typical data: 1 gigabyte of RAM High speed storage required: 60 gigabytes No. of lines in the distributed program including test data, etc.: 550 241 No. of bytes in the distributed program including test data, etc.: 6 258 245 Number of bits in a word: Arbitrary Number of processors used: 1 Has the code been vectorized or parallelized: No Distribution format: tar gzip file Nature of physical problem: Scientific visualization of atomic systems Method of solution: Rendering of atoms using computer graphic techniques, culling algorithms for data

  13. SoccerNet: A Scalable Dataset for Action Spotting in Soccer Videos

    KAUST Repository

    Giancola, Silvio; Amine, Mohieddine; Dghaily, Tarek; Ghanem, Bernard

    2018-01-01

    In this paper, we introduce SoccerNet, a benchmark for action spotting in soccer videos. The dataset is composed of 500 complete soccer games from six main European leagues, covering three seasons from 2014 to 2017 and a total duration of 764 hours. A total of 6,637 temporal annotations are automatically parsed from online match reports at a one minute resolution for three main classes of events (Goal, Yellow/Red Card, and Substitution). As such, the dataset is easily scalable. These annotations are manually refined to a one second resolution by anchoring them at a single timestamp following well-defined soccer rules. With an average of one event every 6.9 minutes, this dataset focuses on the problem of localizing very sparse events within long videos. We define the task of spotting as finding the anchors of soccer events in a video. Making use of recent developments in the realm of generic action recognition and detection in video, we provide strong baselines for detecting soccer events. We show that our best model for classifying temporal segments of length one minute reaches a mean Average Precision (mAP) of 67.8%. For the spotting task, our baseline reaches an Average-mAP of 49.7% for tolerances $\\delta$ ranging from 5 to 60 seconds.

  14. SoccerNet: A Scalable Dataset for Action Spotting in Soccer Videos

    KAUST Repository

    Giancola, Silvio

    2018-04-12

    In this paper, we introduce SoccerNet, a benchmark for action spotting in soccer videos. The dataset is composed of 500 complete soccer games from six main European leagues, covering three seasons from 2014 to 2017 and a total duration of 764 hours. A total of 6,637 temporal annotations are automatically parsed from online match reports at a one minute resolution for three main classes of events (Goal, Yellow/Red Card, and Substitution). As such, the dataset is easily scalable. These annotations are manually refined to a one second resolution by anchoring them at a single timestamp following well-defined soccer rules. With an average of one event every 6.9 minutes, this dataset focuses on the problem of localizing very sparse events within long videos. We define the task of spotting as finding the anchors of soccer events in a video. Making use of recent developments in the realm of generic action recognition and detection in video, we provide strong baselines for detecting soccer events. We show that our best model for classifying temporal segments of length one minute reaches a mean Average Precision (mAP) of 67.8%. For the spotting task, our baseline reaches an Average-mAP of 49.7% for tolerances $\\\\delta$ ranging from 5 to 60 seconds.

  15. The Solar Umbrella: A Low-cost Demonstration of Scalable Space Based Solar Power

    Science.gov (United States)

    Contreras, Michael T.; Trease, Brian P.; Sherwood, Brent

    2013-01-01

    Within the past decade, the Space Solar Power (SSP) community has seen an influx of stakeholders willing to entertain the SSP prospect of potentially boundless, base-load solar energy. Interested parties affiliated with the Department of Defense (DoD), the private sector, and various international entities have all agreed that while the benefits of SSP are tremendous and potentially profitable, the risk associated with developing an efficient end to end SSP harvesting system is still very high. In an effort to reduce the implementation risk for future SSP architectures, this study proposes a system level design that is both low-cost and seeks to demonstrate the furthest transmission of wireless power to date. The overall concept is presented and each subsystem is explained in detail with best estimates of current implementable technologies. Basic cost models were constructed based on input from JPL subject matter experts and assume that the technology demonstration would be carried out by a federally funded entity. The main thrust of the architecture is to demonstrate that a usable amount of solar power can be safely and reliably transmitted from space to the Earth's surface; however, maximum power scalability limits and their cost implications are discussed.

