High-performance computing — an overview

Science.gov (United States)

Marksteiner, Peter

1996-08-01

An overview of high-performance computing (HPC) is given. Different types of computer architectures used in HPC are discussed: vector supercomputers, high-performance RISC processors, various parallel computers like symmetric multiprocessors, workstation clusters, massively parallel processors. Software tools and programming techniques used in HPC are reviewed: vectorizing compilers, optimization and vector tuning, optimization for RISC processors; parallel programming techniques like shared-memory parallelism, message passing and data parallelism; and numerical libraries.

Software Systems for High-performance Quantum Computing

Energy Technology Data Exchange (ETDEWEB)

Humble, Travis S [ORNL; Britt, Keith A [ORNL

2016-01-01

Quantum computing promises new opportunities for solving hard computational problems, but harnessing this novelty requires breakthrough concepts in the design, operation, and application of computing systems. We define some of the challenges facing the development of quantum computing systems as well as software-based approaches that can be used to overcome these challenges. Following a brief overview of the state of the art, we present models for the quantum programming and execution models, the development of architectures for hybrid high-performance computing systems, and the realization of software stacks for quantum networking. This leads to a discussion of the role that conventional computing plays in the quantum paradigm and how some of the current challenges for exascale computing overlap with those facing quantum computing.

High Performance Computing in Science and Engineering '16 : Transactions of the High Performance Computing Center, Stuttgart (HLRS) 2016

CERN Document Server

Kröner, Dietmar; Resch, Michael

2016-01-01

This book presents the state-of-the-art in supercomputer simulation. It includes the latest findings from leading researchers using systems from the High Performance Computing Center Stuttgart (HLRS) in 2016. The reports cover all fields of computational science and engineering ranging from CFD to computational physics and from chemistry to computer science with a special emphasis on industrially relevant applications. Presenting findings of one of Europe’s leading systems, this volume covers a wide variety of applications that deliver a high level of sustained performance. The book covers the main methods in high-performance computing. Its outstanding results in achieving the best performance for production codes are of particular interest for both scientists and engineers. The book comes with a wealth of color illustrations and tables of results.

High-performance computing in seismology

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-09-01

The scientific, technical, and economic importance of the issues discussed here presents a clear agenda for future research in computational seismology. In this way these problems will drive advances in high-performance computing in the field of seismology. There is a broad community that will benefit from this work, including the petroleum industry, research geophysicists, engineers concerned with seismic hazard mitigation, and governments charged with enforcing a comprehensive test ban treaty. These advances may also lead to new applications for seismological research. The recent application of high-resolution seismic imaging of the shallow subsurface for the environmental remediation industry is an example of this activity. This report makes the following recommendations: (1) focused efforts to develop validated documented software for seismological computations should be supported, with special emphasis on scalable algorithms for parallel processors; (2) the education of seismologists in high-performance computing technologies and methodologies should be improved; (3) collaborations between seismologists and computational scientists and engineers should be increased; (4) the infrastructure for archiving, disseminating, and processing large volumes of seismological data should be improved.

High performance computing in Windows Azure cloud

OpenAIRE

Ambruš, Dejan

2013-01-01

High performance, security, availability, scalability, flexibility and lower costs of maintenance have essentially contributed to the growing popularity of cloud computing in all spheres of life, especially in business. In fact cloud computing offers even more than this. With usage of virtual computing clusters a runtime environment for high performance computing can be efficiently implemented also in a cloud. There are many advantages but also some disadvantages of cloud computing, some ...

A Heterogeneous High-Performance System for Computational and Computer Science

Science.gov (United States)

2016-11-15

expand the research infrastructure at the institution but also to enhance the high -performance computing training provided to both undergraduate and... cloud computing, supercomputing, and the availability of cheap memory and storage led to enormous amounts of data to be sifted through in forensic... High -Performance Computing (HPC) tools that can be integrated with existing curricula and support our research to modernize and dramatically advance

Quantum Accelerators for High-performance Computing Systems

Energy Technology Data Exchange (ETDEWEB)

Humble, Travis S. [ORNL; Britt, Keith A. [ORNL; Mohiyaddin, Fahd A. [ORNL

2017-11-01

We define some of the programming and system-level challenges facing the application of quantum processing to high-performance computing. Alongside barriers to physical integration, prominent differences in the execution of quantum and conventional programs challenges the intersection of these computational models. Following a brief overview of the state of the art, we discuss recent advances in programming and execution models for hybrid quantum-classical computing. We discuss a novel quantum-accelerator framework that uses specialized kernels to offload select workloads while integrating with existing computing infrastructure. We elaborate on the role of the host operating system to manage these unique accelerator resources, the prospects for deploying quantum modules, and the requirements placed on the language hierarchy connecting these different system components. We draw on recent advances in the modeling and simulation of quantum computing systems with the development of architectures for hybrid high-performance computing systems and the realization of software stacks for controlling quantum devices. Finally, we present simulation results that describe the expected system-level behavior of high-performance computing systems composed from compute nodes with quantum processing units. We describe performance for these hybrid systems in terms of time-to-solution, accuracy, and energy consumption, and we use simple application examples to estimate the performance advantage of quantum acceleration.

Contemporary high performance computing from petascale toward exascale

CERN Document Server

Vetter, Jeffrey S

2013-01-01

Contemporary High Performance Computing: From Petascale toward Exascale focuses on the ecosystems surrounding the world's leading centers for high performance computing (HPC). It covers many of the important factors involved in each ecosystem: computer architectures, software, applications, facilities, and sponsors. The first part of the book examines significant trends in HPC systems, including computer architectures, applications, performance, and software. It discusses the growth from terascale to petascale computing and the influence of the TOP500 and Green500 lists. The second part of the

High Performance Computing in Science and Engineering '14

CERN Document Server

Kröner, Dietmar; Resch, Michael

2015-01-01

This book presents the state-of-the-art in supercomputer simulation. It includes the latest findings from leading researchers using systems from the High Performance Computing Center Stuttgart (HLRS). The reports cover all fields of computational science and engineering ranging from CFD to computational physics and from chemistry to computer science with a special emphasis on industrially relevant applications. Presenting findings of one of Europe’s leading systems, this volume covers a wide variety of applications that deliver a high level of sustained performance. The book covers the main methods in high-performance computing. Its outstanding results in achieving the best performance for production codes are of particular interest for both scientists and   engineers. The book comes with a wealth of color illustrations and tables of results.  

High-performance computing in accelerating structure design and analysis

International Nuclear Information System (INIS)

Li Zenghai; Folwell, Nathan; Ge Lixin; Guetz, Adam; Ivanov, Valentin; Kowalski, Marc; Lee, Lie-Quan; Ng, Cho-Kuen; Schussman, Greg; Stingelin, Lukas; Uplenchwar, Ravindra; Wolf, Michael; Xiao, Liling; Ko, Kwok

2006-01-01

Future high-energy accelerators such as the Next Linear Collider (NLC) will accelerate multi-bunch beams of high current and low emittance to obtain high luminosity, which put stringent requirements on the accelerating structures for efficiency and beam stability. While numerical modeling has been quite standard in accelerator R and D, designing the NLC accelerating structure required a new simulation capability because of the geometric complexity and level of accuracy involved. Under the US DOE Advanced Computing initiatives (first the Grand Challenge and now SciDAC), SLAC has developed a suite of electromagnetic codes based on unstructured grids and utilizing high-performance computing to provide an advanced tool for modeling structures at accuracies and scales previously not possible. This paper will discuss the code development and computational science research (e.g. domain decomposition, scalable eigensolvers, adaptive mesh refinement) that have enabled the large-scale simulations needed for meeting the computational challenges posed by the NLC as well as projects such as the PEP-II and RIA. Numerical results will be presented to show how high-performance computing has made a qualitative improvement in accelerator structure modeling for these accelerators, either at the component level (single cell optimization), or on the scale of an entire structure (beam heating and long-range wakefields)

High-performance computing for airborne applications

International Nuclear Information System (INIS)

Quinn, Heather M.; Manuzatto, Andrea; Fairbanks, Tom; Dallmann, Nicholas; Desgeorges, Rose

2010-01-01

Recently, there has been attempts to move common satellite tasks to unmanned aerial vehicles (UAVs). UAVs are significantly cheaper to buy than satellites and easier to deploy on an as-needed basis. The more benign radiation environment also allows for an aggressive adoption of state-of-the-art commercial computational devices, which increases the amount of data that can be collected. There are a number of commercial computing devices currently available that are well-suited to high-performance computing. These devices range from specialized computational devices, such as field-programmable gate arrays (FPGAs) and digital signal processors (DSPs), to traditional computing platforms, such as microprocessors. Even though the radiation environment is relatively benign, these devices could be susceptible to single-event effects. In this paper, we will present radiation data for high-performance computing devices in a accelerated neutron environment. These devices include a multi-core digital signal processor, two field-programmable gate arrays, and a microprocessor. From these results, we found that all of these devices are suitable for many airplane environments without reliability problems.

ABINIT: Plane-Wave-Based Density-Functional Theory on High Performance Computers

Science.gov (United States)

Torrent, Marc

2014-03-01

For several years, a continuous effort has been produced to adapt electronic structure codes based on Density-Functional Theory to the future computing architectures. Among these codes, ABINIT is based on a plane-wave description of the wave functions which allows to treat systems of any kind. Porting such a code on petascale architectures pose difficulties related to the many-body nature of the DFT equations. To improve the performances of ABINIT - especially for what concerns standard LDA/GGA ground-state and response-function calculations - several strategies have been followed: A full multi-level parallelisation MPI scheme has been implemented, exploiting all possible levels and distributing both computation and memory. It allows to increase the number of distributed processes and could not be achieved without a strong restructuring of the code. The core algorithm used to solve the eigen problem (``Locally Optimal Blocked Congugate Gradient''), a Blocked-Davidson-like algorithm, is based on a distribution of processes combining plane-waves and bands. In addition to the distributed memory parallelization, a full hybrid scheme has been implemented, using standard shared-memory directives (openMP/openACC) or porting some comsuming code sections to Graphics Processing Units (GPU). As no simple performance model exists, the complexity of use has been increased; the code efficiency strongly depends on the distribution of processes among the numerous levels. ABINIT is able to predict the performances of several process distributions and automatically choose the most favourable one. On the other hand, a big effort has been carried out to analyse the performances of the code on petascale architectures, showing which sections of codes have to be improved; they all are related to Matrix Algebra (diagonalisation, orthogonalisation). The different strategies employed to improve the code scalability will be described. They are based on an exploration of new diagonalization

Department of Energy research in utilization of high-performance computers

International Nuclear Information System (INIS)

Buzbee, B.L.; Worlton, W.J.; Michael, G.; Rodrigue, G.

1980-08-01

Department of Energy (DOE) and other Government research laboratories depend on high-performance computer systems to accomplish their programmatic goals. As the most powerful computer systems become available, they are acquired by these laboratories so that advances can be made in their disciplines. These advances are often the result of added sophistication to numerical models, the execution of which is made possible by high-performance computer systems. However, high-performance computer systems have become increasingly complex, and consequently it has become increasingly difficult to realize their potential performance. The result is a need for research on issues related to the utilization of these systems. This report gives a brief description of high-performance computers, and then addresses the use of and future needs for high-performance computers within DOE, the growing complexity of applications within DOE, and areas of high-performance computer systems warranting research. 1 figure

Benchmarking high performance computing architectures with CMS’ skeleton framework

Science.gov (United States)

Sexton-Kennedy, E.; Gartung, P.; Jones, C. D.

2017-10-01

In 2012 CMS evaluated which underlying concurrency technology would be the best to use for its multi-threaded framework. The available technologies were evaluated on the high throughput computing systems dominating the resources in use at that time. A skeleton framework benchmarking suite that emulates the tasks performed within a CMSSW application was used to select Intel’s Thread Building Block library, based on the measured overheads in both memory and CPU on the different technologies benchmarked. In 2016 CMS will get access to high performance computing resources that use new many core architectures; machines such as Cori Phase 1&2, Theta, Mira. Because of this we have revived the 2012 benchmark to test it’s performance and conclusions on these new architectures. This talk will discuss the results of this exercise.

Optical interconnection networks for high-performance computing systems

International Nuclear Information System (INIS)

Biberman, Aleksandr; Bergman, Keren

2012-01-01

Enabled by silicon photonic technology, optical interconnection networks have the potential to be a key disruptive technology in computing and communication industries. The enduring pursuit of performance gains in computing, combined with stringent power constraints, has fostered the ever-growing computational parallelism associated with chip multiprocessors, memory systems, high-performance computing systems and data centers. Sustaining these parallelism growths introduces unique challenges for on- and off-chip communications, shifting the focus toward novel and fundamentally different communication approaches. Chip-scale photonic interconnection networks, enabled by high-performance silicon photonic devices, offer unprecedented bandwidth scalability with reduced power consumption. We demonstrate that the silicon photonic platforms have already produced all the high-performance photonic devices required to realize these types of networks. Through extensive empirical characterization in much of our work, we demonstrate such feasibility of waveguides, modulators, switches and photodetectors. We also demonstrate systems that simultaneously combine many functionalities to achieve more complex building blocks. We propose novel silicon photonic devices, subsystems, network topologies and architectures to enable unprecedented performance of these photonic interconnection networks. Furthermore, the advantages of photonic interconnection networks extend far beyond the chip, offering advanced communication environments for memory systems, high-performance computing systems, and data centers. (review article)

A high performance scientific cloud computing environment for materials simulations

Science.gov (United States)

Jorissen, K.; Vila, F. D.; Rehr, J. J.

2012-09-01

We describe the development of a scientific cloud computing (SCC) platform that offers high performance computation capability. The platform consists of a scientific virtual machine prototype containing a UNIX operating system and several materials science codes, together with essential interface tools (an SCC toolset) that offers functionality comparable to local compute clusters. In particular, our SCC toolset provides automatic creation of virtual clusters for parallel computing, including tools for execution and monitoring performance, as well as efficient I/O utilities that enable seamless connections to and from the cloud. Our SCC platform is optimized for the Amazon Elastic Compute Cloud (EC2). We present benchmarks for prototypical scientific applications and demonstrate performance comparable to local compute clusters. To facilitate code execution and provide user-friendly access, we have also integrated cloud computing capability in a JAVA-based GUI. Our SCC platform may be an alternative to traditional HPC resources for materials science or quantum chemistry applications.

Debugging a high performance computing program

Science.gov (United States)

Gooding, Thomas M.

2013-08-20

Methods, apparatus, and computer program products are disclosed for debugging a high performance computing program by gathering lists of addresses of calling instructions for a plurality of threads of execution of the program, assigning the threads to groups in dependence upon the addresses, and displaying the groups to identify defective threads.

High-performance scientific computing in the cloud

Science.gov (United States)

Jorissen, Kevin; Vila, Fernando; Rehr, John

2011-03-01

Cloud computing has the potential to open up high-performance computational science to a much broader class of researchers, owing to its ability to provide on-demand, virtualized computational resources. However, before such approaches can become commonplace, user-friendly tools must be developed that hide the unfamiliar cloud environment and streamline the management of cloud resources for many scientific applications. We have recently shown that high-performance cloud computing is feasible for parallelized x-ray spectroscopy calculations. We now present benchmark results for a wider selection of scientific applications focusing on electronic structure and spectroscopic simulation software in condensed matter physics. These applications are driven by an improved portable interface that can manage virtual clusters and run various applications in the cloud. We also describe a next generation of cluster tools, aimed at improved performance and a more robust cluster deployment. Supported by NSF grant OCI-1048052.

Research Activity in Computational Physics utilizing High Performance Computing: Co-authorship Network Analysis

Science.gov (United States)

Ahn, Sul-Ah; Jung, Youngim

2016-10-01

The research activities of the computational physicists utilizing high performance computing are analyzed by bibliometirc approaches. This study aims at providing the computational physicists utilizing high-performance computing and policy planners with useful bibliometric results for an assessment of research activities. In order to achieve this purpose, we carried out a co-authorship network analysis of journal articles to assess the research activities of researchers for high-performance computational physics as a case study. For this study, we used journal articles of the Scopus database from Elsevier covering the time period of 2004-2013. We extracted the author rank in the physics field utilizing high-performance computing by the number of papers published during ten years from 2004. Finally, we drew the co-authorship network for 45 top-authors and their coauthors, and described some features of the co-authorship network in relation to the author rank. Suggestions for further studies are discussed.

Performance of particle in cell methods on highly concurrent computational architectures

International Nuclear Information System (INIS)

Adams, M.F.; Ethier, S.; Wichmann, N.

2009-01-01

Particle in cell (PIC) methods are effective in computing Vlasov-Poisson system of equations used in simulations of magnetic fusion plasmas. PIC methods use grid based computations, for solving Poisson's equation or more generally Maxwell's equations, as well as Monte-Carlo type methods to sample the Vlasov equation. The presence of two types of discretizations, deterministic field solves and Monte-Carlo methods for the Vlasov equation, pose challenges in understanding and optimizing performance on today large scale computers which require high levels of concurrency. These challenges arises from the need to optimize two very different types of processes and the interactions between them. Modern cache based high-end computers have very deep memory hierarchies and high degrees of concurrency which must be utilized effectively to achieve good performance. The effective use of these machines requires maximizing concurrency by eliminating serial or redundant work and minimizing global communication. A related issue is minimizing the memory traffic between levels of the memory hierarchy because performance is often limited by the bandwidths and latencies of the memory system. This paper discusses some of the performance issues, particularly in regard to parallelism, of PIC methods. The gyrokinetic toroidal code (GTC) is used for these studies and a new radial grid decomposition is presented and evaluated. Scaling of the code is demonstrated on ITER sized plasmas with up to 16K Cray XT3/4 cores.

Performance of particle in cell methods on highly concurrent computational architectures

International Nuclear Information System (INIS)

Adams, M F; Ethier, S; Wichmann, N

2007-01-01

Particle in cell (PIC) methods are effective in computing Vlasov-Poisson system of equations used in simulations of magnetic fusion plasmas. PIC methods use grid based computations, for solving Poisson's equation or more generally Maxwell's equations, as well as Monte-Carlo type methods to sample the Vlasov equation. The presence of two types of discretizations, deterministic field solves and Monte-Carlo methods for the Vlasov equation, pose challenges in understanding and optimizing performance on today large scale computers which require high levels of concurrency. These challenges arises from the need to optimize two very different types of processes and the interactions between them. Modern cache based high-end computers have very deep memory hierarchies and high degrees of concurrency which must be utilized effectively to achieve good performance. The effective use of these machines requires maximizing concurrency by eliminating serial or redundant work and minimizing global communication. A related issue is minimizing the memory traffic between levels of the memory hierarchy because performance is often limited by the bandwidths and latencies of the memory system. This paper discusses some of the performance issues, particularly in regard to parallelism, of PIC methods. The gyrokinetic toroidal code (GTC) is used for these studies and a new radial grid decomposition is presented and evaluated. Scaling of the code is demonstrated on ITER sized plasmas with up to 16K Cray XT3/4 cores

Implementing an Affordable High-Performance Computing for Teaching-Oriented Computer Science Curriculum

Science.gov (United States)

Abuzaghleh, Omar; Goldschmidt, Kathleen; Elleithy, Yasser; Lee, Jeongkyu

2013-01-01

With the advances in computing power, high-performance computing (HPC) platforms have had an impact on not only scientific research in advanced organizations but also computer science curriculum in the educational community. For example, multicore programming and parallel systems are highly desired courses in the computer science major. However,…

High performance graphics processor based computed tomography reconstruction algorithms for nuclear and other large scale applications.

Energy Technology Data Exchange (ETDEWEB)

Jimenez, Edward S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Orr, Laurel J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Thompson, Kyle R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2013-09-01

The goal of this work is to develop a fast computed tomography (CT) reconstruction algorithm based on graphics processing units (GPU) that achieves significant improvement over traditional central processing unit (CPU) based implementations. The main challenge in developing a CT algorithm that is capable of handling very large datasets is parallelizing the algorithm in such a way that data transfer does not hinder performance of the reconstruction algorithm. General Purpose Graphics Processing (GPGPU) is a new technology that the Science and Technology (S&T) community is starting to adopt in many fields where CPU-based computing is the norm. GPGPU programming requires a new approach to algorithm development that utilizes massively multi-threaded environments. Multi-threaded algorithms in general are difficult to optimize since performance bottlenecks occur that are non-existent in single-threaded algorithms such as memory latencies. If an efficient GPU-based CT reconstruction algorithm can be developed; computational times could be improved by a factor of 20. Additionally, cost benefits will be realized as commodity graphics hardware could potentially replace expensive supercomputers and high-end workstations. This project will take advantage of the CUDA programming environment and attempt to parallelize the task in such a way that multiple slices of the reconstruction volume are computed simultaneously. This work will also take advantage of the GPU memory by utilizing asynchronous memory transfers, GPU texture memory, and (when possible) pinned host memory so that the memory transfer bottleneck inherent to GPGPU is amortized. Additionally, this work will take advantage of GPU-specific hardware (i.e. fast texture memory, pixel-pipelines, hardware interpolators, and varying memory hierarchy) that will allow for additional performance improvements.

High-performance computing on GPUs for resistivity logging of oil and gas wells

Science.gov (United States)

Glinskikh, V.; Dudaev, A.; Nechaev, O.; Surodina, I.

2017-10-01

We developed and implemented into software an algorithm for high-performance simulation of electrical logs from oil and gas wells using high-performance heterogeneous computing. The numerical solution of the 2D forward problem is based on the finite-element method and the Cholesky decomposition for solving a system of linear algebraic equations (SLAE). Software implementations of the algorithm used the NVIDIA CUDA technology and computing libraries are made, allowing us to perform decomposition of SLAE and find its solution on central processor unit (CPU) and graphics processor unit (GPU). The calculation time is analyzed depending on the matrix size and number of its non-zero elements. We estimated the computing speed on CPU and GPU, including high-performance heterogeneous CPU-GPU computing. Using the developed algorithm, we simulated resistivity data in realistic models.