  16. Technical Report: Toward a Scalable Algorithm to Compute High-Dimensional Integrals of Arbitrary Functions

    International Nuclear Information System (INIS)

    Snyder, Abigail C.; Jiao, Yu

    2010-01-01

    Neutron experiments at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) frequently generate large amounts of data (on the order of 106-1012 data points). Hence, traditional data analysis tools run on a single CPU take too long to be practical and scientists are unable to efficiently analyze all data generated by experiments. Our goal is to develop a scalable algorithm to efficiently compute high-dimensional integrals of arbitrary functions. This algorithm can then be used to integrate the four-dimensional integrals that arise as part of modeling intensity from the experiments at the SNS. Here, three different one-dimensional numerical integration solvers from the GNU Scientific Library were modified and implemented to solve four-dimensional integrals. The results of these solvers on a final integrand provided by scientists at the SNS can be compared to the results of other methods, such as quasi-Monte Carlo methods, computing the same integral. A parallelized version of the most efficient method can allow scientists the opportunity to more effectively analyze all experimental data.

  17. Reactive wavepacket dynamics for four atom systems on scalable parallel computers

    International Nuclear Information System (INIS)

    Goldfield, E.M.

    1994-01-01

    While time-dependent quantum mechanics has been successfully applied to many three atom systems, it was nevertheless a computational challenge to use wavepacket methods to study four atom systems, systems with several heavy atoms, and systems with deep potential wells. S.K. Gray and the author are studying the reaction of OH + CO ↔ (HOCO) ↔ H + CO 2 , a difficult reaction by all the above criteria. Memory considerations alone made it impossible to use a single IBM RS/6000 workstation to study a four degree-of-freedom model of this system. They have developed a scalable parallel wavepacket code for the IBM SP1 and have run it on the SP1 at Argonne and at the Cornell Theory Center. The wavepacket, defined on a four dimensional grid, is spread out among the processors. Two-dimensional FFT's are used to compute the kinetic energy operator acting on the wavepacket. Accomplishing this task, which is the computationally intensive part of the calculation, requires a global transpose of the data. This transpose is the only serious communication between processors. Since the problem is essentially data-parallel, communication is regular and load-balancing is excellent. But as the problem is moderately fine-grained and messages are long, the ratio of communication to computation is somewhat high and they typically get about 55% of ideal speed-up

  18. A scalable machine-learning approach to recognize chemical names within large text databases

    Directory of Open Access Journals (Sweden)

    Wren Jonathan D

    2006-09-01

    Full Text Available Abstract Motivation The use or study of chemical compounds permeates almost every scientific field and in each of them, the amount of textual information is growing rapidly. There is a need to accurately identify chemical names within text for a number of informatics efforts such as database curation, report summarization, tagging of named entities and keywords, or the development/curation of reference databases. Results A first-order Markov Model (MM was evaluated for its ability to distinguish chemical names from words, yielding ~93% recall in recognizing chemical terms and ~99% precision in rejecting non-chemical terms on smaller test sets. However, because total false-positive events increase with the number of words analyzed, the scalability of name recognition was measured by processing 13.1 million MEDLINE records. The method yielded precision ranges from 54.7% to 100%, depending upon the cutoff score used, averaging 82.7% for approximately 1.05 million putative chemical terms extracted. Extracted chemical terms were analyzed to estimate the number of spelling variants per term, which correlated with the total number of times the chemical name appeared in MEDLINE. This variability in term construction was found to affect both information retrieval and term mapping when using PubMed and Ovid.

  19. Scalable Algorithms for Clustering Large Geospatiotemporal Data Sets on Manycore Architectures

    Science.gov (United States)

    Mills, R. T.; Hoffman, F. M.; Kumar, J.; Sreepathi, S.; Sripathi, V.

    2016-12-01

    The increasing availability of high-resolution geospatiotemporal data sets from sources such as observatory networks, remote sensing platforms, and computational Earth system models has opened new possibilities for knowledge discovery using data sets fused from disparate sources. Traditional algorithms and computing platforms are impractical for the analysis and synthesis of data sets of this size; however, new algorithmic approaches that can effectively utilize the complex memory hierarchies and the extremely high levels of available parallelism in state-of-the-art high-performance computing platforms can enable such analysis. We describe a massively parallel implementation of accelerated k-means clustering and some optimizations to boost computational intensity and utilization of wide SIMD lanes on state-of-the art multi- and manycore processors, including the second-generation Intel Xeon Phi ("Knights Landing") processor based on the Intel Many Integrated Core (MIC) architecture, which includes several new features, including an on-package high-bandwidth memory. We also analyze the code in the context of a few practical applications to the analysis of climatic and remotely-sensed vegetation phenology data sets, and speculate on some of the new applications that such scalable analysis methods may enable.

  20. A~Scalable~Data~Taking~System at~a~Test~Beam~for~LHC

    CERN Multimedia

    2002-01-01

    % RD-13 A Scalable Data Taking System at a Test Beam for LHC \\\\ \\\\We have installed a test beam read-out facility for the simultaneous test of LHC detectors, trigger and read-out electronics, together with the development of the supporting architecture in a multiprocessor environment. The aim of the project is to build a system which incorporates all the functionality of a complete read-out chain. Emphasis is put on a highly modular design, such that new hardware and software developments can be conveniently introduced. Exploiting this modularity, the set-up will evolve driven by progress in technologies and new software developments. \\\\ \\\\One of the main thrusts of the project is modelling and integration of different read-out architectures to provide a valuable training ground for new techniques. To address these aspects in a realistic manner, we collaborate with detector R\\&D projects in order to test higher level trigger systems, event building and high rate data transfers, once the techniques involve...

  1. Leveraging Fog Computing for Scalable IoT Datacenter Using Spine-Leaf Network Topology

    Directory of Open Access Journals (Sweden)

    K. C. Okafor

    2017-01-01

    Full Text Available With the Internet of Everything (IoE paradigm that gathers almost every object online, huge traffic workload, bandwidth, security, and latency issues remain a concern for IoT users in today’s world. Besides, the scalability requirements found in the current IoT data processing (in the cloud can hardly be used for applications such as assisted living systems, Big Data analytic solutions, and smart embedded applications. This paper proposes an extended cloud IoT model that optimizes bandwidth while allowing edge devices (Internet-connected objects/devices to smartly process data without relying on a cloud network. Its integration with a massively scaled spine-leaf (SL network topology is highlighted. This is contrasted with a legacy multitier layered architecture housing network services and routing policies. The perspective offered in this paper explains how low-latency and bandwidth intensive applications can transfer data to the cloud (and then back to the edge application without impacting QoS performance. Consequently, a spine-leaf Fog computing network (SL-FCN is presented for reducing latency and network congestion issues in a highly distributed and multilayer virtualized IoT datacenter environment. This approach is cost-effective as it maximizes bandwidth while maintaining redundancy and resiliency against failures in mission critical applications.

  2. Optimal and Scalable Caching for 5G Using Reinforcement Learning of Space-Time Popularities

    Science.gov (United States)

    Sadeghi, Alireza; Sheikholeslami, Fatemeh; Giannakis, Georgios B.

    2018-02-01

    Small basestations (SBs) equipped with caching units have potential to handle the unprecedented demand growth in heterogeneous networks. Through low-rate, backhaul connections with the backbone, SBs can prefetch popular files during off-peak traffic hours, and service them to the edge at peak periods. To intelligently prefetch, each SB must learn what and when to cache, while taking into account SB memory limitations, the massive number of available contents, the unknown popularity profiles, as well as the space-time popularity dynamics of user file requests. In this work, local and global Markov processes model user requests, and a reinforcement learning (RL) framework is put forth for finding the optimal caching policy when the transition probabilities involved are unknown. Joint consideration of global and local popularity demands along with cache-refreshing costs allow for a simple, yet practical asynchronous caching approach. The novel RL-based caching relies on a Q-learning algorithm to implement the optimal policy in an online fashion, thus enabling the cache control unit at the SB to learn, track, and possibly adapt to the underlying dynamics. To endow the algorithm with scalability, a linear function approximation of the proposed Q-learning scheme is introduced, offering faster convergence as well as reduced complexity and memory requirements. Numerical tests corroborate the merits of the proposed approach in various realistic settings.