High performance parallel computers for science

International Nuclear Information System (INIS)

Nash, T.; Areti, H.; Atac, R.; Biel, J.; Cook, A.; Deppe, J.; Edel, M.; Fischler, M.; Gaines, I.; Hance, R.

1989-01-01

This paper reports that Fermilab's Advanced Computer Program (ACP) has been developing cost effective, yet practical, parallel computers for high energy physics since 1984. The ACP's latest developments are proceeding in two directions. A Second Generation ACP Multiprocessor System for experiments will include $3500 RISC processors each with performance over 15 VAX MIPS. To support such high performance, the new system allows parallel I/O, parallel interprocess communication, and parallel host processes. The ACP Multi-Array Processor, has been developed for theoretical physics. Each $4000 node is a FORTRAN or C programmable pipelined 20 Mflops (peak), 10 MByte single board computer. These are plugged into a 16 port crossbar switch crate which handles both inter and intra crate communication. The crates are connected in a hypercube. Site oriented applications like lattice gauge theory are supported by system software called CANOPY, which makes the hardware virtually transparent to users. A 256 node, 5 GFlop, system is under construction

Energy Efficiency Experiments on Samsung Exynos 5 Heterogeneous Multicore using OmpSs Task Based Programming

OpenAIRE

Holmgren, Rune

2015-01-01

This thesis explore the energy efficiency of task based programming with OpenMP SuperScalar (OmpSs) on the heterogeneous Samsung Exynos 5422 system on a chip. The system features small energy efficient cores, large high performance cores and a GPGPU, and OmpSs tasks were run on all three different processors. Experiments running a genetic algorithm and a Cholesky decomposition were used to gather results. The option of running applications on the energy efficient cores, on the high perfo...

Resilient and Robust High Performance Computing Platforms for Scientific Computing Integrity

Energy Technology Data Exchange (ETDEWEB)

Jin, Yier [Univ. of Central Florida, Orlando, FL (United States)

2017-07-14

As technology advances, computer systems are subject to increasingly sophisticated cyber-attacks that compromise both their security and integrity. High performance computing platforms used in commercial and scientific applications involving sensitive, or even classified data, are frequently targeted by powerful adversaries. This situation is made worse by a lack of fundamental security solutions that both perform efficiently and are effective at preventing threats. Current security solutions fail to address the threat landscape and ensure the integrity of sensitive data. As challenges rise, both private and public sectors will require robust technologies to protect its computing infrastructure. The research outcomes from this project try to address all these challenges. For example, we present LAZARUS, a novel technique to harden kernel Address Space Layout Randomization (KASLR) against paging-based side-channel attacks. In particular, our scheme allows for fine-grained protection of the virtual memory mappings that implement the randomization. We demonstrate the effectiveness of our approach by hardening a recent Linux kernel with LAZARUS, mitigating all of the previously presented side-channel attacks on KASLR. Our extensive evaluation shows that LAZARUS incurs only 0.943% overhead for standard benchmarks, and is therefore highly practical. We also introduced HA2lloc, a hardware-assisted allocator that is capable of leveraging an extended memory management unit to detect memory errors in the heap. We also perform testing using HA2lloc in a simulation environment and find that the approach is capable of preventing common memory vulnerabilities.

High Performance Numerical Computing for High Energy Physics: A New Challenge for Big Data Science

International Nuclear Information System (INIS)

Pop, Florin

2014-01-01

Modern physics is based on both theoretical analysis and experimental validation. Complex scenarios like subatomic dimensions, high energy, and lower absolute temperature are frontiers for many theoretical models. Simulation with stable numerical methods represents an excellent instrument for high accuracy analysis, experimental validation, and visualization. High performance computing support offers possibility to make simulations at large scale, in parallel, but the volume of data generated by these experiments creates a new challenge for Big Data Science. This paper presents existing computational methods for high energy physics (HEP) analyzed from two perspectives: numerical methods and high performance computing. The computational methods presented are Monte Carlo methods and simulations of HEP processes, Markovian Monte Carlo, unfolding methods in particle physics, kernel estimation in HEP, and Random Matrix Theory used in analysis of particles spectrum. All of these methods produce data-intensive applications, which introduce new challenges and requirements for ICT systems architecture, programming paradigms, and storage capabilities.

High Performance Computing in Science and Engineering '99 : Transactions of the High Performance Computing Center

CERN Document Server

Jäger, Willi

2000-01-01

The book contains reports about the most significant projects from science and engineering of the Federal High Performance Computing Center Stuttgart (HLRS). They were carefully selected in a peer-review process and are showcases of an innovative combination of state-of-the-art modeling, novel algorithms and the use of leading-edge parallel computer technology. The projects of HLRS are using supercomputer systems operated jointly by university and industry and therefore a special emphasis has been put on the industrial relevance of results and methods.

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...

A checkpoint compression study for high-performance computing systems

Energy Technology Data Exchange (ETDEWEB)

Ibtesham, Dewan [Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Computer Science; Ferreira, Kurt B. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States). Scalable System Software Dept.; Arnold, Dorian [Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Computer Science

2015-02-17

As high-performance computing systems continue to increase in size and complexity, higher failure rates and increased overheads for checkpoint/restart (CR) protocols have raised concerns about the practical viability of CR protocols for future systems. Previously, compression has proven to be a viable approach for reducing checkpoint data volumes and, thereby, reducing CR protocol overhead leading to improved application performance. In this article, we further explore compression-based CR optimization by exploring its baseline performance and scaling properties, evaluating whether improved compression algorithms might lead to even better application performance and comparing checkpoint compression against and alongside other software- and hardware-based optimizations. Our results highlights are: (1) compression is a very viable CR optimization; (2) generic, text-based compression algorithms appear to perform near optimally for checkpoint data compression and faster compression algorithms will not lead to better application performance; (3) compression-based optimizations fare well against and alongside other software-based optimizations; and (4) while hardware-based optimizations outperform software-based ones, they are not as cost effective.

NCI's High Performance Computing (HPC) and High Performance Data (HPD) Computing Platform for Environmental and Earth System Data Science

Science.gov (United States)

Evans, Ben; Allen, Chris; Antony, Joseph; Bastrakova, Irina; Gohar, Kashif; Porter, David; Pugh, Tim; Santana, Fabiana; Smillie, Jon; Trenham, Claire; Wang, Jingbo; Wyborn, Lesley

2015-04-01

The National Computational Infrastructure (NCI) has established a powerful and flexible in-situ petascale computational environment to enable both high performance computing and Data-intensive Science across a wide spectrum of national environmental and earth science data collections - in particular climate, observational data and geoscientific assets. This paper examines 1) the computational environments that supports the modelling and data processing pipelines, 2) the analysis environments and methods to support data analysis, and 3) the progress so far to harmonise the underlying data collections for future interdisciplinary research across these large volume data collections. NCI has established 10+ PBytes of major national and international data collections from both the government and research sectors based on six themes: 1) weather, climate, and earth system science model simulations, 2) marine and earth observations, 3) geosciences, 4) terrestrial ecosystems, 5) water and hydrology, and 6) astronomy, social and biosciences. Collectively they span the lithosphere, crust, biosphere, hydrosphere, troposphere, and stratosphere. The data is largely sourced from NCI's partners (which include the custodians of many of the major Australian national-scale scientific collections), leading research communities, and collaborating overseas organisations. New infrastructures created at NCI mean the data collections are now accessible within an integrated High Performance Computing and Data (HPC-HPD) environment - a 1.2 PFlop supercomputer (Raijin), a HPC class 3000 core OpenStack cloud system and several highly connected large-scale high-bandwidth Lustre filesystems. The hardware was designed at inception to ensure that it would allow the layered software environment to flexibly accommodate the advancement of future data science. New approaches to software technology and data models have also had to be developed to enable access to these large and exponentially

Human Computer Music Performance

OpenAIRE

Dannenberg, Roger B.

2012-01-01

Human Computer Music Performance (HCMP) is the study of music performance by live human performers and real-time computer-based performers. One goal of HCMP is to create a highly autonomous artificial performer that can fill the role of a human, especially in a popular music setting. This will require advances in automated music listening and understanding, new representations for music, techniques for music synchronization, real-time human-computer communication, music generation, sound synt...

High Performance Computing in Science and Engineering '98 : Transactions of the High Performance Computing Center

CERN Document Server

Jäger, Willi

1999-01-01

The book contains reports about the most significant projects from science and industry that are using the supercomputers of the Federal High Performance Computing Center Stuttgart (HLRS). These projects are from different scientific disciplines, with a focus on engineering, physics and chemistry. They were carefully selected in a peer-review process and are showcases for an innovative combination of state-of-the-art physical modeling, novel algorithms and the use of leading-edge parallel computer technology. As HLRS is in close cooperation with industrial companies, special emphasis has been put on the industrial relevance of results and methods.

High-Performance Java Codes for Computational Fluid Dynamics

Science.gov (United States)

Riley, Christopher; Chatterjee, Siddhartha; Biswas, Rupak; Biegel, Bryan (Technical Monitor)

2001-01-01

The computational science community is reluctant to write large-scale computationally -intensive applications in Java due to concerns over Java's poor performance, despite the claimed software engineering advantages of its object-oriented features. Naive Java implementations of numerical algorithms can perform poorly compared to corresponding Fortran or C implementations. To achieve high performance, Java applications must be designed with good performance as a primary goal. This paper presents the object-oriented design and implementation of two real-world applications from the field of Computational Fluid Dynamics (CFD): a finite-volume fluid flow solver (LAURA, from NASA Langley Research Center), and an unstructured mesh adaptation algorithm (2D_TAG, from NASA Ames Research Center). This work builds on our previous experience with the design of high-performance numerical libraries in Java. We examine the performance of the applications using the currently available Java infrastructure and show that the Java version of the flow solver LAURA performs almost within a factor of 2 of the original procedural version. Our Java version of the mesh adaptation algorithm 2D_TAG performs within a factor of 1.5 of its original procedural version on certain platforms. Our results demonstrate that object-oriented software design principles are not necessarily inimical to high performance.

Can We Build a Truly High Performance Computer Which is Flexible and Transparent?

KAUST Repository

Rojas, Jhonathan Prieto

2013-09-10

State-of-the art computers need high performance transistors, which consume ultra-low power resulting in longer battery lifetime. Billions of transistors are integrated neatly using matured silicon fabrication process to maintain the performance per cost advantage. In that context, low-cost mono-crystalline bulk silicon (100) based high performance transistors are considered as the heart of today\\'s computers. One limitation is silicon\\'s rigidity and brittleness. Here we show a generic batch process to convert high performance silicon electronics into flexible and semi-transparent one while retaining its performance, process compatibility, integration density and cost. We demonstrate high-k/metal gate stack based p-type metal oxide semiconductor field effect transistors on 4 inch silicon fabric released from bulk silicon (100) wafers with sub-threshold swing of 80 mV dec(-1) and on/off ratio of near 10(4) within 10% device uniformity with a minimum bending radius of 5 mm and an average transmittance of similar to 7% in the visible spectrum.

Quantum Accelerators for High-Performance Computing Systems

OpenAIRE

Britt, Keith A.; Mohiyaddin, Fahd A.; Humble, Travis S.

2017-01-01

We define some of the programming and system-level challenges facing the application of quantum processing to high-performance computing. Alongside barriers to physical integration, prominent differences in the execution of quantum and conventional programs challenges the intersection of these computational models. Following a brief overview of the state of the art, we discuss recent advances in programming and execution models for hybrid quantum-classical computing. We discuss a novel quantu...

Visualization and Data Analysis for High-Performance Computing

Energy Technology Data Exchange (ETDEWEB)

Sewell, Christopher Meyer [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-09-27

This is a set of slides from a guest lecture for a class at the University of Texas, El Paso on visualization and data analysis for high-performance computing. The topics covered are the following: trends in high-performance computing; scientific visualization, such as OpenGL, ray tracing and volume rendering, VTK, and ParaView; data science at scale, such as in-situ visualization, image databases, distributed memory parallelism, shared memory parallelism, VTK-m, "big data", and then an analysis example.

An Interactive, Web-based High Performance Modeling Environment for Computational Epidemiology.

Science.gov (United States)

Deodhar, Suruchi; Bisset, Keith R; Chen, Jiangzhuo; Ma, Yifei; Marathe, Madhav V

2014-07-01

We present an integrated interactive modeling environment to support public health epidemiology. The environment combines a high resolution individual-based model with a user-friendly web-based interface that allows analysts to access the models and the analytics back-end remotely from a desktop or a mobile device. The environment is based on a loosely-coupled service-oriented-architecture that allows analysts to explore various counter factual scenarios. As the modeling tools for public health epidemiology are getting more sophisticated, it is becoming increasingly hard for non-computational scientists to effectively use the systems that incorporate such models. Thus an important design consideration for an integrated modeling environment is to improve ease of use such that experimental simulations can be driven by the users. This is achieved by designing intuitive and user-friendly interfaces that allow users to design and analyze a computational experiment and steer the experiment based on the state of the system. A key feature of a system that supports this design goal is the ability to start, stop, pause and roll-back the disease propagation and intervention application process interactively. An analyst can access the state of the system at any point in time and formulate dynamic interventions based on additional information obtained through state assessment. In addition, the environment provides automated services for experiment set-up and management, thus reducing the overall time for conducting end-to-end experimental studies. We illustrate the applicability of the system by describing computational experiments based on realistic pandemic planning scenarios. The experiments are designed to demonstrate the system's capability and enhanced user productivity.

High Performance Computing Modernization Program Kerberos Throughput Test Report

Science.gov (United States)

2017-10-26

Naval Research Laboratory Washington, DC 20375-5320 NRL/MR/5524--17-9751 High Performance Computing Modernization Program Kerberos Throughput Test ...NUMBER 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 2. REPORT TYPE1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 6. AUTHOR(S) 8. PERFORMING...PAGE 18. NUMBER OF PAGES 17. LIMITATION OF ABSTRACT High Performance Computing Modernization Program Kerberos Throughput Test Report Daniel G. Gdula* and

SCEAPI: A unified Restful Web API for High-Performance Computing

Science.gov (United States)

Rongqiang, Cao; Haili, Xiao; Shasha, Lu; Yining, Zhao; Xiaoning, Wang; Xuebin, Chi

2017-10-01

The development of scientific computing is increasingly moving to collaborative web and mobile applications. All these applications need high-quality programming interface for accessing heterogeneous computing resources consisting of clusters, grid computing or cloud computing. In this paper, we introduce our high-performance computing environment that integrates computing resources from 16 HPC centers across China. Then we present a bundle of web services called SCEAPI and describe how it can be used to access HPC resources with HTTP or HTTPs protocols. We discuss SCEAPI from several aspects including architecture, implementation and security, and address specific challenges in designing compatible interfaces and protecting sensitive data. We describe the functions of SCEAPI including authentication, file transfer and job management for creating, submitting and monitoring, and how to use SCEAPI in an easy-to-use way. Finally, we discuss how to exploit more HPC resources quickly for the ATLAS experiment by implementing the custom ARC compute element based on SCEAPI, and our work shows that SCEAPI is an easy-to-use and effective solution to extend opportunistic HPC resources.

CUDA/GPU Technology : Parallel Programming For High Performance Scientific Computing

OpenAIRE

YUHENDRA; KUZE, Hiroaki; JOSAPHAT, Tetuko Sri Sumantyo

2009-01-01

[ABSTRACT]Graphics processing units (GP Us) originally designed for computer video cards have emerged as the most powerful chip in a high-performance workstation. In the high performance computation capabilities, graphic processing units (GPU) lead to much more powerful performance than conventional CPUs by means of parallel processing. In 2007, the birth of Compute Unified Device Architecture (CUDA) and CUDA-enabled GPUs by NVIDIA Corporation brought a revolution in the general purpose GPU a...

Computational Environments and Analysis methods available on the NCI High Performance Computing (HPC) and High Performance Data (HPD) Platform

Science.gov (United States)

Evans, B. J. K.; Foster, C.; Minchin, S. A.; Pugh, T.; Lewis, A.; Wyborn, L. A.; Evans, B. J.; Uhlherr, A.

2014-12-01

The National Computational Infrastructure (NCI) has established a powerful in-situ computational environment to enable both high performance computing and data-intensive science across a wide spectrum of national environmental data collections - in particular climate, observational data and geoscientific assets. This paper examines 1) the computational environments that supports the modelling and data processing pipelines, 2) the analysis environments and methods to support data analysis, and 3) the progress in addressing harmonisation of the underlying data collections for future transdisciplinary research that enable accurate climate projections. NCI makes available 10+ PB major data collections from both the government and research sectors based on six themes: 1) weather, climate, and earth system science model simulations, 2) marine and earth observations, 3) geosciences, 4) terrestrial ecosystems, 5) water and hydrology, and 6) astronomy, social and biosciences. Collectively they span the lithosphere, crust, biosphere, hydrosphere, troposphere, and stratosphere. The data is largely sourced from NCI's partners (which include the custodians of many of the national scientific records), major research communities, and collaborating overseas organisations. The data is accessible within an integrated HPC-HPD environment - a 1.2 PFlop supercomputer (Raijin), a HPC class 3000 core OpenStack cloud system and several highly connected large scale and high-bandwidth Lustre filesystems. This computational environment supports a catalogue of integrated reusable software and workflows from earth system and ecosystem modelling, weather research, satellite and other observed data processing and analysis. To enable transdisciplinary research on this scale, data needs to be harmonised so that researchers can readily apply techniques and software across the corpus of data available and not be constrained to work within artificial disciplinary boundaries. Future challenges will

Monitoring SLAC High Performance UNIX Computing Systems

International Nuclear Information System (INIS)

Lettsome, Annette K.

2005-01-01

Knowledge of the effectiveness and efficiency of computers is important when working with high performance systems. The monitoring of such systems is advantageous in order to foresee possible misfortunes or system failures. Ganglia is a software system designed for high performance computing systems to retrieve specific monitoring information. An alternative storage facility for Ganglia's collected data is needed since its default storage system, the round-robin database (RRD), struggles with data integrity. The creation of a script-driven MySQL database solves this dilemma. This paper describes the process took in the creation and implementation of the MySQL database for use by Ganglia. Comparisons between data storage by both databases are made using gnuplot and Ganglia's real-time graphical user interface

High Performance Computing Software Applications for Space Situational Awareness

Science.gov (United States)

Giuliano, C.; Schumacher, P.; Matson, C.; Chun, F.; Duncan, B.; Borelli, K.; Desonia, R.; Gusciora, G.; Roe, K.

The High Performance Computing Software Applications Institute for Space Situational Awareness (HSAI-SSA) has completed its first full year of applications development. The emphasis of our work in this first year was in improving space surveillance sensor models and image enhancement software. These applications are the Space Surveillance Network Analysis Model (SSNAM), the Air Force Space Fence simulation (SimFence), and physically constrained iterative de-convolution (PCID) image enhancement software tool. Specifically, we have demonstrated order of magnitude speed-up in those codes running on the latest Cray XD-1 Linux supercomputer (Hoku) at the Maui High Performance Computing Center. The software applications improvements that HSAI-SSA has made, has had significant impact to the warfighter and has fundamentally changed the role of high performance computing in SSA.

DURIP: High Performance Computing in Biomathematics Applications

Science.gov (United States)

2017-05-10

Mathematics and Statistics (AMS) at the University of California, Santa Cruz (UCSC) to conduct research and research-related education in areas of...Computing in Biomathematics Applications Report Title The goal of this award was to enhance the capabilities of the Department of Applied Mathematics and...DURIP: High Performance Computing in Biomathematics Applications The goal of this award was to enhance the capabilities of the Department of Applied

AHPCRC - Army High Performance Computing Research Center

Science.gov (United States)

2010-01-01

computing. Of particular interest is the ability of a distrib- uted jamming network (DJN) to jam signals in all or part of a sensor or communications net...and reasoning, assistive technologies. FRIEDRICH (FRITZ) PRINZ Finmeccanica Professor of Engineering, Robert Bosch Chair, Department of Engineering...High Performance Computing Research Center www.ahpcrc.org BARBARA BRYAN AHPCRC Research and Outreach Manager, HPTi (650) 604-3732 bbryan@hpti.com Ms

Enabling high performance computational science through combinatorial algorithms

International Nuclear Information System (INIS)

Boman, Erik G; Bozdag, Doruk; Catalyurek, Umit V; Devine, Karen D; Gebremedhin, Assefaw H; Hovland, Paul D; Pothen, Alex; Strout, Michelle Mills

2007-01-01

The Combinatorial Scientific Computing and Petascale Simulations (CSCAPES) Institute is developing algorithms and software for combinatorial problems that play an enabling role in scientific and engineering computations. Discrete algorithms will be increasingly critical for achieving high performance for irregular problems on petascale architectures. This paper describes recent contributions by researchers at the CSCAPES Institute in the areas of load balancing, parallel graph coloring, performance improvement, and parallel automatic differentiation

Enabling high performance computational science through combinatorial algorithms

Energy Technology Data Exchange (ETDEWEB)

Boman, Erik G [Discrete Algorithms and Math Department, Sandia National Laboratories (United States); Bozdag, Doruk [Biomedical Informatics, and Electrical and Computer Engineering, Ohio State University (United States); Catalyurek, Umit V [Biomedical Informatics, and Electrical and Computer Engineering, Ohio State University (United States); Devine, Karen D [Discrete Algorithms and Math Department, Sandia National Laboratories (United States); Gebremedhin, Assefaw H [Computer Science and Center for Computational Science, Old Dominion University (United States); Hovland, Paul D [Mathematics and Computer Science Division, Argonne National Laboratory (United States); Pothen, Alex [Computer Science and Center for Computational Science, Old Dominion University (United States); Strout, Michelle Mills [Computer Science, Colorado State University (United States)

2007-07-15

The Combinatorial Scientific Computing and Petascale Simulations (CSCAPES) Institute is developing algorithms and software for combinatorial problems that play an enabling role in scientific and engineering computations. Discrete algorithms will be increasingly critical for achieving high performance for irregular problems on petascale architectures. This paper describes recent contributions by researchers at the CSCAPES Institute in the areas of load balancing, parallel graph coloring, performance improvement, and parallel automatic differentiation.

COMPUTERS: Teraflops for Europe; EEC Working Group on High Performance Computing

Energy Technology Data Exchange (ETDEWEB)

Anon.

1991-03-15

In little more than a decade, simulation on high performance computers has become an essential tool for theoretical physics, capable of solving a vast range of crucial problems inaccessible to conventional analytic mathematics. In many ways, computer simulation has become the calculus for interacting many-body systems, a key to the study of transitions from isolated to collective behaviour.

COMPUTERS: Teraflops for Europe; EEC Working Group on High Performance Computing

International Nuclear Information System (INIS)

Anon.

1991-01-01

In little more than a decade, simulation on high performance computers has become an essential tool for theoretical physics, capable of solving a vast range of crucial problems inaccessible to conventional analytic mathematics. In many ways, computer simulation has become the calculus for interacting many-body systems, a key to the study of transitions from isolated to collective behaviour

Enabling High-Performance Computing as a Service

KAUST Repository

AbdelBaky, Moustafa; Parashar, Manish; Kim, Hyunjoo; Jordan, Kirk E.; Sachdeva, Vipin; Sexton, James; Jamjoom, Hani; Shae, Zon-Yin; Pencheva, Gergina; Tavakoli, Reza; Wheeler, Mary F.

2012-01-01

With the right software infrastructure, clouds can provide scientists with as a service access to high-performance computing resources. An award-winning prototype framework transforms the Blue Gene/P system into an elastic cloud to run a

Thinking processes used by high-performing students in a computer programming task

Directory of Open Access Journals (Sweden)

Marietjie Havenga

2011-07-01

Full Text Available Computer programmers must be able to understand programming source code and write programs that execute complex tasks to solve real-world problems. This article is a trans- disciplinary study at the intersection of computer programming, education and psychology. It outlines the role of mental processes in the process of programming and indicates how successful thinking processes can support computer science students in writing correct and well-defined programs. A mixed methods approach was used to better understand the thinking activities and programming processes of participating students. Data collection involved both computer programs and students’ reflective thinking processes recorded in their journals. This enabled analysis of psychological dimensions of participants’ thinking processes and their problem-solving activities as they considered a programming problem. Findings indicate that the cognitive, reflective and psychological processes used by high-performing programmers contributed to their success in solving a complex programming problem. Based on the thinking processes of high performers, we propose a model of integrated thinking processes, which can support computer programming students. Keywords: Computer programming, education, mixed methods research, thinking processes.  Disciplines: Computer programming, education, psychology

Parameters that affect parallel processing for computational electromagnetic simulation codes on high performance computing clusters

Science.gov (United States)

Moon, Hongsik

What is the impact of multicore and associated advanced technologies on computational software for science? Most researchers and students have multicore laptops or desktops for their research and they need computing power to run computational software packages. Computing power was initially derived from Central Processing Unit (CPU) clock speed. That changed when increases in clock speed became constrained by power requirements. Chip manufacturers turned to multicore CPU architectures and associated technological advancements to create the CPUs for the future. Most software applications benefited by the increased computing power the same way that increases in clock speed helped applications run faster. However, for Computational ElectroMagnetics (CEM) software developers, this change was not an obvious benefit - it appeared to be a detriment. Developers were challenged to find a way to correctly utilize the advancements in hardware so that their codes could benefit. The solution was parallelization and this dissertation details the investigation to address these challenges. Prior to multicore CPUs, advanced computer technologies were compared with the performance using benchmark software and the metric was FLoting-point Operations Per Seconds (FLOPS) which indicates system performance for scientific applications that make heavy use of floating-point calculations. Is FLOPS an effective metric for parallelized CEM simulation tools on new multicore system? Parallel CEM software needs to be benchmarked not only by FLOPS but also by the performance of other parameters related to type and utilization of the hardware, such as CPU, Random Access Memory (RAM), hard disk, network, etc. The codes need to be optimized for more than just FLOPs and new parameters must be included in benchmarking. In this dissertation, the parallel CEM software named High Order Basis Based Integral Equation Solver (HOBBIES) is introduced. This code was developed to address the needs of the

High performance parallel computing of flows in complex geometries: II. Applications

International Nuclear Information System (INIS)

Gourdain, N; Gicquel, L; Staffelbach, G; Vermorel, O; Duchaine, F; Boussuge, J-F; Poinsot, T

2009-01-01

Present regulations in terms of pollutant emissions, noise and economical constraints, require new approaches and designs in the fields of energy supply and transportation. It is now well established that the next breakthrough will come from a better understanding of unsteady flow effects and by considering the entire system and not only isolated components. However, these aspects are still not well taken into account by the numerical approaches or understood whatever the design stage considered. The main challenge is essentially due to the computational requirements inferred by such complex systems if it is to be simulated by use of supercomputers. This paper shows how new challenges can be addressed by using parallel computing platforms for distinct elements of a more complex systems as encountered in aeronautical applications. Based on numerical simulations performed with modern aerodynamic and reactive flow solvers, this work underlines the interest of high-performance computing for solving flow in complex industrial configurations such as aircrafts, combustion chambers and turbomachines. Performance indicators related to parallel computing efficiency are presented, showing that establishing fair criterions is a difficult task for complex industrial applications. Examples of numerical simulations performed in industrial systems are also described with a particular interest for the computational time and the potential design improvements obtained with high-fidelity and multi-physics computing methods. These simulations use either unsteady Reynolds-averaged Navier-Stokes methods or large eddy simulation and deal with turbulent unsteady flows, such as coupled flow phenomena (thermo-acoustic instabilities, buffet, etc). Some examples of the difficulties with grid generation and data analysis are also presented when dealing with these complex industrial applications.

Enabling High-Performance Computing as a Service

KAUST Repository

AbdelBaky, Moustafa

2012-10-01

With the right software infrastructure, clouds can provide scientists with as a service access to high-performance computing resources. An award-winning prototype framework transforms the Blue Gene/P system into an elastic cloud to run a representative HPC application. © 2012 IEEE.

High-performance simulation-based algorithms for an alpine ski racer’s trajectory optimization in heterogeneous computer systems

Directory of Open Access Journals (Sweden)

Dębski Roman

2014-09-01

Full Text Available Effective, simulation-based trajectory optimization algorithms adapted to heterogeneous computers are studied with reference to the problem taken from alpine ski racing (the presented solution is probably the most general one published so far. The key idea behind these algorithms is to use a grid-based discretization scheme to transform the continuous optimization problem into a search problem over a specially constructed finite graph, and then to apply dynamic programming to find an approximation of the global solution. In the analyzed example it is the minimum-time ski line, represented as a piecewise-linear function (a method of elimination of unfeasible solutions is proposed. Serial and parallel versions of the basic optimization algorithm are presented in detail (pseudo-code, time and memory complexity. Possible extensions of the basic algorithm are also described. The implementation of these algorithms is based on OpenCL. The included experimental results show that contemporary heterogeneous computers can be treated as μ-HPC platforms-they offer high performance (the best speedup was equal to 128 while remaining energy and cost efficient (which is crucial in embedded systems, e.g., trajectory planners of autonomous robots. The presented algorithms can be applied to many trajectory optimization problems, including those having a black-box represented performance measure

Overview of Parallel Platforms for Common High Performance Computing

Directory of Open Access Journals (Sweden)

T. Fryza

2012-04-01

Full Text Available The paper deals with various parallel platforms used for high performance computing in the signal processing domain. More precisely, the methods exploiting the multicores central processing units such as message passing interface and OpenMP are taken into account. The properties of the programming methods are experimentally proved in the application of a fast Fourier transform and a discrete cosine transform and they are compared with the possibilities of MATLAB's built-in functions and Texas Instruments digital signal processors with very long instruction word architectures. New FFT and DCT implementations were proposed and tested. The implementation phase was compared with CPU based computing methods and with possibilities of the Texas Instruments digital signal processing library on C6747 floating-point DSPs. The optimal combination of computing methods in the signal processing domain and new, fast routines' implementation is proposed as well.

High Performance Networks From Supercomputing to Cloud Computing

CERN Document Server

Abts, Dennis

2011-01-01

Datacenter networks provide the communication substrate for large parallel computer systems that form the ecosystem for high performance computing (HPC) systems and modern Internet applications. The design of new datacenter networks is motivated by an array of applications ranging from communication intensive climatology, complex material simulations and molecular dynamics to such Internet applications as Web search, language translation, collaborative Internet applications, streaming video and voice-over-IP. For both Supercomputing and Cloud Computing the network enables distributed applicati

Computers as Components Principles of Embedded Computing System Design

CERN Document Server

Wolf, Wayne

2008-01-01

This book was the first to bring essential knowledge on embedded systems technology and techniques under a single cover. This second edition has been updated to the state-of-the-art by reworking and expanding performance analysis with more examples and exercises, and coverage of electronic systems now focuses on the latest applications. Researchers, students, and savvy professionals schooled in hardware or software design, will value Wayne Wolf's integrated engineering design approach.The second edition gives a more comprehensive view of multiprocessors including VLIW and superscalar archite

Evaluation of high-performance computing software

Energy Technology Data Exchange (ETDEWEB)

Browne, S.; Dongarra, J. [Univ. of Tennessee, Knoxville, TN (United States); Rowan, T. [Oak Ridge National Lab., TN (United States)

1996-12-31

The absence of unbiased and up to date comparative evaluations of high-performance computing software complicates a user`s search for the appropriate software package. The National HPCC Software Exchange (NHSE) is attacking this problem using an approach that includes independent evaluations of software, incorporation of author and user feedback into the evaluations, and Web access to the evaluations. We are applying this approach to the Parallel Tools Library (PTLIB), a new software repository for parallel systems software and tools, and HPC-Netlib, a high performance branch of the Netlib mathematical software repository. Updating the evaluations with feed-back and making it available via the Web helps ensure accuracy and timeliness, and using independent reviewers produces unbiased comparative evaluations difficult to find elsewhere.

14th annual Results and Review Workshop on High Performance Computing in Science and Engineering

CERN Document Server

Nagel, Wolfgang E; Resch, Michael M; Transactions of the High Performance Computing Center, Stuttgart (HLRS) 2011; High Performance Computing in Science and Engineering '11

2012-01-01

This book presents the state-of-the-art in simulation on supercomputers. Leading researchers present results achieved on systems of the High Performance Computing Center Stuttgart (HLRS) for the year 2011. The reports cover all fields of computational science and engineering, ranging from CFD to computational physics and chemistry, to computer science, with a special emphasis on industrially relevant applications. Presenting results for both vector systems and microprocessor-based systems, the book allows readers to compare the performance levels and usability of various architectures. As HLRS

Performance Measurements in a High Throughput Computing Environment

CERN Document Server

AUTHOR|(CDS)2145966; Gribaudo, Marco

The IT infrastructures of companies and research centres are implementing new technologies to satisfy the increasing need of computing resources for big data analysis. In this context, resource profiling plays a crucial role in identifying areas where the improvement of the utilisation efficiency is needed. In order to deal with the profiling and optimisation of computing resources, two complementary approaches can be adopted: the measurement-based approach and the model-based approach. The measurement-based approach gathers and analyses performance metrics executing benchmark applications on computing resources. Instead, the model-based approach implies the design and implementation of a model as an abstraction of the real system, selecting only those aspects relevant to the study. This Thesis originates from a project carried out by the author within the CERN IT department. CERN is an international scientific laboratory that conducts fundamental researches in the domain of elementary particle physics. The p...

Can We Build a Truly High Performance Computer Which is Flexible and Transparent?

KAUST Repository

Rojas, Jhonathan Prieto; Sevilla, Galo T.; Hussain, Muhammad Mustafa

2013-01-01

cost advantage. In that context, low-cost mono-crystalline bulk silicon (100) based high performance transistors are considered as the heart of today's computers. One limitation is silicon's rigidity and brittleness. Here we show a generic batch process

High Performance Computing Operations Review Report

Energy Technology Data Exchange (ETDEWEB)

Cupps, Kimberly C. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2013-12-19

The High Performance Computing Operations Review (HPCOR) meeting—requested by the ASC and ASCR program headquarters at DOE—was held November 5 and 6, 2013, at the Marriott Hotel in San Francisco, CA. The purpose of the review was to discuss the processes and practices for HPC integration and its related software and facilities. Experiences and lessons learned from the most recent systems deployed were covered in order to benefit the deployment of new systems.

High Performance Computing in Science and Engineering '08 : Transactions of the High Performance Computing Center

CERN Document Server

Kröner, Dietmar; Resch, Michael

2009-01-01

The discussions and plans on all scienti?c, advisory, and political levels to realize an even larger “European Supercomputer” in Germany, where the hardware costs alone will be hundreds of millions Euro – much more than in the past – are getting closer to realization. As part of the strategy, the three national supercomputing centres HLRS (Stuttgart), NIC/JSC (Julic ¨ h) and LRZ (Munich) have formed the Gauss Centre for Supercomputing (GCS) as a new virtual organization enabled by an agreement between the Federal Ministry of Education and Research (BMBF) and the state ministries for research of Baden-Wurttem ¨ berg, Bayern, and Nordrhein-Westfalen. Already today, the GCS provides the most powerful high-performance computing - frastructure in Europe. Through GCS, HLRS participates in the European project PRACE (Partnership for Advances Computing in Europe) and - tends its reach to all European member countries. These activities aligns well with the activities of HLRS in the European HPC infrastructur...

High performance computing in science and engineering '09: transactions of the High Performance Computing Center, Stuttgart (HLRS) 2009

National Research Council Canada - National Science Library

Nagel, Wolfgang E; Kröner, Dietmar; Resch, Michael

2010-01-01

...), NIC/JSC (J¨ u lich), and LRZ (Munich). As part of that strategic initiative, in May 2009 already NIC/JSC has installed the first phase of the GCS HPC Tier-0 resources, an IBM Blue Gene/P with roughly 300.000 Cores, this time in J¨ u lich, With that, the GCS provides the most powerful high-performance computing infrastructure in Europe alread...

The contribution of high-performance computing and modelling for industrial development

CSIR Research Space (South Africa)

Sithole, Happy

2017-10-01

Full Text Available Performance Computing and Modelling for Industrial Development Dr Happy Sithole and Dr Onno Ubbink 2 Strategic context • High-performance computing (HPC) combined with machine Learning and artificial intelligence present opportunities to non...

The path toward HEP High Performance Computing

International Nuclear Information System (INIS)

Apostolakis, John; Brun, René; Gheata, Andrei; Wenzel, Sandro; Carminati, Federico

2014-01-01

High Energy Physics code has been known for making poor use of high performance computing architectures. Efforts in optimising HEP code on vector and RISC architectures have yield limited results and recent studies have shown that, on modern architectures, it achieves a performance between 10% and 50% of the peak one. Although several successful attempts have been made to port selected codes on GPUs, no major HEP code suite has a 'High Performance' implementation. With LHC undergoing a major upgrade and a number of challenging experiments on the drawing board, HEP cannot any longer neglect the less-than-optimal performance of its code and it has to try making the best usage of the hardware. This activity is one of the foci of the SFT group at CERN, which hosts, among others, the Root and Geant4 project. The activity of the experiments is shared and coordinated via a Concurrency Forum, where the experience in optimising HEP code is presented and discussed. Another activity is the Geant-V project, centred on the development of a highperformance prototype for particle transport. Achieving a good concurrency level on the emerging parallel architectures without a complete redesign of the framework can only be done by parallelizing at event level, or with a much larger effort at track level. Apart the shareable data structures, this typically implies a multiplication factor in terms of memory consumption compared to the single threaded version, together with sub-optimal handling of event processing tails. Besides this, the low level instruction pipelining of modern processors cannot be used efficiently to speedup the program. We have implemented a framework that allows scheduling vectors of particles to an arbitrary number of computing resources in a fine grain parallel approach. The talk will review the current optimisation activities within the SFT group with a particular emphasis on the development perspectives towards a simulation framework able to profit

High performance computing and communications: FY 1997 implementation plan

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-12-01

The High Performance Computing and Communications (HPCC) Program was formally authorized by passage, with bipartisan support, of the High-Performance Computing Act of 1991, signed on December 9, 1991. The original Program, in which eight Federal agencies participated, has now grown to twelve agencies. This Plan provides a detailed description of the agencies` FY 1996 HPCC accomplishments and FY 1997 HPCC plans. Section 3 of this Plan provides an overview of the HPCC Program. Section 4 contains more detailed definitions of the Program Component Areas, with an emphasis on the overall directions and milestones planned for each PCA. Appendix A provides a detailed look at HPCC Program activities within each agency.

High performance computing and communications: FY 1996 implementation plan

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-05-16

The High Performance Computing and Communications (HPCC) Program was formally authorized by passage of the High Performance Computing Act of 1991, signed on December 9, 1991. Twelve federal agencies, in collaboration with scientists and managers from US industry, universities, and research laboratories, have developed the Program to meet the challenges of advancing computing and associated communications technologies and practices. This plan provides a detailed description of the agencies` HPCC implementation plans for FY 1995 and FY 1996. This Implementation Plan contains three additional sections. Section 3 provides an overview of the HPCC Program definition and organization. Section 4 contains a breakdown of the five major components of the HPCC Program, with an emphasis on the overall directions and milestones planned for each one. Section 5 provides a detailed look at HPCC Program activities within each agency.

High performance computing in science and engineering Garching/Munich 2016

Energy Technology Data Exchange (ETDEWEB)

Wagner, Siegfried; Bode, Arndt; Bruechle, Helmut; Brehm, Matthias (eds.)

2016-11-01

Computer simulations are the well-established third pillar of natural sciences along with theory and experimentation. Particularly high performance computing is growing fast and constantly demands more and more powerful machines. To keep pace with this development, in spring 2015, the Leibniz Supercomputing Centre installed the high performance computing system SuperMUC Phase 2, only three years after the inauguration of its sibling SuperMUC Phase 1. Thereby, the compute capabilities were more than doubled. This book covers the time-frame June 2014 until June 2016. Readers will find many examples of outstanding research in the more than 130 projects that are covered in this book, with each one of these projects using at least 4 million core-hours on SuperMUC. The largest scientific communities using SuperMUC in the last two years were computational fluid dynamics simulations, chemistry and material sciences, astrophysics, and life sciences.

Contemporary high performance computing from petascale toward exascale

CERN Document Server

Vetter, Jeffrey S

2015-01-01

A continuation of Contemporary High Performance Computing: From Petascale toward Exascale, this second volume continues the discussion of HPC flagship systems, major application workloads, facilities, and sponsors. The book includes of figures and pictures that capture the state of existing systems: pictures of buildings, systems in production, floorplans, and many block diagrams and charts to illustrate system design and performance.

High Performance Spaceflight Computing (HPSC)

Data.gov (United States)

National Aeronautics and Space Administration — Space-based computing has not kept up with the needs of current and future NASA missions. We are developing a next-generation flight computing system that addresses...

Using high performance interconnects in a distributed computing and mass storage environment

International Nuclear Information System (INIS)

Ernst, M.

1994-01-01

Detector Collaborations of the HERA Experiments typically involve more than 500 physicists from a few dozen institutes. These physicists require access to large amounts of data in a fully transparent manner. Important issues include Distributed Mass Storage Management Systems in a Distributed and Heterogeneous Computing Environment. At the very center of a distributed system, including tens of CPUs and network attached mass storage peripherals are the communication links. Today scientists are witnessing an integration of computing and communication technology with the open-quote network close-quote becoming the computer. This contribution reports on a centrally operated computing facility for the HERA Experiments at DESY, including Symmetric Multiprocessor Machines (84 Processors), presently more than 400 GByte of magnetic disk and 40 TB of automoted tape storage, tied together by a HIPPI open-quote network close-quote. Focussing on the High Performance Interconnect technology, details will be provided about the HIPPI based open-quote Backplane close-quote configured around a 20 Gigabit/s Multi Media Router and the performance and efficiency of the related computer interfaces

Inclusive vision for high performance computing at the CSIR

CSIR Research Space (South Africa)

Gazendam, A

2006-02-01

Full Text Available and computationally intensive applications. A number of different technologies and standards were identified as core to the open and distributed high-performance infrastructure envisaged...

High Performance Computing Multicast

Science.gov (United States)

2012-02-01

A History of the Virtual Synchrony Replication Model,” in Replication: Theory and Practice, Charron-Bost, B., Pedone, F., and Schiper, A. (Eds...Performance Computing IP / IPv4 Internet Protocol (version 4.0) IPMC Internet Protocol MultiCast LAN Local Area Network MCMD Dr. Multicast MPI

A high performance scientific cloud computing environment for materials simulations

OpenAIRE

Jorissen, Kevin; Vila, Fernando D.; Rehr, John J.

2011-01-01

We describe the development of a scientific cloud computing (SCC) platform that offers high performance computation capability. The platform consists of a scientific virtual machine prototype containing a UNIX operating system and several materials science codes, together with essential interface tools (an SCC toolset) that offers functionality comparable to local compute clusters. In particular, our SCC toolset provides automatic creation of virtual clusters for parallel computing, including...

The path toward HEP High Performance Computing

CERN Document Server

Apostolakis, John; Carminati, Federico; Gheata, Andrei; Wenzel, Sandro

2014-01-01

High Energy Physics code has been known for making poor use of high performance computing architectures. Efforts in optimising HEP code on vector and RISC architectures have yield limited results and recent studies have shown that, on modern architectures, it achieves a performance between 10% and 50% of the peak one. Although several successful attempts have been made to port selected codes on GPUs, no major HEP code suite has a 'High Performance' implementation. With LHC undergoing a major upgrade and a number of challenging experiments on the drawing board, HEP cannot any longer neglect the less-than-optimal performance of its code and it has to try making the best usage of the hardware. This activity is one of the foci of the SFT group at CERN, which hosts, among others, the Root and Geant4 project. The activity of the experiments is shared and coordinated via a Concurrency Forum, where the experience in optimising HEP code is presented and discussed. Another activity is the Geant-V project, centred on th...