  3. Facile and scalable fabrication of polymer-ceramic composite electrolyte with high ceramic loadings

    Science.gov (United States)

    Pandian, Amaresh Samuthira; Chen, X. Chelsea; Chen, Jihua; Lokitz, Bradley S.; Ruther, Rose E.; Yang, Guang; Lou, Kun; Nanda, Jagjit; Delnick, Frank M.; Dudney, Nancy J.

    2018-06-01

    Solid state electrolytes are a promising alternative to flammable liquid electrolytes for high-energy lithium battery applications. In this work polymer-ceramic composite electrolyte membrane with high ceramic loading (greater than 60 vol%) is fabricated using a model polymer electrolyte poly(ethylene oxide) + lithium trifluoromethane sulfonate and a lithium-conducting ceramic powder. The effects of processing methods, choice of plasticizer and varying composition on ionic conductivity of the composite electrolyte are thoroughly investigated. The physical, structural and thermal properties of the composites are exhaustively characterized. We demonstrate that aqueous spray coating followed by hot pressing is a scalable and inexpensive technique to obtain composite membranes that are amazingly dense and uniform. The ionic conductivity of composites fabricated using this protocol is at least one order of magnitude higher than those made by dry milling and solution casting. The introduction of tetraethylene glycol dimethyl ether further increases the ionic conductivity. The composite electrolyte's interfacial compatibility with metallic lithium and good cyclability is verified by constructing lithium symmetrical cells. A remarkable Li+ transference number of 0.79 is discovered for the composite electrolyte.

  4. CA-LOD: Collision Avoidance Level of Detail for Scalable, Controllable Crowds

    Science.gov (United States)

    Paris, Sébastien; Gerdelan, Anton; O'Sullivan, Carol

    The new wave of computer-driven entertainment technology throws audiences and game players into massive virtual worlds where entire cities are rendered in real time. Computer animated characters run through inner-city streets teeming with pedestrians, all fully rendered with 3D graphics, animations, particle effects and linked to 3D sound effects to produce more realistic and immersive computer-hosted entertainment experiences than ever before. Computing all of this detail at once is enormously computationally expensive, and game designers as a rule, have sacrificed the behavioural realism in favour of better graphics. In this paper we propose a new Collision Avoidance Level of Detail (CA-LOD) algorithm that allows games to support huge crowds in real time with the appearance of more intelligent behaviour. We propose two collision avoidance models used for two different CA-LODs: a fuzzy steering focusing on the performances, and a geometric steering to obtain the best realism. Mixing these approaches allows to obtain thousands of autonomous characters in real time, resulting in a scalable but still controllable crowd.

  5. A scalable pressure sensor based on an electrothermally and electrostatically operated resonator

    KAUST Repository

    Hajjaj, Amal Z.

    2017-11-29

    We present a pressure sensor based on the convective cooling of the air surrounding an electrothermally heated resonant bridge. Unlike conventional pressure sensors that rely on diaphragm deformation in response to pressure, the sensor does not require diaphragms of the large surface area, and hence is scalable and can be realized even at the nanoscale. The concept is demonstrated using both straight and arch microbeam resonators driven and sensed electrostatically. The change in the surrounding pressure is shown to be accurately tracked by monitoring the change in the resonance frequency of the structure. The sensitivity of the sensor, which is controllable by the applied electrothermal load, is shown near 57 811 ppm/mbar for a pressure range from 1 to 10 Torr. We show that a straight beam operated near the buckling threshold leads to the maximum sensitivity of the device. The experimental data and simulation results, based on a multi-physics finite element model, demonstrate the feasibility and simplicity of the pressure sensor. Published by AIP Publishing.