High-performance computing for structural mechanics and earthquake/tsunami engineering

CERN Document Server

Hori, Muneo; Ohsaki, Makoto

2016-01-01

Huge earthquakes and tsunamis have caused serious damage to important structures such as civil infrastructure elements, buildings and power plants around the globe.  To quantitatively evaluate such damage processes and to design effective prevention and mitigation measures, the latest high-performance computational mechanics technologies, which include telascale to petascale computers, can offer powerful tools. The phenomena covered in this book include seismic wave propagation in the crust and soil, seismic response of infrastructure elements such as tunnels considering soil-structure interactions, seismic response of high-rise buildings, seismic response of nuclear power plants, tsunami run-up over coastal towns and tsunami inundation considering fluid-structure interactions. The book provides all necessary information for addressing these phenomena, ranging from the fundamentals of high-performance computing for finite element methods, key algorithms of accurate dynamic structural analysis, fluid flows ...

Acceleration of FDTD mode solver by high-performance computing techniques.

Science.gov (United States)

Han, Lin; Xi, Yanping; Huang, Wei-Ping

2010-06-21

A two-dimensional (2D) compact finite-difference time-domain (FDTD) mode solver is developed based on wave equation formalism in combination with the matrix pencil method (MPM). The method is validated for calculation of both real guided and complex leaky modes of typical optical waveguides against the bench-mark finite-difference (FD) eigen mode solver. By taking advantage of the inherent parallel nature of the FDTD algorithm, the mode solver is implemented on graphics processing units (GPUs) using the compute unified device architecture (CUDA). It is demonstrated that the high-performance computing technique leads to significant acceleration of the FDTD mode solver with more than 30 times improvement in computational efficiency in comparison with the conventional FDTD mode solver running on CPU of a standard desktop computer. The computational efficiency of the accelerated FDTD method is in the same order of magnitude of the standard finite-difference eigen mode solver and yet require much less memory (e.g., less than 10%). Therefore, the new method may serve as an efficient, accurate and robust tool for mode calculation of optical waveguides even when the conventional eigen value mode solvers are no longer applicable due to memory limitation.

High performance computing system in the framework of the Higgs boson studies

CERN Document Server

Belyaev, Nikita; The ATLAS collaboration

2017-01-01

The Higgs boson physics is one of the most important and promising fields of study in modern High Energy Physics. To perform precision measurements of the Higgs boson properties, the use of fast and efficient instruments of Monte Carlo event simulation is required. Due to the increasing amount of data and to the growing complexity of the simulation software tools, the computing resources currently available for Monte Carlo simulation on the LHC GRID are not sufficient. One of the possibilities to address this shortfall of computing resources is the usage of institutes computer clusters, commercial computing resources and supercomputers. In this paper, a brief description of the Higgs boson physics, the Monte-Carlo generation and event simulation techniques are presented. A description of modern high performance computing systems and tests of their performance are also discussed. These studies have been performed on the Worldwide LHC Computing Grid and Kurchatov Institute Data Processing Center, including Tier...

The effects of laboratory inquire-based experiments and computer simulations on high school students‘ performance and cognitive load in physics teaching

Directory of Open Access Journals (Sweden)

Radulović Branka

2016-01-01

Full Text Available The main goal of this study was to examine the extent to which different teaching instructions focused on the application of laboratory inquire-based experiments (LIBEs and interactive computer based simulations (ICBSs improved understanding of physical contents in high school students, compared to traditional teaching approach. Additionally, the study examined how the applied instructions influenced students’ assessment of invested cognitive load. A convenience sample of this research included 187 high school students. A multiple-choice test of knowledge was used as a measuring instrument for the students’ performance. Each task in the test was followed by the five-point Likert-type scale for the evaluation of invested cognitive load. In addition to descriptive statistics, determination of significant differences in performance and cognitive load as well as the calculation of instructional efficiency of applied instructional design, computed one-factor analysis of variance and Tukey’s post-hoc test. The findings indicate that teaching instructions based on the use of LIBEs and ICBSs equally contribute to an increase in students’ performance and the reduction of cognitive load unlike traditional teaching of Physics. The results obtained by the students from the LIBEs and ICBSs groups for calculated instructional efficiency suggest that the applied teaching strategies represent effective teaching instructions. [Projekat Ministarstva nauke Republike Srbije, br. 179010: The Quality of Education System in Serbia from European Perspective

Scientific Grand Challenges: Forefront Questions in Nuclear Science and the Role of High Performance Computing

International Nuclear Information System (INIS)

Khaleel, Mohammad A.

2009-01-01

This report is an account of the deliberations and conclusions of the workshop on 'Forefront Questions in Nuclear Science and the Role of High Performance Computing' held January 26-28, 2009, co-sponsored by the U.S. Department of Energy (DOE) Office of Nuclear Physics (ONP) and the DOE Office of Advanced Scientific Computing (ASCR). Representatives from the national and international nuclear physics communities, as well as from the high performance computing community, participated. The purpose of this workshop was to (1) identify forefront scientific challenges in nuclear physics and then determine which-if any-of these could be aided by high performance computing at the extreme scale; (2) establish how and why new high performance computing capabilities could address issues at the frontiers of nuclear science; (3) provide nuclear physicists the opportunity to influence the development of high performance computing; and (4) provide the nuclear physics community with plans for development of future high performance computing capability by DOE ASCR.

Scientific Grand Challenges: Forefront Questions in Nuclear Science and the Role of High Performance Computing

Energy Technology Data Exchange (ETDEWEB)

Khaleel, Mohammad A.

2009-10-01

This report is an account of the deliberations and conclusions of the workshop on "Forefront Questions in Nuclear Science and the Role of High Performance Computing" held January 26-28, 2009, co-sponsored by the U.S. Department of Energy (DOE) Office of Nuclear Physics (ONP) and the DOE Office of Advanced Scientific Computing (ASCR). Representatives from the national and international nuclear physics communities, as well as from the high performance computing community, participated. The purpose of this workshop was to 1) identify forefront scientific challenges in nuclear physics and then determine which-if any-of these could be aided by high performance computing at the extreme scale; 2) establish how and why new high performance computing capabilities could address issues at the frontiers of nuclear science; 3) provide nuclear physicists the opportunity to influence the development of high performance computing; and 4) provide the nuclear physics community with plans for development of future high performance computing capability by DOE ASCR.

High performance parallel computers for science: New developments at the Fermilab advanced computer program

International Nuclear Information System (INIS)

Nash, T.; Areti, H.; Atac, R.

1988-08-01

Fermilab's Advanced Computer Program (ACP) has been developing highly cost effective, yet practical, parallel computers for high energy physics since 1984. The ACP's latest developments are proceeding in two directions. A Second Generation ACP Multiprocessor System for experiments will include $3500 RISC processors each with performance over 15 VAX MIPS. To support such high performance, the new system allows parallel I/O, parallel interprocess communication, and parallel host processes. The ACP Multi-Array Processor, has been developed for theoretical physics. Each $4000 node is a FORTRAN or C programmable pipelined 20 MFlops (peak), 10 MByte single board computer. These are plugged into a 16 port crossbar switch crate which handles both inter and intra crate communication. The crates are connected in a hypercube. Site oriented applications like lattice gauge theory are supported by system software called CANOPY, which makes the hardware virtually transparent to users. A 256 node, 5 GFlop, system is under construction. 10 refs., 7 figs

Simple, parallel, high-performance virtual machines for extreme computations

International Nuclear Information System (INIS)

Chokoufe Nejad, Bijan; Ohl, Thorsten; Reuter, Jurgen

2014-11-01

We introduce a high-performance virtual machine (VM) written in a numerically fast language like Fortran or C to evaluate very large expressions. We discuss the general concept of how to perform computations in terms of a VM and present specifically a VM that is able to compute tree-level cross sections for any number of external legs, given the corresponding byte code from the optimal matrix element generator, O'Mega. Furthermore, this approach allows to formulate the parallel computation of a single phase space point in a simple and obvious way. We analyze hereby the scaling behaviour with multiple threads as well as the benefits and drawbacks that are introduced with this method. Our implementation of a VM can run faster than the corresponding native, compiled code for certain processes and compilers, especially for very high multiplicities, and has in general runtimes in the same order of magnitude. By avoiding the tedious compile and link steps, which may fail for source code files of gigabyte sizes, new processes or complex higher order corrections that are currently out of reach could be evaluated with a VM given enough computing power.

A High Performance VLSI Computer Architecture For Computer Graphics

Science.gov (United States)

Chin, Chi-Yuan; Lin, Wen-Tai

1988-10-01

A VLSI computer architecture, consisting of multiple processors, is presented in this paper to satisfy the modern computer graphics demands, e.g. high resolution, realistic animation, real-time display etc.. All processors share a global memory which are partitioned into multiple banks. Through a crossbar network, data from one memory bank can be broadcasted to many processors. Processors are physically interconnected through a hyper-crossbar network (a crossbar-like network). By programming the network, the topology of communication links among processors can be reconfigurated to satisfy specific dataflows of different applications. Each processor consists of a controller, arithmetic operators, local memory, a local crossbar network, and I/O ports to communicate with other processors, memory banks, and a system controller. Operations in each processor are characterized into two modes, i.e. object domain and space domain, to fully utilize the data-independency characteristics of graphics processing. Special graphics features such as 3D-to-2D conversion, shadow generation, texturing, and reflection, can be easily handled. With the current high density interconnection (MI) technology, it is feasible to implement a 64-processor system to achieve 2.5 billion operations per second, a performance needed in most advanced graphics applications.

FY 1992 Blue Book: Grand Challenges: High Performance Computing and Communications

Data.gov (United States)

Networking and Information Technology Research and Development, Executive Office of the President — High performance computing and computer communications networks are becoming increasingly important to scientific advancement, economic competition, and national...

High performance computing and communications: Advancing the frontiers of information technology

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-12-31

This report, which supplements the President`s Fiscal Year 1997 Budget, describes the interagency High Performance Computing and Communications (HPCC) Program. The HPCC Program will celebrate its fifth anniversary in October 1996 with an impressive array of accomplishments to its credit. Over its five-year history, the HPCC Program has focused on developing high performance computing and communications technologies that can be applied to computation-intensive applications. Major highlights for FY 1996: (1) High performance computing systems enable practical solutions to complex problems with accuracies not possible five years ago; (2) HPCC-funded research in very large scale networking techniques has been instrumental in the evolution of the Internet, which continues exponential growth in size, speed, and availability of information; (3) The combination of hardware capability measured in gigaflop/s, networking technology measured in gigabit/s, and new computational science techniques for modeling phenomena has demonstrated that very large scale accurate scientific calculations can be executed across heterogeneous parallel processing systems located thousands of miles apart; (4) Federal investments in HPCC software R and D support researchers who pioneered the development of parallel languages and compilers, high performance mathematical, engineering, and scientific libraries, and software tools--technologies that allow scientists to use powerful parallel systems to focus on Federal agency mission applications; and (5) HPCC support for virtual environments has enabled the development of immersive technologies, where researchers can explore and manipulate multi-dimensional scientific and engineering problems. Educational programs fostered by the HPCC Program have brought into classrooms new science and engineering curricula designed to teach computational science. This document contains a small sample of the significant HPCC Program accomplishments in FY 1996.

Computational Fluid Dynamics (CFD) Computations With Zonal Navier-Stokes Flow Solver (ZNSFLOW) Common High Performance Computing Scalable Software Initiative (CHSSI) Software

National Research Council Canada - National Science Library

Edge, Harris

1999-01-01

...), computational fluid dynamics (CFD) 6 project. Under the project, a proven zonal Navier-Stokes solver was rewritten for scalable parallel performance on both shared memory and distributed memory high performance computers...

Real-time Tsunami Inundation Prediction Using High Performance Computers

Science.gov (United States)

Oishi, Y.; Imamura, F.; Sugawara, D.

2014-12-01

Recently off-shore tsunami observation stations based on cabled ocean bottom pressure gauges are actively being deployed especially in Japan. These cabled systems are designed to provide real-time tsunami data before tsunamis reach coastlines for disaster mitigation purposes. To receive real benefits of these observations, real-time analysis techniques to make an effective use of these data are necessary. A representative study was made by Tsushima et al. (2009) that proposed a method to provide instant tsunami source prediction based on achieving tsunami waveform data. As time passes, the prediction is improved by using updated waveform data. After a tsunami source is predicted, tsunami waveforms are synthesized from pre-computed tsunami Green functions of linear long wave equations. Tsushima et al. (2014) updated the method by combining the tsunami waveform inversion with an instant inversion of coseismic crustal deformation and improved the prediction accuracy and speed in the early stages. For disaster mitigation purposes, real-time predictions of tsunami inundation are also important. In this study, we discuss the possibility of real-time tsunami inundation predictions, which require faster-than-real-time tsunami inundation simulation in addition to instant tsunami source analysis. Although the computational amount is large to solve non-linear shallow water equations for inundation predictions, it has become executable through the recent developments of high performance computing technologies. We conducted parallel computations of tsunami inundation and achieved 6.0 TFLOPS by using 19,000 CPU cores. We employed a leap-frog finite difference method with nested staggered grids of which resolution range from 405 m to 5 m. The resolution ratio of each nested domain was 1/3. Total number of grid points were 13 million, and the time step was 0.1 seconds. Tsunami sources of 2011 Tohoku-oki earthquake were tested. The inundation prediction up to 2 hours after the

A Generic High-performance GPU-based Library for PDE solvers

DEFF Research Database (Denmark)

Glimberg, Stefan Lemvig; Engsig-Karup, Allan Peter

, the privilege of high-performance parallel computing is now in principle accessible for many scientific users, no matter their economic resources. Though being highly effective units, GPUs and parallel architectures in general, pose challenges for software developers to utilize their efficiency. Sequential...... legacy codes are not always easily parallelized and the time spent on conversion might not pay o in the end. We present a highly generic C++ library for fast assembling of partial differential equation (PDE) solvers, aiming at utilizing the computational resources of GPUs. The library requires a minimum...... of GPU computing knowledge, while still oering the possibility to customize user-specic solvers at kernel level if desired. Spatial dierential operators are based on matrix free exible order nite dierence approximations. These matrix free operators minimize both memory consumption and main memory access...

High performance computing and communications: FY 1995 implementation plan

Energy Technology Data Exchange (ETDEWEB)

NONE

1994-04-01

The High Performance Computing and Communications (HPCC) Program was formally established following passage of the High Performance Computing Act of 1991 signed on December 9, 1991. Ten federal agencies in collaboration with scientists and managers from US industry, universities, and laboratories have developed the HPCC Program to meet the challenges of advancing computing and associated communications technologies and practices. This plan provides a detailed description of the agencies` HPCC implementation plans for FY 1994 and FY 1995. This Implementation Plan contains three additional sections. Section 3 provides an overview of the HPCC Program definition and organization. Section 4 contains a breakdown of the five major components of the HPCC Program, with an emphasis on the overall directions and milestones planned for each one. Section 5 provides a detailed look at HPCC Program activities within each agency. Although the Department of Education is an official HPCC agency, its current funding and reporting of crosscut activities goes through the Committee on Education and Health Resources, not the HPCC Program. For this reason the Implementation Plan covers nine HPCC agencies.

Unravelling the structure of matter on high-performance computers

International Nuclear Information System (INIS)

Kieu, T.D.; McKellar, B.H.J.

1992-11-01

The various phenomena and the different forms of matter in nature are believed to be the manifestation of only a handful set of fundamental building blocks-the elementary particles-which interact through the four fundamental forces. In the study of the structure of matter at this level one has to consider forces which are not sufficiently weak to be treated as small perturbations to the system, an example of which is the strong force that binds the nucleons together. High-performance computers, both vector and parallel machines, have facilitated the necessary non-perturbative treatments. The principles and the techniques of computer simulations applied to Quantum Chromodynamics are explained examples include the strong interactions, the calculation of the mass of nucleons and their decay rates. Some commercial and special-purpose high-performance machines for such calculations are also mentioned. 3 refs., 2 tabs

A Performance/Cost Evaluation for a GPU-Based Drug Discovery Application on Volunteer Computing

Science.gov (United States)

Guerrero, Ginés D.; Imbernón, Baldomero; García, José M.

2014-01-01

Bioinformatics is an interdisciplinary research field that develops tools for the analysis of large biological databases, and, thus, the use of high performance computing (HPC) platforms is mandatory for the generation of useful biological knowledge. The latest generation of graphics processing units (GPUs) has democratized the use of HPC as they push desktop computers to cluster-level performance. Many applications within this field have been developed to leverage these powerful and low-cost architectures. However, these applications still need to scale to larger GPU-based systems to enable remarkable advances in the fields of healthcare, drug discovery, genome research, etc. The inclusion of GPUs in HPC systems exacerbates power and temperature issues, increasing the total cost of ownership (TCO). This paper explores the benefits of volunteer computing to scale bioinformatics applications as an alternative to own large GPU-based local infrastructures. We use as a benchmark a GPU-based drug discovery application called BINDSURF that their computational requirements go beyond a single desktop machine. Volunteer computing is presented as a cheap and valid HPC system for those bioinformatics applications that need to process huge amounts of data and where the response time is not a critical factor. PMID:25025055

Improving the Eco-Efficiency of High Performance Computing Clusters Using EECluster

Directory of Open Access Journals (Sweden)

Alberto Cocaña-Fernández

2016-03-01

Full Text Available As data and supercomputing centres increase their performance to improve service quality and target more ambitious challenges every day, their carbon footprint also continues to grow, and has already reached the magnitude of the aviation industry. Also, high power consumptions are building up to a remarkable bottleneck for the expansion of these infrastructures in economic terms due to the unavailability of sufficient energy sources. A substantial part of the problem is caused by current energy consumptions of High Performance Computing (HPC clusters. To alleviate this situation, we present in this work EECluster, a tool that integrates with multiple open-source Resource Management Systems to significantly reduce the carbon footprint of clusters by improving their energy efficiency. EECluster implements a dynamic power management mechanism based on Computational Intelligence techniques by learning a set of rules through multi-criteria evolutionary algorithms. This approach enables cluster operators to find the optimal balance between a reduction in the cluster energy consumptions, service quality, and number of reconfigurations. Experimental studies using both synthetic and actual workloads from a real world cluster support the adoption of this tool to reduce the carbon footprint of HPC clusters.

Monitoring performance of a highly distributed and complex computing infrastructure in LHCb

Science.gov (United States)

Mathe, Z.; Haen, C.; Stagni, F.

2017-10-01

In order to ensure an optimal performance of the LHCb Distributed Computing, based on LHCbDIRAC, it is necessary to be able to inspect the behavior over time of many components: firstly the agents and services on which the infrastructure is built, but also all the computing tasks and data transfers that are managed by this infrastructure. This consists of recording and then analyzing time series of a large number of observables, for which the usage of SQL relational databases is far from optimal. Therefore within DIRAC we have been studying novel possibilities based on NoSQL databases (ElasticSearch, OpenTSDB and InfluxDB) as a result of this study we developed a new monitoring system based on ElasticSearch. It has been deployed on the LHCb Distributed Computing infrastructure for which it collects data from all the components (agents, services, jobs) and allows creating reports through Kibana and a web user interface, which is based on the DIRAC web framework. In this paper we describe this new implementation of the DIRAC monitoring system. We give details on the ElasticSearch implementation within the DIRAC general framework, as well as an overview of the advantages of the pipeline aggregation used for creating a dynamic bucketing of the time series. We present the advantages of using the ElasticSearch DSL high-level library for creating and running queries. Finally we shall present the performances of that system.

A high-performance data acquisition system for computer-based multichannel analyzer

International Nuclear Information System (INIS)

Zhou Xinzhi; Bai Rongsheng; Wen Liangbi; Huang Yanwen

1996-01-01

A high-performance data acquisition system applied in the multichannel analyzer is designed with single-chip microcomputer system. The paper proposes the principle and the method of realizing the simultaneous data acquisition, the data pre-processing, and the fast bidirectional data transfer by means of direct memory access based on dual-port RAM as well. The measurement for dead or live time of ADC system can also be implemented efficiently by using it

GPU-based high performance Monte Carlo simulation in neutron transport

Energy Technology Data Exchange (ETDEWEB)

Heimlich, Adino; Mol, Antonio C.A.; Pereira, Claudio M.N.A. [Instituto de Engenharia Nuclear (IEN/CNEN-RJ), Rio de Janeiro, RJ (Brazil). Lab. de Inteligencia Artificial Aplicada], e-mail: cmnap@ien.gov.br

2009-07-01

Graphics Processing Units (GPU) are high performance co-processors intended, originally, to improve the use and quality of computer graphics applications. Since researchers and practitioners realized the potential of using GPU for general purpose, their application has been extended to other fields out of computer graphics scope. The main objective of this work is to evaluate the impact of using GPU in neutron transport simulation by Monte Carlo method. To accomplish that, GPU- and CPU-based (single and multicore) approaches were developed and applied to a simple, but time-consuming problem. Comparisons demonstrated that the GPU-based approach is about 15 times faster than a parallel 8-core CPU-based approach also developed in this work. (author)

GPU-based high performance Monte Carlo simulation in neutron transport

International Nuclear Information System (INIS)

Heimlich, Adino; Mol, Antonio C.A.; Pereira, Claudio M.N.A.

2009-01-01

Graphics Processing Units (GPU) are high performance co-processors intended, originally, to improve the use and quality of computer graphics applications. Since researchers and practitioners realized the potential of using GPU for general purpose, their application has been extended to other fields out of computer graphics scope. The main objective of this work is to evaluate the impact of using GPU in neutron transport simulation by Monte Carlo method. To accomplish that, GPU- and CPU-based (single and multicore) approaches were developed and applied to a simple, but time-consuming problem. Comparisons demonstrated that the GPU-based approach is about 15 times faster than a parallel 8-core CPU-based approach also developed in this work. (author)

High-performance integrated field-effect transistor-based sensors

Energy Technology Data Exchange (ETDEWEB)

Adzhri, R., E-mail: adzhri@gmail.com [Institute of Nano Electronic Engineering (INEE), Universiti Malaysia Perlis (UniMAP), Kangar, Perlis (Malaysia); Md Arshad, M.K., E-mail: mohd.khairuddin@unimap.edu.my [Institute of Nano Electronic Engineering (INEE), Universiti Malaysia Perlis (UniMAP), Kangar, Perlis (Malaysia); School of Microelectronic Engineering (SoME), Universiti Malaysia Perlis (UniMAP), Kangar, Perlis (Malaysia); Gopinath, Subash C.B., E-mail: subash@unimap.edu.my [Institute of Nano Electronic Engineering (INEE), Universiti Malaysia Perlis (UniMAP), Kangar, Perlis (Malaysia); School of Bioprocess Engineering (SBE), Universiti Malaysia Perlis (UniMAP), Arau, Perlis (Malaysia); Ruslinda, A.R., E-mail: ruslinda@unimap.edu.my [Institute of Nano Electronic Engineering (INEE), Universiti Malaysia Perlis (UniMAP), Kangar, Perlis (Malaysia); Fathil, M.F.M., E-mail: faris.fathil@gmail.com [Institute of Nano Electronic Engineering (INEE), Universiti Malaysia Perlis (UniMAP), Kangar, Perlis (Malaysia); Ayub, R.M., E-mail: ramzan@unimap.edu.my [Institute of Nano Electronic Engineering (INEE), Universiti Malaysia Perlis (UniMAP), Kangar, Perlis (Malaysia); Nor, M. Nuzaihan Mohd, E-mail: m.nuzaihan@unimap.edu.my [Institute of Nano Electronic Engineering (INEE), Universiti Malaysia Perlis (UniMAP), Kangar, Perlis (Malaysia); Voon, C.H., E-mail: chvoon@unimap.edu.my [Institute of Nano Electronic Engineering (INEE), Universiti Malaysia Perlis (UniMAP), Kangar, Perlis (Malaysia)

2016-04-21

Field-effect transistors (FETs) have succeeded in modern electronics in an era of computers and hand-held applications. Currently, considerable attention has been paid to direct electrical measurements, which work by monitoring changes in intrinsic electrical properties. Further, FET-based sensing systems drastically reduce cost, are compatible with CMOS technology, and ease down-stream applications. Current technologies for sensing applications rely on time-consuming strategies and processes and can only be performed under recommended conditions. To overcome these obstacles, an overview is presented here in which we specifically focus on high-performance FET-based sensor integration with nano-sized materials, which requires understanding the interaction of surface materials with the surrounding environment. Therefore, we present strategies, material depositions, device structures and other characteristics involved in FET-based devices. Special attention was given to silicon and polyaniline nanowires and graphene, which have attracted much interest due to their remarkable properties in sensing applications. - Highlights: • Performance of FET-based biosensors for the detection of biomolecules is presented. • Silicon nanowire, polyaniline and graphene are the highlighted nanoscaled materials as sensing transducers. • The importance of surface material interaction with the surrounding environment is discussed. • Different device structure architectures for ease in fabrication and high sensitivity of sensing are presented.

High-performance integrated field-effect transistor-based sensors

International Nuclear Information System (INIS)

Adzhri, R.; Md Arshad, M.K.; Gopinath, Subash C.B.; Ruslinda, A.R.; Fathil, M.F.M.; Ayub, R.M.; Nor, M. Nuzaihan Mohd; Voon, C.H.

2016-01-01

Field-effect transistors (FETs) have succeeded in modern electronics in an era of computers and hand-held applications. Currently, considerable attention has been paid to direct electrical measurements, which work by monitoring changes in intrinsic electrical properties. Further, FET-based sensing systems drastically reduce cost, are compatible with CMOS technology, and ease down-stream applications. Current technologies for sensing applications rely on time-consuming strategies and processes and can only be performed under recommended conditions. To overcome these obstacles, an overview is presented here in which we specifically focus on high-performance FET-based sensor integration with nano-sized materials, which requires understanding the interaction of surface materials with the surrounding environment. Therefore, we present strategies, material depositions, device structures and other characteristics involved in FET-based devices. Special attention was given to silicon and polyaniline nanowires and graphene, which have attracted much interest due to their remarkable properties in sensing applications. - Highlights: • Performance of FET-based biosensors for the detection of biomolecules is presented. • Silicon nanowire, polyaniline and graphene are the highlighted nanoscaled materials as sensing transducers. • The importance of surface material interaction with the surrounding environment is discussed. • Different device structure architectures for ease in fabrication and high sensitivity of sensing are presented.

High-Bandwidth Tactical-Network Data Analysis in a High-Performance-Computing (HPC) Environment: Packet-Level Analysis

Science.gov (United States)

2015-09-01

individual fragments using the hash-based method. In general, fragments 6 appear in order and relatively close to each other in the file. A fragment...data product derived from the data model is shown in Fig. 5, a Google Earth12 Keyhole Markup Language (KML) file. This product includes aggregate...System BLOb binary large object FPGA field-programmable gate array HPC high-performance computing IP Internet Protocol KML Keyhole Markup Language

JMS: An Open Source Workflow Management System and Web-Based Cluster Front-End for High Performance Computing.

Science.gov (United States)

Brown, David K; Penkler, David L; Musyoka, Thommas M; Bishop, Özlem Tastan

2015-01-01

Complex computational pipelines are becoming a staple of modern scientific research. Often these pipelines are resource intensive and require days of computing time. In such cases, it makes sense to run them over high performance computing (HPC) clusters where they can take advantage of the aggregated resources of many powerful computers. In addition to this, researchers often want to integrate their workflows into their own web servers. In these cases, software is needed to manage the submission of jobs from the web interface to the cluster and then return the results once the job has finished executing. We have developed the Job Management System (JMS), a workflow management system and web interface for high performance computing (HPC). JMS provides users with a user-friendly web interface for creating complex workflows with multiple stages. It integrates this workflow functionality with the resource manager, a tool that is used to control and manage batch jobs on HPC clusters. As such, JMS combines workflow management functionality with cluster administration functionality. In addition, JMS provides developer tools including a code editor and the ability to version tools and scripts. JMS can be used by researchers from any field to build and run complex computational pipelines and provides functionality to include these pipelines in external interfaces. JMS is currently being used to house a number of bioinformatics pipelines at the Research Unit in Bioinformatics (RUBi) at Rhodes University. JMS is an open-source project and is freely available at https://github.com/RUBi-ZA/JMS.

JMS: An Open Source Workflow Management System and Web-Based Cluster Front-End for High Performance Computing.

Directory of Open Access Journals (Sweden)

David K Brown

Full Text Available Complex computational pipelines are becoming a staple of modern scientific research. Often these pipelines are resource intensive and require days of computing time. In such cases, it makes sense to run them over high performance computing (HPC clusters where they can take advantage of the aggregated resources of many powerful computers. In addition to this, researchers often want to integrate their workflows into their own web servers. In these cases, software is needed to manage the submission of jobs from the web interface to the cluster and then return the results once the job has finished executing. We have developed the Job Management System (JMS, a workflow management system and web interface for high performance computing (HPC. JMS provides users with a user-friendly web interface for creating complex workflows with multiple stages. It integrates this workflow functionality with the resource manager, a tool that is used to control and manage batch jobs on HPC clusters. As such, JMS combines workflow management functionality with cluster administration functionality. In addition, JMS provides developer tools including a code editor and the ability to version tools and scripts. JMS can be used by researchers from any field to build and run complex computational pipelines and provides functionality to include these pipelines in external interfaces. JMS is currently being used to house a number of bioinformatics pipelines at the Research Unit in Bioinformatics (RUBi at Rhodes University. JMS is an open-source project and is freely available at https://github.com/RUBi-ZA/JMS.

JMS: An Open Source Workflow Management System and Web-Based Cluster Front-End for High Performance Computing

Science.gov (United States)

Brown, David K.; Penkler, David L.; Musyoka, Thommas M.; Bishop, Özlem Tastan

2015-01-01

Complex computational pipelines are becoming a staple of modern scientific research. Often these pipelines are resource intensive and require days of computing time. In such cases, it makes sense to run them over high performance computing (HPC) clusters where they can take advantage of the aggregated resources of many powerful computers. In addition to this, researchers often want to integrate their workflows into their own web servers. In these cases, software is needed to manage the submission of jobs from the web interface to the cluster and then return the results once the job has finished executing. We have developed the Job Management System (JMS), a workflow management system and web interface for high performance computing (HPC). JMS provides users with a user-friendly web interface for creating complex workflows with multiple stages. It integrates this workflow functionality with the resource manager, a tool that is used to control and manage batch jobs on HPC clusters. As such, JMS combines workflow management functionality with cluster administration functionality. In addition, JMS provides developer tools including a code editor and the ability to version tools and scripts. JMS can be used by researchers from any field to build and run complex computational pipelines and provides functionality to include these pipelines in external interfaces. JMS is currently being used to house a number of bioinformatics pipelines at the Research Unit in Bioinformatics (RUBi) at Rhodes University. JMS is an open-source project and is freely available at https://github.com/RUBi-ZA/JMS. PMID:26280450

STEMsalabim: A high-performance computing cluster friendly code for scanning transmission electron microscopy image simulations of thin specimens

International Nuclear Information System (INIS)

Oelerich, Jan Oliver; Duschek, Lennart; Belz, Jürgen; Beyer, Andreas; Baranovskii, Sergei D.; Volz, Kerstin

2017-01-01

Highlights: • We present STEMsalabim, a modern implementation of the multislice algorithm for simulation of STEM images. • Our package is highly parallelizable on high-performance computing clusters, combining shared and distributed memory architectures. • With STEMsalabim, computationally and memory expensive STEM image simulations can be carried out within reasonable time. - Abstract: We present a new multislice code for the computer simulation of scanning transmission electron microscope (STEM) images based on the frozen lattice approximation. Unlike existing software packages, the code is optimized to perform well on highly parallelized computing clusters, combining distributed and shared memory architectures. This enables efficient calculation of large lateral scanning areas of the specimen within the frozen lattice approximation and fine-grained sweeps of parameter space.

STEMsalabim: A high-performance computing cluster friendly code for scanning transmission electron microscopy image simulations of thin specimens

Energy Technology Data Exchange (ETDEWEB)

Oelerich, Jan Oliver, E-mail: jan.oliver.oelerich@physik.uni-marburg.de; Duschek, Lennart; Belz, Jürgen; Beyer, Andreas; Baranovskii, Sergei D.; Volz, Kerstin

2017-06-15

Highlights: • We present STEMsalabim, a modern implementation of the multislice algorithm for simulation of STEM images. • Our package is highly parallelizable on high-performance computing clusters, combining shared and distributed memory architectures. • With STEMsalabim, computationally and memory expensive STEM image simulations can be carried out within reasonable time. - Abstract: We present a new multislice code for the computer simulation of scanning transmission electron microscope (STEM) images based on the frozen lattice approximation. Unlike existing software packages, the code is optimized to perform well on highly parallelized computing clusters, combining distributed and shared memory architectures. This enables efficient calculation of large lateral scanning areas of the specimen within the frozen lattice approximation and fine-grained sweeps of parameter space.

5th International Conference on High Performance Scientific Computing

CERN Document Server

Hoang, Xuan; Rannacher, Rolf; Schlöder, Johannes

2014-01-01

This proceedings volume gathers a selection of papers presented at the Fifth International Conference on High Performance Scientific Computing, which took place in Hanoi on March 5-9, 2012. The conference was organized by the Institute of Mathematics of the Vietnam Academy of Science and Technology (VAST), the Interdisciplinary Center for Scientific Computing (IWR) of Heidelberg University, Ho Chi Minh City University of Technology, and the Vietnam Institute for Advanced Study in Mathematics. The contributions cover the broad interdisciplinary spectrum of scientific computing and present recent advances in theory, development of methods, and practical applications. Subjects covered include mathematical modeling; numerical simulation; methods for optimization and control; parallel computing; software development; and applications of scientific computing in physics, mechanics and biomechanics, material science, hydrology, chemistry, biology, biotechnology, medicine, sports, psychology, transport, logistics, com...

3rd International Conference on High Performance Scientific Computing

CERN Document Server

Kostina, Ekaterina; Phu, Hoang; Rannacher, Rolf

2008-01-01

This proceedings volume contains a selection of papers presented at the Third International Conference on High Performance Scientific Computing held at the Hanoi Institute of Mathematics, Vietnamese Academy of Science and Technology (VAST), March 6-10, 2006. The conference has been organized by the Hanoi Institute of Mathematics, Interdisciplinary Center for Scientific Computing (IWR), Heidelberg, and its International PhD Program ``Complex Processes: Modeling, Simulation and Optimization'', and Ho Chi Minh City University of Technology. The contributions cover the broad interdisciplinary spectrum of scientific computing and present recent advances in theory, development of methods, and applications in practice. Subjects covered are mathematical modelling, numerical simulation, methods for optimization and control, parallel computing, software development, applications of scientific computing in physics, chemistry, biology and mechanics, environmental and hydrology problems, transport, logistics and site loca...

6th International Conference on High Performance Scientific Computing

CERN Document Server

Phu, Hoang; Rannacher, Rolf; Schlöder, Johannes

2017-01-01

This proceedings volume highlights a selection of papers presented at the Sixth International Conference on High Performance Scientific Computing, which took place in Hanoi, Vietnam on March 16-20, 2015. The conference was jointly organized by the Heidelberg Institute of Theoretical Studies (HITS), the Institute of Mathematics of the Vietnam Academy of Science and Technology (VAST), the Interdisciplinary Center for Scientific Computing (IWR) at Heidelberg University, and the Vietnam Institute for Advanced Study in Mathematics, Ministry of Education The contributions cover a broad, interdisciplinary spectrum of scientific computing and showcase recent advances in theory, methods, and practical applications. Subjects covered numerical simulation, methods for optimization and control, parallel computing, and software development, as well as the applications of scientific computing in physics, mechanics, biomechanics and robotics, material science, hydrology, biotechnology, medicine, transport, scheduling, and in...

High performance computing system in the framework of the Higgs boson studies

CERN Document Server

Belyaev, Nikita; The ATLAS collaboration; Velikhov, Vasily; Konoplich, Rostislav

2017-01-01

The Higgs boson physics is one of the most important and promising fields of study in the modern high energy physics. It is important to notice, that GRID computing resources become strictly limited due to increasing amount of statistics, required for physics analyses and unprecedented LHC performance. One of the possibilities to address the shortfall of computing resources is the usage of computer institutes' clusters, commercial computing resources and supercomputers. To perform precision measurements of the Higgs boson properties in these realities, it is also highly required to have effective instruments to simulate kinematic distributions of signal events. In this talk we give a brief description of the modern distribution reconstruction method called Morphing and perform few efficiency tests to demonstrate its potential. These studies have been performed on the WLCG and Kurchatov Institute’s Data Processing Center, including Tier-1 GRID site and supercomputer as well. We also analyze the CPU efficienc...

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.

8th International Workshop on Parallel Tools for High Performance Computing

CERN Document Server

Gracia, José; Knüpfer, Andreas; Resch, Michael; Nagel, Wolfgang

2015-01-01

Numerical simulation and modelling using High Performance Computing has evolved into an established technique in academic and industrial research. At the same time, the High Performance Computing infrastructure is becoming ever more complex. For instance, most of the current top systems around the world use thousands of nodes in which classical CPUs are combined with accelerator cards in order to enhance their compute power and energy efficiency. This complexity can only be mastered with adequate development and optimization tools. Key topics addressed by these tools include parallelization on heterogeneous systems, performance optimization for CPUs and accelerators, debugging of increasingly complex scientific applications, and optimization of energy usage in the spirit of green IT. This book represents the proceedings of the 8th International Parallel Tools Workshop, held October 1-2, 2014 in Stuttgart, Germany – which is a forum to discuss the latest advancements in the parallel tools.

Solving Problems in Various Domains by Hybrid Models of High Performance Computations

Directory of Open Access Journals (Sweden)

Yurii Rogozhin

2014-03-01

Full Text Available This work presents a hybrid model of high performance computations. The model is based on membrane system (P~system where some membranes may contain quantum device that is triggered by the data entering the membrane. This model is supposed to take advantages of both biomolecular and quantum paradigms and to overcome some of their inherent limitations. The proposed approach is demonstrated through two selected problems: SAT, and image retrieving.

Prospective randomized study of contrast reaction management curricula: Computer-based interactive simulation versus high-fidelity hands-on simulation

Energy Technology Data Exchange (ETDEWEB)

Wang, Carolyn L., E-mail: wangcl@uw.edu [Department of Radiology, University of Washington, Box 357115, 1959 NE Pacific Street, Seattle, WA 98195-7115 (United States); Schopp, Jennifer G.; Kani, Kimia [Department of Radiology, University of Washington, Box 357115, 1959 NE Pacific Street, Seattle, WA 98195-7115 (United States); Petscavage-Thomas, Jonelle M. [Penn State Hershey Medical Center, Department of Radiology, 500 University Drive, Hershey, PA 17033 (United States); Zaidi, Sadaf; Hippe, Dan S.; Paladin, Angelisa M.; Bush, William H. [Department of Radiology, University of Washington, Box 357115, 1959 NE Pacific Street, Seattle, WA 98195-7115 (United States)

2013-12-01

Purpose: We developed a computer-based interactive simulation program for teaching contrast reaction management to radiology trainees and compared its effectiveness to high-fidelity hands-on simulation training. Materials and methods: IRB approved HIPAA compliant prospective study of 44 radiology residents, fellows and faculty who were randomized into either the high-fidelity hands-on simulation group or computer-based simulation group. All participants took separate written tests prior to and immediately after their intervention. Four months later participants took a delayed written test and a hands-on high-fidelity severe contrast reaction scenario performance test graded on predefined critical actions. Results: There was no statistically significant difference between the computer and hands-on groups’ written pretest, immediate post-test, or delayed post-test scores (p > 0.6 for all). Both groups’ scores improved immediately following the intervention (p < 0.001). The delayed test scores 4 months later were still significantly higher than the pre-test scores (p ≤ 0.02). The computer group's performance was similar to the hands-on group on the severe contrast reaction simulation scenario test (p = 0.7). There were also no significant differences between the computer and hands-on groups in performance on the individual core competencies of contrast reaction management during the contrast reaction scenario. Conclusion: It is feasible to develop a computer-based interactive simulation program to teach contrast reaction management. Trainees that underwent computer-based simulation training scored similarly on written tests and on a hands-on high-fidelity severe contrast reaction scenario performance test as those trained with hands-on high-fidelity simulation.

Prospective randomized study of contrast reaction management curricula: Computer-based interactive simulation versus high-fidelity hands-on simulation

International Nuclear Information System (INIS)

Wang, Carolyn L.; Schopp, Jennifer G.; Kani, Kimia; Petscavage-Thomas, Jonelle M.; Zaidi, Sadaf; Hippe, Dan S.; Paladin, Angelisa M.; Bush, William H.

2013-01-01

Purpose: We developed a computer-based interactive simulation program for teaching contrast reaction management to radiology trainees and compared its effectiveness to high-fidelity hands-on simulation training. Materials and methods: IRB approved HIPAA compliant prospective study of 44 radiology residents, fellows and faculty who were randomized into either the high-fidelity hands-on simulation group or computer-based simulation group. All participants took separate written tests prior to and immediately after their intervention. Four months later participants took a delayed written test and a hands-on high-fidelity severe contrast reaction scenario performance test graded on predefined critical actions. Results: There was no statistically significant difference between the computer and hands-on groups’ written pretest, immediate post-test, or delayed post-test scores (p > 0.6 for all). Both groups’ scores improved immediately following the intervention (p < 0.001). The delayed test scores 4 months later were still significantly higher than the pre-test scores (p ≤ 0.02). The computer group's performance was similar to the hands-on group on the severe contrast reaction simulation scenario test (p = 0.7). There were also no significant differences between the computer and hands-on groups in performance on the individual core competencies of contrast reaction management during the contrast reaction scenario. Conclusion: It is feasible to develop a computer-based interactive simulation program to teach contrast reaction management. Trainees that underwent computer-based simulation training scored similarly on written tests and on a hands-on high-fidelity severe contrast reaction scenario performance test as those trained with hands-on high-fidelity simulation

High-performance computational fluid dynamics: a custom-code approach

International Nuclear Information System (INIS)

Fannon, James; Náraigh, Lennon Ó; Loiseau, Jean-Christophe; Valluri, Prashant; Bethune, Iain

2016-01-01

We introduce a modified and simplified version of the pre-existing fully parallelized three-dimensional Navier–Stokes flow solver known as TPLS. We demonstrate how the simplified version can be used as a pedagogical tool for the study of computational fluid dynamics (CFDs) and parallel computing. TPLS is at its heart a two-phase flow solver, and uses calls to a range of external libraries to accelerate its performance. However, in the present context we narrow the focus of the study to basic hydrodynamics and parallel computing techniques, and the code is therefore simplified and modified to simulate pressure-driven single-phase flow in a channel, using only relatively simple Fortran 90 code with MPI parallelization, but no calls to any other external libraries. The modified code is analysed in order to both validate its accuracy and investigate its scalability up to 1000 CPU cores. Simulations are performed for several benchmark cases in pressure-driven channel flow, including a turbulent simulation, wherein the turbulence is incorporated via the large-eddy simulation technique. The work may be of use to advanced undergraduate and graduate students as an introductory study in CFDs, while also providing insight for those interested in more general aspects of high-performance computing. (paper)

High-performance computational fluid dynamics: a custom-code approach

Science.gov (United States)

Fannon, James; Loiseau, Jean-Christophe; Valluri, Prashant; Bethune, Iain; Náraigh, Lennon Ó.