  6. Treatment of wastewater contaminated with detergents and mineral oils using effective and scalable technology.

    Science.gov (United States)

    Abdelmoez, Wael; Barakat, Nasser A M; Moaz, Asmaa

    2013-01-01

    In this work, effective, cheap and scalable methodology is introduced to treat oily wastewater. The water produced from car-wash processes was utilized as a model because it has various pollutants - oil, lubricants, detergents, solid particles, etc. The results showed that the turbidity and chemical oxygen demand (COD) values dramatically decrease by using the proposed treatment process, which consists of coagulation, flocculation, sand filtration, and oxidation followed by sand as well as activated carbon filtration. Moreover, the operating conditions were optimized. Without adjustment of the pH value of car-wash wastewater, it was found that 200 ppm of ferric chloride, as a coagulant, and 1 ppm of potassium permanganate, as an oxidant, are the optimum doses. The COD and turbidity values of the final treated wastewater were reduced by almost 88 and 100%, respectively. A prototype with 15 L capacity was designed and fabricated to investigate the scaling up and continuity of the proposed treatment strategy. The results were very promising and indicated that the introduced methodology can be industrially applied.

  7. A QFD-based optimization method for a scalable product platform

    Science.gov (United States)

    Luo, Xinggang; Tang, Jiafu; Kwong, C. K.

    2010-02-01

    In order to incorporate the customer into the early phase of the product development cycle and to better satisfy customers' requirements, this article adopts quality function deployment (QFD) for optimal design of a scalable product platform. A five-step QFD-based method is proposed to determine the optimal values for platform engineering characteristics (ECs) and non-platform ECs of the products within a product family. First of all, the houses of quality (HoQs) for all product variants are developed and a QFD-based optimization approach is used to determine the optimal ECs for each product variant. Sensitivity analysis is performed for each EC with respect to overall customer satisfaction (OCS). Based on the obtained sensitivity indices of ECs, a mathematical model is established to simultaneously optimize the values of the platform and the non-platform ECs. Finally, by comparing and analysing the optimal solutions with different number of platform ECs, the ECs with which the worst OCS loss can be avoided are selected as platform ECs. An illustrative example is used to demonstrate the feasibility of this method. A comparison between the proposed method and a two-step approach is conducted on the example. The comparison shows that, as a kind of single-stage approach, the proposed method yields better average degree of customer satisfaction due to the simultaneous optimization of platform and non-platform ECs.

  8. Gesture Modelling for Linguistic Purposes

    CSIR Research Space (South Africa)

    Olivrin, GJ

    2007-05-01

    Full Text Available The study of sign languages attempts to create a coherent model that binds the expressive nature of signs conveyed in gestures to a linguistic framework. Gesture modelling offers an alternative that provides device independence, scalability...

  9. Scalable synthesis and energy applications of defect engineeered nano materials

    Science.gov (United States)

    Karakaya, Mehmet

    Nanomaterials and nanotechnologies have attracted a great deal of attention in a few decades due to their novel physical properties such as, high aspect ratio, surface morphology, impurities, etc. which lead to unique chemical, optical and electronic properties. The awareness of importance of nanomaterials has motivated researchers to develop nanomaterial growth techniques to further control nanostructures properties such as, size, surface morphology, etc. that may alter their fundamental behavior. Carbon nanotubes (CNTs) are one of the most promising materials with their rigidity, strength, elasticity and electric conductivity for future applications. Despite their excellent properties explored by the abundant research works, there is big challenge to introduce them into the macroscopic world for practical applications. This thesis first gives a brief overview of the CNTs, it will then go on mechanical and oil absorption properties of macro-scale CNT assemblies, then following CNT energy storage applications and finally fundamental studies of defect introduced graphene systems. Chapter Two focuses on helically coiled carbon nanotube (HCNT) foams in compression. Similarly to other foams, HCNT foams exhibit preconditioning effects in response to cyclic loading; however, their fundamental deformation mechanisms are unique. Bulk HCNT foams exhibit super-compressibility and recover more than 90% of large compressive strains (up to 80%). When subjected to striker impacts, HCNT foams mitigate impact stresses more effectively compared to other CNT foams comprised of non-helical CNTs (~50% improvement). The unique mechanical properties we revealed demonstrate that the HCNT foams are ideally suited for applications in packaging, impact protection, and vibration mitigation. The third chapter describes a simple method for the scalable synthesis of three-dimensional, elastic, and recyclable multi-walled carbon nanotube (MWCNT) based light weight bucky-aerogels (BAGs) that are