2016-07-01

We introduce a modified and simplified version of the pre-existing fully parallelized three-dimensional Navier-Stokes flow solver known as TPLS. We demonstrate how the simplified version can be used as a pedagogical tool for the study of computational fluid dynamics (CFDs) and parallel computing. TPLS is at its heart a two-phase flow solver, and uses calls to a range of external libraries to accelerate its performance. However, in the present context we narrow the focus of the study to basic hydrodynamics and parallel computing techniques, and the code is therefore simplified and modified to simulate pressure-driven single-phase flow in a channel, using only relatively simple Fortran 90 code with MPI parallelization, but no calls to any other external libraries. The modified code is analysed in order to both validate its accuracy and investigate its scalability up to 1000 CPU cores. Simulations are performed for several benchmark cases in pressure-driven channel flow, including a turbulent simulation, wherein the turbulence is incorporated via the large-eddy simulation technique. The work may be of use to advanced undergraduate and graduate students as an introductory study in CFDs, while also providing insight for those interested in more general aspects of high-performance computing.

An Application-Based Performance Evaluation of NASAs Nebula Cloud Computing Platform

Science.gov (United States)

Saini, Subhash; Heistand, Steve; Jin, Haoqiang; Chang, Johnny; Hood, Robert T.; Mehrotra, Piyush; Biswas, Rupak

2012-01-01

The high performance computing (HPC) community has shown tremendous interest in exploring cloud computing as it promises high potential. In this paper, we examine the feasibility, performance, and scalability of production quality scientific and engineering applications of interest to NASA on NASA's cloud computing platform, called Nebula, hosted at Ames Research Center. This work represents the comprehensive evaluation of Nebula using NUTTCP, HPCC, NPB, I/O, and MPI function benchmarks as well as four applications representative of the NASA HPC workload. Specifically, we compare Nebula performance on some of these benchmarks and applications to that of NASA s Pleiades supercomputer, a traditional HPC system. We also investigate the impact of virtIO and jumbo frames on interconnect performance. Overall results indicate that on Nebula (i) virtIO and jumbo frames improve network bandwidth by a factor of 5x, (ii) there is a significant virtualization layer overhead of about 10% to 25%, (iii) write performance is lower by a factor of 25x, (iv) latency for short MPI messages is very high, and (v) overall performance is 15% to 48% lower than that on Pleiades for NASA HPC applications. We also comment on the usability of the cloud platform.

Performance Evaluation of Superscalar Processor Architecture Through UML

OpenAIRE

Taskeen Zaidi; Vipin Saxena

2013-01-01

In the current scenario, most of the applications are based upon graphical user interface and dependent upon the object-oriented technology. Software Industries are interested to convert old structured based softwares into object-oriented based softwares and also to reduce the lines of the code of application for reduction in the execution time of application. Therefore, it is a big challenge to reduce the execution time of the application based upon the object-oriented technology. The presen...

A Performance/Cost Evaluation for a GPU-Based Drug Discovery Application on Volunteer Computing

Directory of Open Access Journals (Sweden)

Ginés D. Guerrero

2014-01-01

Full Text Available Bioinformatics is an interdisciplinary research field that develops tools for the analysis of large biological databases, and, thus, the use of high performance computing (HPC platforms is mandatory for the generation of useful biological knowledge. The latest generation of graphics processing units (GPUs has democratized the use of HPC as they push desktop computers to cluster-level performance. Many applications within this field have been developed to leverage these powerful and low-cost architectures. However, these applications still need to scale to larger GPU-based systems to enable remarkable advances in the fields of healthcare, drug discovery, genome research, etc. The inclusion of GPUs in HPC systems exacerbates power and temperature issues, increasing the total cost of ownership (TCO. This paper explores the benefits of volunteer computing to scale bioinformatics applications as an alternative to own large GPU-based local infrastructures. We use as a benchmark a GPU-based drug discovery application called BINDSURF that their computational requirements go beyond a single desktop machine. Volunteer computing is presented as a cheap and valid HPC system for those bioinformatics applications that need to process huge amounts of data and where the response time is not a critical factor.

Multi-Language Programming Environments for High Performance Java Computing

OpenAIRE

Vladimir Getov; Paul Gray; Sava Mintchev; Vaidy Sunderam

1999-01-01

Recent developments in processor capabilities, software tools, programming languages and programming paradigms have brought about new approaches to high performance computing. A steadfast component of this dynamic evolution has been the scientific community’s reliance on established scientific packages. As a consequence, programmers of high‐performance applications are reluctant to embrace evolving languages such as Java. This paper describes the Java‐to‐C Interface (JCI) tool which provides ...

FY 1993 Blue Book: Grand Challenges 1993: High Performance Computing and Communications

Data.gov (United States)

Networking and Information Technology Research and Development, Executive Office of the President — High performance computing and computer communications networks are becoming increasingly important to scientific advancement, economic competition, and national...

FPGA hardware acceleration for high performance neutron transport computation based on agent methodology - 318

International Nuclear Information System (INIS)

Shanjie, Xiao; Tatjana, Jevremovic

2010-01-01

The accurate, detailed and 3D neutron transport analysis for Gen-IV reactors is still time-consuming regardless of advanced computational hardware available in developed countries. This paper introduces a new concept in addressing the computational time while persevering the detailed and accurate modeling; a specifically designed FPGA co-processor accelerates robust AGENT methodology for complex reactor geometries. For the first time this approach is applied to accelerate the neutronics analysis. The AGENT methodology solves neutron transport equation using the method of characteristics. The AGENT methodology performance was carefully analyzed before the hardware design based on the FPGA co-processor was adopted. The most time-consuming kernel part is then transplanted into the FPGA co-processor. The FPGA co-processor is designed with data flow-driven non von-Neumann architecture and has much higher efficiency than the conventional computer architecture. Details of the FPGA co-processor design are introduced and the design is benchmarked using two different examples. The advanced chip architecture helps the FPGA co-processor obtaining more than 20 times speed up with its working frequency much lower than the CPU frequency. (authors)

High-Performance Computing Paradigm and Infrastructure

CERN Document Server

Yang, Laurence T

2006-01-01

With hyperthreading in Intel processors, hypertransport links in next generation AMD processors, multi-core silicon in today's high-end microprocessors from IBM and emerging grid computing, parallel and distributed computers have moved into the mainstream

SiGe epitaxial memory for neuromorphic computing with reproducible high performance based on engineered dislocations

Science.gov (United States)

Choi, Shinhyun; Tan, Scott H.; Li, Zefan; Kim, Yunjo; Choi, Chanyeol; Chen, Pai-Yu; Yeon, Hanwool; Yu, Shimeng; Kim, Jeehwan

2018-01-01

Although several types of architecture combining memory cells and transistors have been used to demonstrate artificial synaptic arrays, they usually present limited scalability and high power consumption. Transistor-free analog switching devices may overcome these limitations, yet the typical switching process they rely on—formation of filaments in an amorphous medium—is not easily controlled and hence hampers the spatial and temporal reproducibility of the performance. Here, we demonstrate analog resistive switching devices that possess desired characteristics for neuromorphic computing networks with minimal performance variations using a single-crystalline SiGe layer epitaxially grown on Si as a switching medium. Such epitaxial random access memories utilize threading dislocations in SiGe to confine metal filaments in a defined, one-dimensional channel. This confinement results in drastically enhanced switching uniformity and long retention/high endurance with a high analog on/off ratio. Simulations using the MNIST handwritten recognition data set prove that epitaxial random access memories can operate with an online learning accuracy of 95.1%.

Human and Robotic Space Mission Use Cases for High-Performance Spaceflight Computing

Science.gov (United States)

Some, Raphael; Doyle, Richard; Bergman, Larry; Whitaker, William; Powell, Wesley; Johnson, Michael; Goforth, Montgomery; Lowry, Michael

2013-01-01

Spaceflight computing is a key resource in NASA space missions and a core determining factor of spacecraft capability, with ripple effects throughout the spacecraft, end-to-end system, and mission. Onboard computing can be aptly viewed as a "technology multiplier" in that advances provide direct dramatic improvements in flight functions and capabilities across the NASA mission classes, and enable new flight capabilities and mission scenarios, increasing science and exploration return. Space-qualified computing technology, however, has not advanced significantly in well over ten years and the current state of the practice fails to meet the near- to mid-term needs of NASA missions. Recognizing this gap, the NASA Game Changing Development Program (GCDP), under the auspices of the NASA Space Technology Mission Directorate, commissioned a study on space-based computing needs, looking out 15-20 years. The study resulted in a recommendation to pursue high-performance spaceflight computing (HPSC) for next-generation missions, and a decision to partner with the Air Force Research Lab (AFRL) in this development.

A Framework for Debugging Geoscience Projects in a High Performance Computing Environment

Science.gov (United States)

Baxter, C.; Matott, L.

2012-12-01

High performance computing (HPC) infrastructure has become ubiquitous in today's world with the emergence of commercial cloud computing and academic supercomputing centers. Teams of geoscientists, hydrologists and engineers can take advantage of this infrastructure to undertake large research projects - for example, linking one or more site-specific environmental models with soft computing algorithms, such as heuristic global search procedures, to perform parameter estimation and predictive uncertainty analysis, and/or design least-cost remediation systems. However, the size, complexity and distributed nature of these projects can make identifying failures in the associated numerical experiments using conventional ad-hoc approaches both time- consuming and ineffective. To address these problems a multi-tiered debugging framework has been developed. The framework allows for quickly isolating and remedying a number of potential experimental failures, including: failures in the HPC scheduler; bugs in the soft computing code; bugs in the modeling code; and permissions and access control errors. The utility of the framework is demonstrated via application to a series of over 200,000 numerical experiments involving a suite of 5 heuristic global search algorithms and 15 mathematical test functions serving as cheap analogues for the simulation-based optimization of pump-and-treat subsurface remediation systems.

High Performance Computing - Power Application Programming Interface Specification.

Energy Technology Data Exchange (ETDEWEB)

Laros, James H.,; Kelly, Suzanne M.; Pedretti, Kevin; Grant, Ryan; Olivier, Stephen Lecler; Levenhagen, Michael J.; DeBonis, David

2014-08-01

Measuring and controlling the power and energy consumption of high performance computing systems by various components in the software stack is an active research area [13, 3, 5, 10, 4, 21, 19, 16, 7, 17, 20, 18, 11, 1, 6, 14, 12]. Implementations in lower level software layers are beginning to emerge in some production systems, which is very welcome. To be most effective, a portable interface to measurement and control features would significantly facilitate participation by all levels of the software stack. We present a proposal for a standard power Application Programming Interface (API) that endeavors to cover the entire software space, from generic hardware interfaces to the input from the computer facility manager.

Nuclear forces and high-performance computing: The perfect match

International Nuclear Information System (INIS)

Luu, T; Walker-Loud, A

2009-01-01

High-performance computing is now enabling the calculation of certain hadronic interaction parameters directly from Quantum Chromodynamics, the quantum field theory that governs the behavior of quarks and gluons and is ultimately responsible for the nuclear strong force. In this paper we briefly describe the state of the field and show how other aspects of hadronic interactions will be ascertained in the near future. We give estimates of computational requirements needed to obtain these goals, and outline a procedure for incorporating these results into the broader nuclear physics community.

High-performance computing on the Intel Xeon Phi how to fully exploit MIC architectures

CERN Document Server

Wang, Endong; Shen, Bo; Zhang, Guangyong; Lu, Xiaowei; Wu, Qing; Wang, Yajuan

2014-01-01

The aim of this book is to explain to high-performance computing (HPC) developers how to utilize the Intel® Xeon Phi™ series products efficiently. To that end, it introduces some computing grammar, programming technology and optimization methods for using many-integrated-core (MIC) platforms and also offers tips and tricks for actual use, based on the authors' first-hand optimization experience.The material is organized in three sections. The first section, "Basics of MIC", introduces the fundamentals of MIC architecture and programming, including the specific Intel MIC programming environment

High performance optical encryption based on computational ghost imaging with QR code and compressive sensing technique

Science.gov (United States)

Zhao, Shengmei; Wang, Le; Liang, Wenqiang; Cheng, Weiwen; Gong, Longyan

2015-10-01

In this paper, we propose a high performance optical encryption (OE) scheme based on computational ghost imaging (GI) with QR code and compressive sensing (CS) technique, named QR-CGI-OE scheme. N random phase screens, generated by Alice, is a secret key and be shared with its authorized user, Bob. The information is first encoded by Alice with QR code, and the QR-coded image is then encrypted with the aid of computational ghost imaging optical system. Here, measurement results from the GI optical system's bucket detector are the encrypted information and be transmitted to Bob. With the key, Bob decrypts the encrypted information to obtain the QR-coded image with GI and CS techniques, and further recovers the information by QR decoding. The experimental and numerical simulated results show that the authorized users can recover completely the original image, whereas the eavesdroppers can not acquire any information about the image even the eavesdropping ratio (ER) is up to 60% at the given measurement times. For the proposed scheme, the number of bits sent from Alice to Bob are reduced considerably and the robustness is enhanced significantly. Meantime, the measurement times in GI system is reduced and the quality of the reconstructed QR-coded image is improved.

NINJA: Java for High Performance Numerical Computing

Directory of Open Access Journals (Sweden)

José E. Moreira

2002-01-01

Full Text Available When Java was first introduced, there was a perception that its many benefits came at a significant performance cost. In the particularly performance-sensitive field of numerical computing, initial measurements indicated a hundred-fold performance disadvantage between Java and more established languages such as Fortran and C. Although much progress has been made, and Java now can be competitive with C/C++ in many important situations, significant performance challenges remain. Existing Java virtual machines are not yet capable of performing the advanced loop transformations and automatic parallelization that are now common in state-of-the-art Fortran compilers. Java also has difficulties in implementing complex arithmetic efficiently. These performance deficiencies can be attacked with a combination of class libraries (packages, in Java that implement truly multidimensional arrays and complex numbers, and new compiler techniques that exploit the properties of these class libraries to enable other, more conventional, optimizations. Two compiler techniques, versioning and semantic expansion, can be leveraged to allow fully automatic optimization and parallelization of Java code. Our measurements with the NINJA prototype Java environment show that Java can be competitive in performance with highly optimized and tuned Fortran code.

RAPPORT: running scientific high-performance computing applications on the cloud.

Science.gov (United States)

Cohen, Jeremy; Filippis, Ioannis; Woodbridge, Mark; Bauer, Daniela; Hong, Neil Chue; Jackson, Mike; Butcher, Sarah; Colling, David; Darlington, John; Fuchs, Brian; Harvey, Matt

2013-01-28

Cloud computing infrastructure is now widely used in many domains, but one area where there has been more limited adoption is research computing, in particular for running scientific high-performance computing (HPC) software. The Robust Application Porting for HPC in the Cloud (RAPPORT) project took advantage of existing links between computing researchers and application scientists in the fields of bioinformatics, high-energy physics (HEP) and digital humanities, to investigate running a set of scientific HPC applications from these domains on cloud infrastructure. In this paper, we focus on the bioinformatics and HEP domains, describing the applications and target cloud platforms. We conclude that, while there are many factors that need consideration, there is no fundamental impediment to the use of cloud infrastructure for running many types of HPC applications and, in some cases, there is potential for researchers to benefit significantly from the flexibility offered by cloud platforms.

FY 1995 Blue Book: High Performance Computing and Communications: Technology for the National Information Infrastructure

Data.gov (United States)

Networking and Information Technology Research and Development, Executive Office of the President — The Federal High Performance Computing and Communications HPCC Program was created to accelerate the development of future generations of high performance computers...

High-performance implementation of Chebyshev filter diagonalization for interior eigenvalue computations

Energy Technology Data Exchange (ETDEWEB)

Pieper, Andreas [Ernst-Moritz-Arndt-Universität Greifswald (Germany); Kreutzer, Moritz [Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany); Alvermann, Andreas, E-mail: alvermann@physik.uni-greifswald.de [Ernst-Moritz-Arndt-Universität Greifswald (Germany); Galgon, Martin [Bergische Universität Wuppertal (Germany); Fehske, Holger [Ernst-Moritz-Arndt-Universität Greifswald (Germany); Hager, Georg [Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany); Lang, Bruno [Bergische Universität Wuppertal (Germany); Wellein, Gerhard [Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany)

2016-11-15

We study Chebyshev filter diagonalization as a tool for the computation of many interior eigenvalues of very large sparse symmetric matrices. In this technique the subspace projection onto the target space of wanted eigenvectors is approximated with filter polynomials obtained from Chebyshev expansions of window functions. After the discussion of the conceptual foundations of Chebyshev filter diagonalization we analyze the impact of the choice of the damping kernel, search space size, and filter polynomial degree on the computational accuracy and effort, before we describe the necessary steps towards a parallel high-performance implementation. Because Chebyshev filter diagonalization avoids the need for matrix inversion it can deal with matrices and problem sizes that are presently not accessible with rational function methods based on direct or iterative linear solvers. To demonstrate the potential of Chebyshev filter diagonalization for large-scale problems of this kind we include as an example the computation of the 10{sup 2} innermost eigenpairs of a topological insulator matrix with dimension 10{sup 9} derived from quantum physics applications.

Implementation of the Principal Component Analysis onto High-Performance Computer Facilities for Hyperspectral Dimensionality Reduction: Results and Comparisons

Directory of Open Access Journals (Sweden)

Ernestina Martel

2018-06-01

Full Text Available Dimensionality reduction represents a critical preprocessing step in order to increase the efficiency and the performance of many hyperspectral imaging algorithms. However, dimensionality reduction algorithms, such as the Principal Component Analysis (PCA, suffer from their computationally demanding nature, becoming advisable for their implementation onto high-performance computer architectures for applications under strict latency constraints. This work presents the implementation of the PCA algorithm onto two different high-performance devices, namely, an NVIDIA Graphics Processing Unit (GPU and a Kalray manycore, uncovering a highly valuable set of tips and tricks in order to take full advantage of the inherent parallelism of these high-performance computing platforms, and hence, reducing the time that is required to process a given hyperspectral image. Moreover, the achieved results obtained with different hyperspectral images have been compared with the ones that were obtained with a field programmable gate array (FPGA-based implementation of the PCA algorithm that has been recently published, providing, for the first time in the literature, a comprehensive analysis in order to highlight the pros and cons of each option.

The high performance cluster computing system for BES offline data analysis

International Nuclear Information System (INIS)

Sun Yongzhao; Xu Dong; Zhang Shaoqiang; Yang Ting

2004-01-01

A high performance cluster computing system (EPCfarm) is introduced, which used for BES offline data analysis. The setup and the characteristics of the hardware and software of EPCfarm are described. The PBS, a queue management package, and the performance of EPCfarm is presented also. (authors)

HIGH-PERFORMANCE COMPUTING FOR THE STUDY OF EARTH AND ENVIRONMENTAL SCIENCE MATERIALS USING SYNCHROTRON X-RAY COMPUTED MICROTOMOGRAPHY

International Nuclear Information System (INIS)

FENG, H.; JONES, K.W.; MCGUIGAN, M.; SMITH, G.J.; SPILETIC, J.

2001-01-01

Synchrotron x-ray computed microtomography (CMT) is a non-destructive method for examination of rock, soil, and other types of samples studied in the earth and environmental sciences. The high x-ray intensities of the synchrotron source make possible the acquisition of tomographic volumes at a high rate that requires the application of high-performance computing techniques for data reconstruction to produce the three-dimensional volumes, for their visualization, and for data analysis. These problems are exacerbated by the need to share information between collaborators at widely separated locations over both local and tide-area networks. A summary of the CMT technique and examples of applications are given here together with a discussion of the applications of high-performance computing methods to improve the experimental techniques and analysis of the data

HIGH-PERFORMANCE COMPUTING FOR THE STUDY OF EARTH AND ENVIRONMENTAL SCIENCE MATERIALS USING SYNCHROTRON X-RAY COMPUTED MICROTOMOGRAPHY.

Energy Technology Data Exchange (ETDEWEB)

FENG,H.; JONES,K.W.; MCGUIGAN,M.; SMITH,G.J.; SPILETIC,J.

2001-10-12

Synchrotron x-ray computed microtomography (CMT) is a non-destructive method for examination of rock, soil, and other types of samples studied in the earth and environmental sciences. The high x-ray intensities of the synchrotron source make possible the acquisition of tomographic volumes at a high rate that requires the application of high-performance computing techniques for data reconstruction to produce the three-dimensional volumes, for their visualization, and for data analysis. These problems are exacerbated by the need to share information between collaborators at widely separated locations over both local and tide-area networks. A summary of the CMT technique and examples of applications are given here together with a discussion of the applications of high-performance computing methods to improve the experimental techniques and analysis of the data.

Computational Performance of a Parallelized Three-Dimensional High-Order Spectral Element Toolbox

Science.gov (United States)

Bosshard, Christoph; Bouffanais, Roland; Clémençon, Christian; Deville, Michel O.; Fiétier, Nicolas; Gruber, Ralf; Kehtari, Sohrab; Keller, Vincent; Latt, Jonas

In this paper, a comprehensive performance review of an MPI-based high-order three-dimensional spectral element method C++ toolbox is presented. The focus is put on the performance evaluation of several aspects with a particular emphasis on the parallel efficiency. The performance evaluation is analyzed with help of a time prediction model based on a parameterization of the application and the hardware resources. A tailor-made CFD computation benchmark case is introduced and used to carry out this review, stressing the particular interest for clusters with up to 8192 cores. Some problems in the parallel implementation have been detected and corrected. The theoretical complexities with respect to the number of elements, to the polynomial degree, and to communication needs are correctly reproduced. It is concluded that this type of code has a nearly perfect speed up on machines with thousands of cores, and is ready to make the step to next-generation petaflop machines.

Spatial Processing of Urban Acoustic Wave Fields from High-Performance Computations

National Research Council Canada - National Science Library

Ketcham, Stephen A; Wilson, D. K; Cudney, Harley H; Parker, Michael W

2007-01-01

.... The objective of this work is to develop spatial processing techniques for acoustic wave propagation data from three-dimensional high-performance computations to quantify scattering due to urban...