  10. A scalable computational framework for establishing long-term behavior of stochastic reaction networks.

    Directory of Open Access Journals (Sweden)

    Ankit Gupta

    2014-06-01

    Full Text Available Reaction networks are systems in which the populations of a finite number of species evolve through predefined interactions. Such networks are found as modeling tools in many biological disciplines such as biochemistry, ecology, epidemiology, immunology, systems biology and synthetic biology. It is now well-established that, for small population sizes, stochastic models for biochemical reaction networks are necessary to capture randomness in the interactions. The tools for analyzing such models, however, still lag far behind their deterministic counterparts. In this paper, we bridge this gap by developing a constructive framework for examining the long-term behavior and stability properties of the reaction dynamics in a stochastic setting. In particular, we address the problems of determining ergodicity of the reaction dynamics, which is analogous to having a globally attracting fixed point for deterministic dynamics. We also examine when the statistical moments of the underlying process remain bounded with time and when they converge to their steady state values. The framework we develop relies on a blend of ideas from probability theory, linear algebra and optimization theory. We demonstrate that the stability properties of a wide class of biological networks can be assessed from our sufficient theoretical conditions that can be recast as efficient and scalable linear programs, well-known for their tractability. It is notably shown that the computational complexity is often linear in the number of species. We illustrate the validity, the efficiency and the wide applicability of our results on several reaction networks arising in biochemistry, systems biology, epidemiology and ecology. The biological implications of the results as well as an example of a non-ergodic biological network are also discussed.

  11. Scalable Failure Masking for Stencil Computations using Ghost Region Expansion and Cell to Rank Remapping

    International Nuclear Information System (INIS)

    Gamell, Marc; Kolla, Hemanth; Mayo, Jackson; Heroux, Michael A.

    2017-01-01

    In order to achieve exascale systems, application resilience needs to be addressed. Some programming models, such as task-DAG (directed acyclic graphs) architectures, currently embed resilience features whereas traditional SPMD (single program, multiple data) and message-passing models do not. Since a large part of the community's code base follows the latter models, it is still required to take advantage of application characteristics to minimize the overheads of fault tolerance. To that end, this paper explores how recovering from hard process/node failures in a local manner is a natural approach for certain applications to obtain resilience at lower costs in faulty environments. In particular, this paper targets enabling online, semitransparent local recovery for stencil computations on current leadership-class systems as well as presents programming support and scalable runtime mechanisms. Also described and demonstrated in this paper is the effect of failure masking, which allows the effective reduction of impact on total time to solution due to multiple failures. Furthermore, we discuss, implement, and evaluate ghost region expansion and cell-to-rank remapping to increase the probability of failure masking. To conclude, this paper shows the integration of all aforementioned mechanisms with the S3D combustion simulation through an experimental demonstration (using the Titan system) of the ability to tolerate high failure rates (i.e., node failures every five seconds) with low overhead while sustaining performance at large scales. In addition, this demonstration also displays the failure masking probability increase resulting from the combination of both ghost region expansion and cell-to-rank remapping.

  12. Trident: scalable compute archives: workflows, visualization, and analysis

    Science.gov (United States)

    Gopu, Arvind; Hayashi, Soichi; Young, Michael D.; Kotulla, Ralf; Henschel, Robert; Harbeck, Daniel