DEISA2: supporting and developing a European high-performance computing ecosystem

International Nuclear Information System (INIS)

Lederer, H

2008-01-01

The DEISA Consortium has deployed and operated the Distributed European Infrastructure for Supercomputing Applications. Through the EU FP7 DEISA2 project (funded for three years as of May 2008), the consortium is continuing to support and enhance the distributed high-performance computing infrastructure and its activities and services relevant for applications enabling, operation, and technologies, as these are indispensable for the effective support of computational sciences for high-performance computing (HPC). The service-provisioning model will be extended from one that supports single projects to one supporting virtual European communities. Collaborative activities will also be carried out with new European and other international initiatives. Of strategic importance is cooperation with the PRACE project, which is preparing for the installation of a limited number of leadership-class Tier-0 supercomputers in Europe. The key role and aim of DEISA will be to deliver a turnkey operational solution for a persistent European HPC ecosystem that will integrate national Tier-1 centers and the new Tier-0 centers

Development of a GPU-based high-performance radiative transfer model for the Infrared Atmospheric Sounding Interferometer (IASI)

International Nuclear Information System (INIS)

Huang Bormin; Mielikainen, Jarno; Oh, Hyunjong; Allen Huang, Hung-Lung

2011-01-01

Satellite-observed radiance is a nonlinear functional of surface properties and atmospheric temperature and absorbing gas profiles as described by the radiative transfer equation (RTE). In the era of hyperspectral sounders with thousands of high-resolution channels, the computation of the radiative transfer model becomes more time-consuming. The radiative transfer model performance in operational numerical weather prediction systems still limits the number of channels we can use in hyperspectral sounders to only a few hundreds. To take the full advantage of such high-resolution infrared observations, a computationally efficient radiative transfer model is needed to facilitate satellite data assimilation. In recent years the programmable commodity graphics processing unit (GPU) has evolved into a highly parallel, multi-threaded, many-core processor with tremendous computational speed and very high memory bandwidth. The radiative transfer model is very suitable for the GPU implementation to take advantage of the hardware's efficiency and parallelism where radiances of many channels can be calculated in parallel in GPUs. In this paper, we develop a GPU-based high-performance radiative transfer model for the Infrared Atmospheric Sounding Interferometer (IASI) launched in 2006 onboard the first European meteorological polar-orbiting satellites, METOP-A. Each IASI spectrum has 8461 spectral channels. The IASI radiative transfer model consists of three modules. The first module for computing the regression predictors takes less than 0.004% of CPU time, while the second module for transmittance computation and the third module for radiance computation take approximately 92.5% and 7.5%, respectively. Our GPU-based IASI radiative transfer model is developed to run on a low-cost personal supercomputer with four GPUs with total 960 compute cores, delivering near 4 TFlops theoretical peak performance. By massively parallelizing the second and third modules, we reached 364x

High performance simulation for the Silva project using the tera computer

International Nuclear Information System (INIS)

Bergeaud, V.; La Hargue, J.P.; Mougery, F.; Boulet, M.; Scheurer, B.; Le Fur, J.F.; Comte, M.; Benisti, D.; Lamare, J. de; Petit, A.

2003-01-01

In the context of the SILVA Project (Atomic Vapor Laser Isotope Separation), numerical simulation of the plant scale propagation of laser beams through uranium vapour was a great challenge. The PRODIGE code has been developed to achieve this goal. Here we focus on the task of achieving high performance simulation on the TERA computer. We describe the main issues for optimizing the parallelization of the PRODIGE code on TERA. Thus, we discuss advantages and drawbacks of the implemented diagonal parallelization scheme. As a consequence, it has been found fruitful to fit out the code in three aspects: memory allocation, MPI communications and interconnection network bandwidth usage. We stress out the interest of MPI/IO in this context and the benefit obtained for production computations on TERA. Finally, we shall illustrate our developments. We indicate some performance measurements reflecting the good parallelization properties of PRODIGE on the TERA computer. The code is currently used for demonstrating the feasibility of the laser propagation at a plant enrichment level and for preparing the 2003 Menphis experiment. We conclude by emphasizing the contribution of high performance TERA simulation to the project. (authors)

High performance simulation for the Silva project using the tera computer

Energy Technology Data Exchange (ETDEWEB)

Bergeaud, V.; La Hargue, J.P.; Mougery, F. [CS Communication and Systemes, 92 - Clamart (France); Boulet, M.; Scheurer, B. [CEA Bruyeres-le-Chatel, 91 - Bruyeres-le-Chatel (France); Le Fur, J.F.; Comte, M.; Benisti, D.; Lamare, J. de; Petit, A. [CEA Saclay, 91 - Gif sur Yvette (France)

2003-07-01

In the context of the SILVA Project (Atomic Vapor Laser Isotope Separation), numerical simulation of the plant scale propagation of laser beams through uranium vapour was a great challenge. The PRODIGE code has been developed to achieve this goal. Here we focus on the task of achieving high performance simulation on the TERA computer. We describe the main issues for optimizing the parallelization of the PRODIGE code on TERA. Thus, we discuss advantages and drawbacks of the implemented diagonal parallelization scheme. As a consequence, it has been found fruitful to fit out the code in three aspects: memory allocation, MPI communications and interconnection network bandwidth usage. We stress out the interest of MPI/IO in this context and the benefit obtained for production computations on TERA. Finally, we shall illustrate our developments. We indicate some performance measurements reflecting the good parallelization properties of PRODIGE on the TERA computer. The code is currently used for demonstrating the feasibility of the laser propagation at a plant enrichment level and for preparing the 2003 Menphis experiment. We conclude by emphasizing the contribution of high performance TERA simulation to the project. (authors)

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.

Comparing Postsecondary Marketing Student Performance on Computer-Based and Handwritten Essay Tests

Science.gov (United States)

Truell, Allen D.; Alexander, Melody W.; Davis, Rodney E.

2004-01-01

The purpose of this study was to determine if there were differences in postsecondary marketing student performance on essay tests based on test format (i.e., computer-based or handwritten). Specifically, the variables of performance, test completion time, and gender were explored for differences based on essay test format. Results of the study…

Analysis and modeling of social influence in high performance computing workloads

KAUST Repository

Zheng, Shuai; Shae, Zon Yin; Zhang, Xiangliang; Jamjoom, Hani T.; Fong, Liana

2011-01-01

Social influence among users (e.g., collaboration on a project) creates bursty behavior in the underlying high performance computing (HPC) workloads. Using representative HPC and cluster workload logs, this paper identifies, analyzes, and quantifies

Topic 14+16: High-performance and scientific applications and extreme-scale computing (Introduction)

KAUST Repository

Downes, Turlough P.

2013-01-01

As our understanding of the world around us increases it becomes more challenging to make use of what we already know, and to increase our understanding still further. Computational modeling and simulation have become critical tools in addressing this challenge. The requirements of high-resolution, accurate modeling have outstripped the ability of desktop computers and even small clusters to provide the necessary compute power. Many applications in the scientific and engineering domains now need very large amounts of compute time, while other applications, particularly in the life sciences, frequently have large data I/O requirements. There is thus a growing need for a range of high performance applications which can utilize parallel compute systems effectively, which have efficient data handling strategies and which have the capacity to utilise current and future systems. The High Performance and Scientific Applications topic aims to highlight recent progress in the use of advanced computing and algorithms to address the varied, complex and increasing challenges of modern research throughout both the "hard" and "soft" sciences. This necessitates being able to use large numbers of compute nodes, many of which are equipped with accelerators, and to deal with difficult I/O requirements. © 2013 Springer-Verlag.

Design Example of Useful Memory Latency for Developing a Hazard Preventive Pipeline High-Performance Embedded-Microprocessor

Directory of Open Access Journals (Sweden)

Ching-Hwa Cheng

2013-01-01

Full Text Available The existence of structural, control, and data hazards presents a major challenge in designing an advanced pipeline/superscalar microprocessor. An efficient memory hierarchy cache-RAM-Disk design greatly enhances the microprocessor's performance. However, there are complex relationships among the memory hierarchy and the functional units in the microprocessor. Most past architectural design simulations focus on the instruction hazard detection/prevention scheme from the viewpoint of function units. This paper emphasizes that additional inboard memory can be well utilized to handle the hazardous conditions. When the instruction meets hazardous issues, the memory latency can be utilized to prevent performance degradation due to the hazard prevention mechanism. By using the proposed technique, a better architectural design can be rapidly validated by an FPGA at the start of the design stage. In this paper, the simulation results prove that our proposed methodology has a better performance and less power consumption compared to the conventional hazard prevention technique.

Bringing high-performance computing to the biologist's workbench: approaches, applications, and challenges

International Nuclear Information System (INIS)

Oehmen, C S; Cannon, W R

2008-01-01

Data-intensive and high-performance computing are poised to significantly impact the future of biological research which is increasingly driven by the prevalence of high-throughput experimental methodologies for genome sequencing, transcriptomics, proteomics, and other areas. Large centers such as NIH's National Center for Biotechnology Information, The Institute for Genomic Research, and the DOE's Joint Genome Institute) have made extensive use of multiprocessor architectures to deal with some of the challenges of processing, storing and curating exponentially growing genomic and proteomic datasets, thus enabling users to rapidly access a growing public data source, as well as use analysis tools transparently on high-performance computing resources. Applying this computational power to single-investigator analysis, however, often relies on users to provide their own computational resources, forcing them to endure the learning curve of porting, building, and running software on multiprocessor architectures. Solving the next generation of large-scale biology challenges using multiprocessor machines-from small clusters to emerging petascale machines-can most practically be realized if this learning curve can be minimized through a combination of workflow management, data management and resource allocation as well as intuitive interfaces and compatibility with existing common data formats

High-Performance Compute Infrastructure in Astronomy: 2020 Is Only Months Away

Science.gov (United States)

Berriman, B.; Deelman, E.; Juve, G.; Rynge, M.; Vöckler, J. S.

2012-09-01

By 2020, astronomy will be awash with as much as 60 PB of public data. Full scientific exploitation of such massive volumes of data will require high-performance computing on server farms co-located with the data. Development of this computing model will be a community-wide enterprise that has profound cultural and technical implications. Astronomers must be prepared to develop environment-agnostic applications that support parallel processing. The community must investigate the applicability and cost-benefit of emerging technologies such as cloud computing to astronomy, and must engage the Computer Science community to develop science-driven cyberinfrastructure such as workflow schedulers and optimizers. We report here the results of collaborations between a science center, IPAC, and a Computer Science research institute, ISI. These collaborations may be considered pathfinders in developing a high-performance compute infrastructure in astronomy. These collaborations investigated two exemplar large-scale science-driver workflow applications: 1) Calculation of an infrared atlas of the Galactic Plane at 18 different wavelengths by placing data from multiple surveys on a common plate scale and co-registering all the pixels; 2) Calculation of an atlas of periodicities present in the public Kepler data sets, which currently contain 380,000 light curves. These products have been generated with two workflow applications, written in C for performance and designed to support parallel processing on multiple environments and platforms, but with different compute resource needs: the Montage image mosaic engine is I/O-bound, and the NASA Star and Exoplanet Database periodogram code is CPU-bound. Our presentation will report cost and performance metrics and lessons-learned for continuing development. Applicability of Cloud Computing: Commercial Cloud providers generally charge for all operations, including processing, transfer of input and output data, and for storage of data

A performance model for the communication in fast multipole methods on high-performance computing platforms

KAUST Repository

Ibeid, Huda; Yokota, Rio; Keyes, David E.

2016-01-01

model and the actual communication time on four high-performance computing (HPC) systems, when latency, bandwidth, network topology, and multicore penalties are all taken into account. To our knowledge, this is the first formal characterization

Using a Computer-based Messaging System at a High School To Increase School/Home Communication.

Science.gov (United States)

Burden, Mitzi K.

Minimal communication between school and home was found to contribute to low performance by students at McDuffie High School (South Carolina). This report describes the experience of establishing a computer-based telephone messaging system in the high school and involving parents, teachers, and students in its use. Additional strategies employed…

RGCA: A Reliable GPU Cluster Architecture for Large-Scale Internet of Things Computing Based on Effective Performance-Energy Optimization.

Science.gov (United States)

Fang, Yuling; Chen, Qingkui; Xiong, Neal N; Zhao, Deyu; Wang, Jingjuan

2017-08-04

This paper aims to develop a low-cost, high-performance and high-reliability computing system to process large-scale data using common data mining algorithms in the Internet of Things (IoT) computing environment. Considering the characteristics of IoT data processing, similar to mainstream high performance computing, we use a GPU (Graphics Processing Unit) cluster to achieve better IoT services. Firstly, we present an energy consumption calculation method (ECCM) based on WSNs. Then, using the CUDA (Compute Unified Device Architecture) Programming model, we propose a Two-level Parallel Optimization Model (TLPOM) which exploits reasonable resource planning and common compiler optimization techniques to obtain the best blocks and threads configuration considering the resource constraints of each node. The key to this part is dynamic coupling Thread-Level Parallelism (TLP) and Instruction-Level Parallelism (ILP) to improve the performance of the algorithms without additional energy consumption. Finally, combining the ECCM and the TLPOM, we use the Reliable GPU Cluster Architecture (RGCA) to obtain a high-reliability computing system considering the nodes' diversity, algorithm characteristics, etc. The results show that the performance of the algorithms significantly increased by 34.1%, 33.96% and 24.07% for Fermi, Kepler and Maxwell on average with TLPOM and the RGCA ensures that our IoT computing system provides low-cost and high-reliability services.

Exploring Infiniband Hardware Virtualization in OpenNebula towards Efficient High-Performance Computing

Energy Technology Data Exchange (ETDEWEB)

Pais Pitta de Lacerda Ruivo, Tiago [IIT, Chicago; Bernabeu Altayo, Gerard [Fermilab; Garzoglio, Gabriele [Fermilab; Timm, Steven [Fermilab; Kim, Hyun-Woo [Fermilab; Noh, Seo-Young [KISTI, Daejeon; Raicu, Ioan [IIT, Chicago

2014-11-11

has been widely accepted that software virtualization has a big negative impact on high-performance computing (HPC) application performance. This work explores the potential use of Infiniband hardware virtualization in an OpenNebula cloud towards the efficient support of MPI-based workloads. We have implemented, deployed, and tested an Infiniband network on the FermiCloud private Infrastructure-as-a-Service (IaaS) cloud. To avoid software virtualization towards minimizing the virtualization overhead, we employed a technique called Single Root Input/Output Virtualization (SRIOV). Our solution spanned modifications to the Linux’s Hypervisor as well as the OpenNebula manager. We evaluated the performance of the hardware virtualization on up to 56 virtual machines connected by up to 8 DDR Infiniband network links, with micro-benchmarks (latency and bandwidth) as well as w a MPI-intensive application (the HPL Linpack benchmark).

Interactive Data Exploration for High-Performance Fluid Flow Computations through Porous Media

KAUST Repository

Perovic, Nevena

2014-09-01

© 2014 IEEE. Huge data advent in high-performance computing (HPC) applications such as fluid flow simulations usually hinders the interactive processing and exploration of simulation results. Such an interactive data exploration not only allows scientiest to \\'play\\' with their data but also to visualise huge (distributed) data sets in both an efficient and easy way. Therefore, we propose an HPC data exploration service based on a sliding window concept, that enables researches to access remote data (available on a supercomputer or cluster) during simulation runtime without exceeding any bandwidth limitations between the HPC back-end and the user front-end.

10th International Workshop on Parallel Tools for High Performance Computing

CERN Document Server

Gracia, José; Hilbrich, Tobias; Knüpfer, Andreas; Resch, Michael; Nagel, Wolfgang

2017-01-01

This book presents the proceedings of the 10th International Parallel Tools Workshop, held October 4-5, 2016 in Stuttgart, Germany – a forum to discuss the latest advances in parallel tools. High-performance computing plays an increasingly important role for numerical simulation and modelling in academic and industrial research. At the same time, using large-scale parallel systems efficiently is becoming more difficult. A number of tools addressing parallel program development and analysis have emerged from the high-performance computing community over the last decade, and what may have started as collection of small helper script has now matured to production-grade frameworks. Powerful user interfaces and an extensive body of documentation allow easy usage by non-specialists.

HIGH PERFORMANCE PHOTOGRAMMETRIC PROCESSING ON COMPUTER CLUSTERS

Directory of Open Access Journals (Sweden)

V. N. Adrov

2012-07-01

Full Text Available Most cpu consuming tasks in photogrammetric processing can be done in parallel. The algorithms take independent bits as input and produce independent bits as output. The independence of bits comes from the nature of such algorithms since images, stereopairs or small image blocks parts can be processed independently. Many photogrammetric algorithms are fully automatic and do not require human interference. Photogrammetric workstations can perform tie points measurements, DTM calculations, orthophoto construction, mosaicing and many other service operations in parallel using distributed calculations. Distributed calculations save time reducing several days calculations to several hours calculations. Modern trends in computer technology show the increase of cpu cores in workstations, speed increase in local networks, and as a result dropping the price of the supercomputers or computer clusters that can contain hundreds or even thousands of computing nodes. Common distributed processing in DPW is usually targeted for interactive work with a limited number of cpu cores and is not optimized for centralized administration. The bottleneck of common distributed computing in photogrammetry can be in the limited lan throughput and storage performance, since the processing of huge amounts of large raster images is needed.

A task-based parallelism and vectorized approach to 3D Method of Characteristics (MOC) reactor simulation for high performance computing architectures

Science.gov (United States)

Tramm, John R.; Gunow, Geoffrey; He, Tim; Smith, Kord S.; Forget, Benoit; Siegel, Andrew R.

2016-05-01

In this study we present and analyze a formulation of the 3D Method of Characteristics (MOC) technique applied to the simulation of full core nuclear reactors. Key features of the algorithm include a task-based parallelism model that allows independent MOC tracks to be assigned to threads dynamically, ensuring load balancing, and a wide vectorizable inner loop that takes advantage of modern SIMD computer architectures. The algorithm is implemented in a set of highly optimized proxy applications in order to investigate its performance characteristics on CPU, GPU, and Intel Xeon Phi architectures. Speed, power, and hardware cost efficiencies are compared. Additionally, performance bottlenecks are identified for each architecture in order to determine the prospects for continued scalability of the algorithm on next generation HPC architectures.

Multicore Challenges and Benefits for High Performance Scientific Computing

Directory of Open Access Journals (Sweden)

Ida M.B. Nielsen

2008-01-01

Full Text Available Until recently, performance gains in processors were achieved largely by improvements in clock speeds and instruction level parallelism. Thus, applications could obtain performance increases with relatively minor changes by upgrading to the latest generation of computing hardware. Currently, however, processor performance improvements are realized by using multicore technology and hardware support for multiple threads within each core, and taking full advantage of this technology to improve the performance of applications requires exposure of extreme levels of software parallelism. We will here discuss the architecture of parallel computers constructed from many multicore chips as well as techniques for managing the complexity of programming such computers, including the hybrid message-passing/multi-threading programming model. We will illustrate these ideas with a hybrid distributed memory matrix multiply and a quantum chemistry algorithm for energy computation using Møller–Plesset perturbation theory.

High Performance Computing Facility Operational Assessment 2015: Oak Ridge Leadership Computing Facility

Energy Technology Data Exchange (ETDEWEB)

Barker, Ashley D. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Bernholdt, David E. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Bland, Arthur S. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Gary, Jeff D. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Hack, James J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; McNally, Stephen T. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Rogers, James H. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Smith, Brian E. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Straatsma, T. P. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Sukumar, Sreenivas Rangan [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Thach, Kevin G. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Tichenor, Suzy [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Vazhkudai, Sudharshan S. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Wells, Jack C. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility

2016-03-01

Oak Ridge National Laboratory’s (ORNL’s) Leadership Computing Facility (OLCF) continues to surpass its operational target goals: supporting users; delivering fast, reliable systems; creating innovative solutions for high-performance computing (HPC) needs; and managing risks, safety, and security aspects associated with operating one of the most powerful computers in the world. The results can be seen in the cutting-edge science delivered by users and the praise from the research community. Calendar year (CY) 2015 was filled with outstanding operational results and accomplishments: a very high rating from users on overall satisfaction that ties the highest-ever mark set in CY 2014; the greatest number of core-hours delivered to research projects; the largest percentage of capability usage since the OLCF began tracking the metric in 2009; and success in delivering on the allocation of 60, 30, and 10% of core hours offered for the INCITE (Innovative and Novel Computational Impact on Theory and Experiment), ALCC (Advanced Scientific Computing Research Leadership Computing Challenge), and Director’s Discretionary programs, respectively. These accomplishments, coupled with the extremely high utilization rate, represent the fulfillment of the promise of Titan: maximum use by maximum-size simulations. The impact of all of these successes and more is reflected in the accomplishments of OLCF users, with publications this year in notable journals Nature, Nature Materials, Nature Chemistry, Nature Physics, Nature Climate Change, ACS Nano, Journal of the American Chemical Society, and Physical Review Letters, as well as many others. The achievements included in the 2015 OLCF Operational Assessment Report reflect first-ever or largest simulations in their communities; for example Titan enabled engineers in Los Angeles and the surrounding region to design and begin building improved critical infrastructure by enabling the highest-resolution Cybershake map for Southern

Breast tumor segmentation in high resolution x-ray phase contrast analyzer based computed tomography.