    2016-08-01

    The Astronomy scientific community has embraced Big Data processing challenges, e.g. associated with time-domain astronomy, and come up with a variety of novel and efficient data processing solutions. However, data processing is only a small part of the Big Data challenge. Efficient knowledge discovery and scientific advancement in the Big Data era requires new and equally efficient tools: modern user interfaces for searching, identifying and viewing data online without direct access to the data; tracking of data provenance; searching, plotting and analyzing metadata; interactive visual analysis, especially of (time-dependent) image data; and the ability to execute pipelines on supercomputing and cloud resources with minimal user overhead or expertise even to novice computing users. The Trident project at Indiana University offers a comprehensive web and cloud-based microservice software suite that enables the straight forward deployment of highly customized Scalable Compute Archive (SCA) systems; including extensive visualization and analysis capabilities, with minimal amount of additional coding. Trident seamlessly scales up or down in terms of data volumes and computational needs, and allows feature sets within a web user interface to be quickly adapted to meet individual project requirements. Domain experts only have to provide code or business logic about handling/visualizing their domain's data products and about executing their pipelines and application work flows. Trident's microservices architecture is made up of light-weight services connected by a REST API and/or a message bus; a web interface elements are built using NodeJS, AngularJS, and HighCharts JavaScript libraries among others while backend services are written in NodeJS, PHP/Zend, and Python. The software suite currently consists of (1) a simple work flow execution framework to integrate, deploy, and execute pipelines and applications (2) a progress service to monitor work flows and sub

  13. Constraint Solver Techniques for Implementing Precise and Scalable Static Program Analysis

    DEFF Research Database (Denmark)

    Zhang, Ye

    solver using unification we could make a program analysis easier to design and implement, much more scalable, and still as precise as expected. We present an inclusion constraint language with the explicit equality constructs for specifying program analysis problems, and a parameterized framework...... developers to build reliable software systems more quickly and with fewer bugs or security defects. While designing and implementing a program analysis remains a hard work, making it both scalable and precise is even more challenging. In this dissertation, we show that with a general inclusion constraint...... data flow analyses for C language, we demonstrate a large amount of equivalences could be detected by off-line analyses, and they could then be used by a constraint solver to significantly improve the scalability of an analysis without sacrificing any precision....

  14. Advanced technologies for scalable ATLAS conditions database access on the grid

    CERN Document Server

    Basset, R; Dimitrov, G; Girone, M; Hawkings, R; Nevski, P; Valassi, A; Vaniachine, A; Viegas, F; Walker, R; Wong, A

    2010-01-01

    During massive data reprocessing operations an ATLAS Conditions Database application must support concurrent access from numerous ATLAS data processing jobs running on the Grid. By simulating realistic work-flow, ATLAS database scalability tests provided feedback for Conditions Db software optimization and allowed precise determination of required distributed database resources. In distributed data processing one must take into account the chaotic nature of Grid computing characterized by peak loads, which can be much higher than average access rates. To validate database performance at peak loads, we tested database scalability at very high concurrent jobs rates. This has been achieved through coordinated database stress tests performed in series of ATLAS reprocessing exercises at the Tier-1 sites. The goal of database stress tests is to detect scalability limits of the hardware deployed at the Tier-1 sites, so that the server overload conditions can be safely avoided in a production environment. Our analysi...

  15. Parallel scalability and efficiency of vortex particle method for aeroelasticity analysis of bluff bodies

    Science.gov (United States)

    Tolba, Khaled Ibrahim; Morgenthal, Guido

    2018-01-01

    This paper presents an analysis of the scalability and efficiency of a simulation framework based on the vortex particle method. The code is applied for the numerical aerodynamic analysis of line-like structures. The numerical code runs on multicore CPU and GPU architectures using OpenCL framework. The focus of this paper is the analysis of the parallel efficiency and scalability of the method being applied to an engineering test case, specifically the aeroelastic response of a long-span bridge girder at the construction stage. The target is to assess the optimal configuration and the required computer architecture, such that it becomes feasible to efficiently utilise the method within the computational resources available for a regular engineering office. The simulations and the scalability analysis are performed on a regular gaming type computer.

  16. Scalable architecture for a room temperature solid-state quantum information processor.

    Science.gov (United States)

    Yao, N Y; Jiang, L; Gorshkov, A V; Maurer, P C; Giedke, G; Cirac, J I; Lukin, M D

    2012-04-24

    The realization of a scalable quantum information processor has emerged over the past decade as one of the central challenges at the interface of fundamental science and engineering. Here we propose and analyse an architecture for a scalable, solid-state quantum information processor capable of operating at room temperature. Our approach is based on recent experimental advances involving nitrogen-vacancy colour centres in diamond. In particular, we demonstrate that the multiple challenges associated with operation at ambient temperature, individual addressing at the nanoscale, strong qubit coupling, robustness against disorder and low decoherence rates can be simultaneously achieved under realistic, experimentally relevant conditions. The architecture uses a novel approach to quantum information transfer and includes a hierarchy of control at successive length scales. Moreover, it alleviates the stringent constraints currently limiting the realization of scalable quantum processors and will provide fundamental insights into the physics of non-equilibrium many-body quantum systems.

  17. Asynchronous Checkpoint Migration with MRNet in the Scalable Checkpoint / Restart Library

    Energy Technology Data Exchange (ETDEWEB)

    Mohror, K; Moody, A; de Supinski, B R

    2012-03-20

    Applications running on today's supercomputers tolerate failures by periodically saving their state in checkpoint files on stable storage, such as a parallel file system. Although this approach is simple, the overhead of writing the checkpoints can be prohibitive, especially for large-scale jobs. In this paper, we present initial results of an enhancement to our Scalable Checkpoint/Restart Library (SCR). We employ MRNet, a tree-based overlay network library, to transfer checkpoints from the compute nodes to the parallel file system asynchronously. This enhancement increases application efficiency by removing the need for an application to block while checkpoints are transferred to the parallel file system. We show that the integration of SCR with MRNet can reduce the time spent in I/O operations by as much as 15x. However, our experiments exposed new scalability issues with our initial implementation. We discuss the sources of the scalability problems and our plans to address them.

  18. Impact of multiplexed reading scheme on nanocrossbar memristor memory's scalability

    International Nuclear Information System (INIS)

    Zhu Xuan; Tang Yu-Hua; Wu Jun-Jie; Yi Xun; Wu Chun-Qing

    2014-01-01

    Nanocrossbar is a potential memory architecture to integrate memristor to achieve large scale and high density memory. However, based on the currently widely-adopted parallel reading scheme, scalability of the nanocrossbar memory is limited, since the overhead of the reading circuits is in proportion with the size of the nanocrossbar component. In this paper, a multiplexed reading scheme is adopted as the foundation of the discussion. Through HSPICE simulation, we reanalyze scalability of the nanocrossbar memristor memory by investigating the impact of various circuit parameters on the output voltage swing as the memory scales to larger size. We find that multiplexed reading maintains sufficient noise margin in large size nanocrossbar memristor memory. In order to improve the scalability of the memory, memristors with nonlinear I—V characteristics and high LRS (low resistive state) resistance should be adopted. (interdisciplinary physics and related areas of science and technology)

  19. Scalable Motion Estimation Processor Core for Multimedia System-on-Chip Applications

    Science.gov (United States)

    Lai, Yeong-Kang; Hsieh, Tian-En; Chen, Lien-Fei

    2007-04-01

    In this paper, we describe a high-throughput and scalable motion estimation processor architecture for multimedia system-on-chip applications. The number of processing elements (PEs) is scalable according to the variable algorithm parameters and the performance required for different applications. Using the PE rings efficiently and an intelligent memory-interleaving organization, the efficiency of the architecture can be increased. Moreover, using efficient on-chip memories and a data management technique can effectively decrease the power consumption and memory bandwidth. Techniques for reducing the number of interconnections and external memory accesses are also presented. Our results demonstrate that the proposed scalable PE-ringed architecture is a flexible and high-performance processor core in multimedia system-on-chip applications.

  20. Development of an Efficient GPU-Accelerated Model for Fully Nonlinear Water Waves

    DEFF Research Database (Denmark)

    of an optimized sequential single-CPU algorithm based on a flexible-order Finite Difference Method. High performance is pursued by utilizing many-core processing in the model focusing on GPUs for acceleration of code execution. This involves combining analytical methods with an algorithm redesign of the current...