Science.gov (United States)

Brun, E; Grandl, S; Sztrókay-Gaul, A; Barbone, G; Mittone, A; Gasilov, S; Bravin, A; Coan, P

2014-11-01

Phase contrast computed tomography has emerged as an imaging method, which is able to outperform present day clinical mammography in breast tumor visualization while maintaining an equivalent average dose. To this day, no segmentation technique takes into account the specificity of the phase contrast signal. In this study, the authors propose a new mathematical framework for human-guided breast tumor segmentation. This method has been applied to high-resolution images of excised human organs, each of several gigabytes. The authors present a segmentation procedure based on the viscous watershed transform and demonstrate the efficacy of this method on analyzer based phase contrast images. The segmentation of tumors inside two full human breasts is then shown as an example of this procedure's possible applications. A correct and precise identification of the tumor boundaries was obtained and confirmed by manual contouring performed independently by four experienced radiologists. The authors demonstrate that applying the watershed viscous transform allows them to perform the segmentation of tumors in high-resolution x-ray analyzer based phase contrast breast computed tomography images. Combining the additional information provided by the segmentation procedure with the already high definition of morphological details and tissue boundaries offered by phase contrast imaging techniques, will represent a valuable multistep procedure to be used in future medical diagnostic applications.

Export Controls: Implementation of the 1998 Legislative Mandate for High Performance Computers

National Research Council Canada - National Science Library

1999-01-01

We found that most of the 938 proposed exports of high performance computers to civilian end users in countries of concern from February 3, 1998, when procedures implementing the 1998 authorization...

Development of High-speed Visualization System of Hypocenter Data Using CUDA-based GPU computing

Science.gov (United States)

Kumagai, T.; Okubo, K.; Uchida, N.; Matsuzawa, T.; Kawada, N.; Takeuchi, N.

2014-12-01

After the Great East Japan Earthquake on March 11, 2011, intelligent visualization of seismic information is becoming important to understand the earthquake phenomena. On the other hand, to date, the quantity of seismic data becomes enormous as a progress of high accuracy observation network; we need to treat many parameters (e.g., positional information, origin time, magnitude, etc.) to efficiently display the seismic information. Therefore, high-speed processing of data and image information is necessary to handle enormous amounts of seismic data. Recently, GPU (Graphic Processing Unit) is used as an acceleration tool for data processing and calculation in various study fields. This movement is called GPGPU (General Purpose computing on GPUs). In the last few years the performance of GPU keeps on improving rapidly. GPU computing gives us the high-performance computing environment at a lower cost than before. Moreover, use of GPU has an advantage of visualization of processed data, because GPU is originally architecture for graphics processing. In the GPU computing, the processed data is always stored in the video memory. Therefore, we can directly write drawing information to the VRAM on the video card by combining CUDA and the graphics API. In this study, we employ CUDA and OpenGL and/or DirectX to realize full-GPU implementation. This method makes it possible to write drawing information to the VRAM on the video card without PCIe bus data transfer: It enables the high-speed processing of seismic data. The present study examines the GPU computing-based high-speed visualization and the feasibility for high-speed visualization system of hypocenter data.

Computer science of the high performance; Informatica del alto rendimiento

Energy Technology Data Exchange (ETDEWEB)

Moraleda, A.

2008-07-01

The high performance computing is taking shape as a powerful accelerator of the process of innovation, to drastically reduce the waiting times for access to the results and the findings in a growing number of processes and activities as complex and important as medicine, genetics, pharmacology, environment, natural resources management or the simulation of complex processes in a wide variety of industries. (Author)

Business Models of High Performance Computing Centres in Higher Education in Europe

Science.gov (United States)

Eurich, Markus; Calleja, Paul; Boutellier, Roman

2013-01-01

High performance computing (HPC) service centres are a vital part of the academic infrastructure of higher education organisations. However, despite their importance for research and the necessary high capital expenditures, business research on HPC service centres is mostly missing. From a business perspective, it is important to find an answer to…

A parallel calibration utility for WRF-Hydro on high performance computers

Science.gov (United States)

Wang, J.; Wang, C.; Kotamarthi, V. R.

2017-12-01

A successful modeling of complex hydrological processes comprises establishing an integrated hydrological model which simulates the hydrological processes in each water regime, calibrates and validates the model performance based on observation data, and estimates the uncertainties from different sources especially those associated with parameters. Such a model system requires large computing resources and often have to be run on High Performance Computers (HPC). The recently developed WRF-Hydro modeling system provides a significant advancement in the capability to simulate regional water cycles more completely. The WRF-Hydro model has a large range of parameters such as those in the input table files — GENPARM.TBL, SOILPARM.TBL and CHANPARM.TBL — and several distributed scaling factors such as OVROUGHRTFAC. These parameters affect the behavior and outputs of the model and thus may need to be calibrated against the observations in order to obtain a good modeling performance. Having a parameter calibration tool specifically for automate calibration and uncertainty estimates of WRF-Hydro model can provide significant convenience for the modeling community. In this study, we developed a customized tool using the parallel version of the model-independent parameter estimation and uncertainty analysis tool, PEST, to enabled it to run on HPC with PBS and SLURM workload manager and job scheduler. We also developed a series of PEST input file templates that are specifically for WRF-Hydro model calibration and uncertainty analysis. Here we will present a flood case study occurred in April 2013 over Midwest. The sensitivity and uncertainties are analyzed using the customized PEST tool we developed.

High Performance Computing Facility Operational Assessment, FY 2010 Oak Ridge Leadership Computing Facility

Energy Technology Data Exchange (ETDEWEB)

Bland, Arthur S Buddy [ORNL; Hack, James J [ORNL; Baker, Ann E [ORNL; Barker, Ashley D [ORNL; Boudwin, Kathlyn J. [ORNL; Kendall, Ricky A [ORNL; Messer, Bronson [ORNL; Rogers, James H [ORNL; Shipman, Galen M [ORNL; White, Julia C [ORNL

2010-08-01

Oak Ridge National Laboratory's (ORNL's) Cray XT5 supercomputer, Jaguar, kicked off the era of petascale scientific computing in 2008 with applications that sustained more than a thousand trillion floating point calculations per second - or 1 petaflop. Jaguar continues to grow even more powerful as it helps researchers broaden the boundaries of knowledge in virtually every domain of computational science, including weather and climate, nuclear energy, geosciences, combustion, bioenergy, fusion, and materials science. Their insights promise to broaden our knowledge in areas that are vitally important to the Department of Energy (DOE) and the nation as a whole, particularly energy assurance and climate change. The science of the 21st century, however, will demand further revolutions in computing, supercomputers capable of a million trillion calculations a second - 1 exaflop - and beyond. These systems will allow investigators to continue attacking global challenges through modeling and simulation and to unravel longstanding scientific questions. Creating such systems will also require new approaches to daunting challenges. High-performance systems of the future will need to be codesigned for scientific and engineering applications with best-in-class communications networks and data-management infrastructures and teams of skilled researchers able to take full advantage of these new resources. The Oak Ridge Leadership Computing Facility (OLCF) provides the nation's most powerful open resource for capability computing, with a sustainable path that will maintain and extend national leadership for DOE's Office of Science (SC). The OLCF has engaged a world-class team to support petascale science and to take a dramatic step forward, fielding new capabilities for high-end science. This report highlights the successful delivery and operation of a petascale system and shows how the OLCF fosters application development teams, developing cutting-edge tools

Accessible high performance computing solutions for near real-time image processing for time critical applications

Science.gov (United States)

Bielski, Conrad; Lemoine, Guido; Syryczynski, Jacek

2009-09-01

High Performance Computing (HPC) hardware solutions such as grid computing and General Processing on a Graphics Processing Unit (GPGPU) are now accessible to users with general computing needs. Grid computing infrastructures in the form of computing clusters or blades are becoming common place and GPGPU solutions that leverage the processing power of the video card are quickly being integrated into personal workstations. Our interest in these HPC technologies stems from the need to produce near real-time maps from a combination of pre- and post-event satellite imagery in support of post-disaster management. Faster processing provides a twofold gain in this situation: 1. critical information can be provided faster and 2. more elaborate automated processing can be performed prior to providing the critical information. In our particular case, we test the use of the PANTEX index which is based on analysis of image textural measures extracted using anisotropic, rotation-invariant GLCM statistics. The use of this index, applied in a moving window, has been shown to successfully identify built-up areas in remotely sensed imagery. Built-up index image masks are important input to the structuring of damage assessment interpretation because they help optimise the workload. The performance of computing the PANTEX workflow is compared on two different HPC hardware architectures: (1) a blade server with 4 blades, each having dual quad-core CPUs and (2) a CUDA enabled GPU workstation. The reference platform is a dual CPU-quad core workstation and the PANTEX workflow total computing time is measured. Furthermore, as part of a qualitative evaluation, the differences in setting up and configuring various hardware solutions and the related software coding effort is presented.

Breast tumor segmentation in high resolution x-ray phase contrast analyzer based computed tomography

Energy Technology Data Exchange (ETDEWEB)

Brun, E., E-mail: emmanuel.brun@esrf.fr [European Synchrotron Radiation Facility (ESRF), Grenoble 380000, France and Department of Physics, Ludwig-Maximilians University, Garching 85748 (Germany); Grandl, S.; Sztrókay-Gaul, A.; Gasilov, S. [Institute for Clinical Radiology, Ludwig-Maximilians-University Hospital Munich, 81377 Munich (Germany); Barbone, G. [Department of Physics, Harvard University, Cambridge, Massachusetts 02138 (United States); Mittone, A.; Coan, P. [Department of Physics, Ludwig-Maximilians University, Garching 85748, Germany and Institute for Clinical Radiology, Ludwig-Maximilians-University Hospital Munich, 81377 Munich (Germany); Bravin, A. [European Synchrotron Radiation Facility (ESRF), Grenoble 380000 (France)

2014-11-01

Purpose: Phase contrast computed tomography has emerged as an imaging method, which is able to outperform present day clinical mammography in breast tumor visualization while maintaining an equivalent average dose. To this day, no segmentation technique takes into account the specificity of the phase contrast signal. In this study, the authors propose a new mathematical framework for human-guided breast tumor segmentation. This method has been applied to high-resolution images of excised human organs, each of several gigabytes. Methods: The authors present a segmentation procedure based on the viscous watershed transform and demonstrate the efficacy of this method on analyzer based phase contrast images. The segmentation of tumors inside two full human breasts is then shown as an example of this procedure’s possible applications. Results: A correct and precise identification of the tumor boundaries was obtained and confirmed by manual contouring performed independently by four experienced radiologists. Conclusions: The authors demonstrate that applying the watershed viscous transform allows them to perform the segmentation of tumors in high-resolution x-ray analyzer based phase contrast breast computed tomography images. Combining the additional information provided by the segmentation procedure with the already high definition of morphological details and tissue boundaries offered by phase contrast imaging techniques, will represent a valuable multistep procedure to be used in future medical diagnostic applications.

High performance cellular level agent-based simulation with FLAME for the GPU.

Science.gov (United States)

Richmond, Paul; Walker, Dawn; Coakley, Simon; Romano, Daniela

2010-05-01

Driven by the availability of experimental data and ability to simulate a biological scale which is of immediate interest, the cellular scale is fast emerging as an ideal candidate for middle-out modelling. As with 'bottom-up' simulation approaches, cellular level simulations demand a high degree of computational power, which in large-scale simulations can only be achieved through parallel computing. The flexible large-scale agent modelling environment (FLAME) is a template driven framework for agent-based modelling (ABM) on parallel architectures ideally suited to the simulation of cellular systems. It is available for both high performance computing clusters (www.flame.ac.uk) and GPU hardware (www.flamegpu.com) and uses a formal specification technique that acts as a universal modelling format. This not only creates an abstraction from the underlying hardware architectures, but avoids the steep learning curve associated with programming them. In benchmarking tests and simulations of advanced cellular systems, FLAME GPU has reported massive improvement in performance over more traditional ABM frameworks. This allows the time spent in the development and testing stages of modelling to be drastically reduced and creates the possibility of real-time visualisation for simple visual face-validation.

Benefits of computer screen-based simulation in learning cardiac arrest procedures.

Science.gov (United States)

Bonnetain, Elodie; Boucheix, Jean-Michel; Hamet, Maël; Freysz, Marc

2010-07-01

What is the best way to train medical students early so that they acquire basic skills in cardiopulmonary resuscitation as effectively as possible? Studies have shown the benefits of high-fidelity patient simulators, but have also demonstrated their limits. New computer screen-based multimedia simulators have fewer constraints than high-fidelity patient simulators. In this area, as yet, there has been no research on the effectiveness of transfer of learning from a computer screen-based simulator to more realistic situations such as those encountered with high-fidelity patient simulators. We tested the benefits of learning cardiac arrest procedures using a multimedia computer screen-based simulator in 28 Year 2 medical students. Just before the end of the traditional resuscitation course, we compared two groups. An experiment group (EG) was first asked to learn to perform the appropriate procedures in a cardiac arrest scenario (CA1) in the computer screen-based learning environment and was then tested on a high-fidelity patient simulator in another cardiac arrest simulation (CA2). While the EG was learning to perform CA1 procedures in the computer screen-based learning environment, a control group (CG) actively continued to learn cardiac arrest procedures using practical exercises in a traditional class environment. Both groups were given the same amount of practice, exercises and trials. The CG was then also tested on the high-fidelity patient simulator for CA2, after which it was asked to perform CA1 using the computer screen-based simulator. Performances with both simulators were scored on a precise 23-point scale. On the test on a high-fidelity patient simulator, the EG trained with a multimedia computer screen-based simulator performed significantly better than the CG trained with traditional exercises and practice (16.21 versus 11.13 of 23 possible points, respectively; p<0.001). Computer screen-based simulation appears to be effective in preparing learners to

Parallel Backprojection: A Case Study in High-Performance Reconfigurable Computing

Directory of Open Access Journals (Sweden)

Cordes Ben

2009-01-01

Full Text Available High-performance reconfigurable computing (HPRC is a novel approach to provide large-scale computing power to modern scientific applications. Using both general-purpose processors and FPGAs allows application designers to exploit fine-grained and coarse-grained parallelism, achieving high degrees of speedup. One scientific application that benefits from this technique is backprojection, an image formation algorithm that can be used as part of a synthetic aperture radar (SAR processing system. We present an implementation of backprojection for SAR on an HPRC system. Using simulated data taken at a variety of ranges, our implementation runs over 200 times faster than a similar software program, with an overall application speedup better than 50x. The backprojection application is easily parallelizable, achieving near-linear speedup when run on multiple nodes of a clustered HPRC system. The results presented can be applied to other systems and other algorithms with similar characteristics.

Parallel Backprojection: A Case Study in High-Performance Reconfigurable Computing

Directory of Open Access Journals (Sweden)

2009-03-01

Full Text Available High-performance reconfigurable computing (HPRC is a novel approach to provide large-scale computing power to modern scientific applications. Using both general-purpose processors and FPGAs allows application designers to exploit fine-grained and coarse-grained parallelism, achieving high degrees of speedup. One scientific application that benefits from this technique is backprojection, an image formation algorithm that can be used as part of a synthetic aperture radar (SAR processing system. We present an implementation of backprojection for SAR on an HPRC system. Using simulated data taken at a variety of ranges, our implementation runs over 200 times faster than a similar software program, with an overall application speedup better than 50x. The backprojection application is easily parallelizable, achieving near-linear speedup when run on multiple nodes of a clustered HPRC system. The results presented can be applied to other systems and other algorithms with similar characteristics.

High performance computing environment for multidimensional image analysis.

Science.gov (United States)

Rao, A Ravishankar; Cecchi, Guillermo A; Magnasco, Marcelo

2007-07-10

The processing of images acquired through microscopy is a challenging task due to the large size of datasets (several gigabytes) and the fast turnaround time required. If the throughput of the image processing stage is significantly increased, it can have a major impact in microscopy applications. We present a high performance computing (HPC) solution to this problem. This involves decomposing the spatial 3D image into segments that are assigned to unique processors, and matched to the 3D torus architecture of the IBM Blue Gene/L machine. Communication between segments is restricted to the nearest neighbors. When running on a 2 Ghz Intel CPU, the task of 3D median filtering on a typical 256 megabyte dataset takes two and a half hours, whereas by using 1024 nodes of Blue Gene, this task can be performed in 18.8 seconds, a 478x speedup. Our parallel solution dramatically improves the performance of image processing, feature extraction and 3D reconstruction tasks. This increased throughput permits biologists to conduct unprecedented large scale experiments with massive datasets.

Development of high performance scientific components for interoperability of computing packages

Energy Technology Data Exchange (ETDEWEB)

Gulabani, Teena Pratap [Iowa State Univ., Ames, IA (United States)

2008-01-01

Three major high performance quantum chemistry computational packages, NWChem, GAMESS and MPQC have been developed by different research efforts following different design patterns. The goal is to achieve interoperability among these packages by overcoming the challenges caused by the different communication patterns and software design of each of these packages. A chemistry algorithm is hard to develop as well as being a time consuming process; integration of large quantum chemistry packages will allow resource sharing and thus avoid reinvention of the wheel. Creating connections between these incompatible packages is the major motivation of the proposed work. This interoperability is achieved by bringing the benefits of Component Based Software Engineering through a plug-and-play component framework called Common Component Architecture (CCA). In this thesis, I present a strategy and process used for interfacing two widely used and important computational chemistry methodologies: Quantum Mechanics and Molecular Mechanics. To show the feasibility of the proposed approach the Tuning and Analysis Utility (TAU) has been coupled with NWChem code and its CCA components. Results show that the overhead is negligible when compared to the ease and potential of organizing and coping with large-scale software applications.

Multi-Language Programming Environments for High Performance Java Computing

Directory of Open Access Journals (Sweden)

Vladimir Getov

1999-01-01

Full Text Available Recent developments in processor capabilities, software tools, programming languages and programming paradigms have brought about new approaches to high performance computing. A steadfast component of this dynamic evolution has been the scientific community’s reliance on established scientific packages. As a consequence, programmers of high‐performance applications are reluctant to embrace evolving languages such as Java. This paper describes the Java‐to‐C Interface (JCI tool which provides application programmers wishing to use Java with immediate accessibility to existing scientific packages. The JCI tool also facilitates rapid development and reuse of existing code. These benefits are provided at minimal cost to the programmer. While beneficial to the programmer, the additional advantages of mixed‐language programming in terms of application performance and portability are addressed in detail within the context of this paper. In addition, we discuss how the JCI tool is complementing other ongoing projects such as IBM’s High‐Performance Compiler for Java (HPCJ and IceT’s metacomputing environment.

What Physicists Should Know About High Performance Computing - Circa 2002

Science.gov (United States)

Frederick, Donald

2002-08-01

High Performance Computing (HPC) is a dynamic, cross-disciplinary field that traditionally has involved applied mathematicians, computer scientists, and others primarily from the various disciplines that have been major users of HPC resources - physics, chemistry, engineering, with increasing use by those in the life sciences. There is a technological dynamic that is powered by economic as well as by technical innovations and developments. This talk will discuss practical ideas to be considered when developing numerical applications for research purposes. Even with the rapid pace of development in the field, the author believes that these concepts will not become obsolete for a while, and will be of use to scientists who either are considering, or who have already started down the HPC path. These principles will be applied in particular to current parallel HPC systems, but there will also be references of value to desktop users. The talk will cover such topics as: computing hardware basics, single-cpu optimization, compilers, timing, numerical libraries, debugging and profiling tools and the emergence of Computational Grids.

RISC Processors and High Performance Computing

Science.gov (United States)

Bailey, David H.; Saini, Subhash; Craw, James M. (Technical Monitor)

1995-01-01

This tutorial will discuss the top five RISC microprocessors and the parallel systems in which they are used. It will provide a unique cross-machine comparison not available elsewhere. The effective performance of these processors will be compared by citing standard benchmarks in the context of real applications. The latest NAS Parallel Benchmarks, both absolute performance and performance per dollar, will be listed. The next generation of the NPB will be described. The tutorial will conclude with a discussion of future directions in the field. Technology Transfer Considerations: All of these computer systems are commercially available internationally. Information about these processors is available in the public domain, mostly from the vendors themselves. The NAS Parallel Benchmarks and their results have been previously approved numerous times for public release, beginning back in 1991.

Comprehensive Simulation Lifecycle Management for High Performance Computing Modeling and Simulation, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — There are significant logistical barriers to entry-level high performance computing (HPC) modeling and simulation (M IllinoisRocstar) sets up the infrastructure for...

How to build a high-performance compute cluster for the Grid

CERN Document Server

Reinefeld, A

2001-01-01

The success of large-scale multi-national projects like the forthcoming analysis of the LHC particle collision data at CERN relies to a great extent on the ability to efficiently utilize computing and data-storage resources at geographically distributed sites. Currently, much effort is spent on the design of Grid management software (Datagrid, Globus, etc.), while the effective integration of computing nodes has been largely neglected up to now. This is the focus of our work. We present a framework for a high- performance cluster that can be used as a reliable computing node in the Grid. We outline the cluster architecture, the management of distributed data and the seamless integration of the cluster into the Grid environment. (11 refs).

Big Data and High-Performance Computing in Global Seismology

Science.gov (United States)

Bozdag, Ebru; Lefebvre, Matthieu; Lei, Wenjie; Peter, Daniel; Smith, James; Komatitsch, Dimitri; Tromp, Jeroen

2014-05-01

Much of our knowledge of Earth's interior is based on seismic observations and measurements. Adjoint methods provide an efficient way of incorporating 3D full wave propagation in iterative seismic inversions to enhance tomographic images and thus our understanding of processes taking place inside the Earth. Our aim is to take adjoint tomography, which has been successfully applied to regional and continental scale problems, further to image the entire planet. This is one of the extreme imaging challenges in seismology, mainly due to the intense computational requirements and vast amount of high-quality seismic data that can potentially be assimilated. We have started low-resolution inversions (T > 30 s and T > 60 s for body and surface waves, respectively) with a limited data set (253 carefully selected earthquakes and seismic data from permanent and temporary networks) on Oak Ridge National Laboratory's Cray XK7 "Titan" system. Recent improvements in our 3D global wave propagation solvers, such as a GPU version of the SPECFEM3D_GLOBE package, will enable us perform higher-resolution (T > 9 s) and longer duration (~180 m) simulations to take the advantage of high-frequency body waves and major-arc surface waves, thereby improving imbalanced ray coverage as a result of the uneven global distribution of sources and receivers. Our ultimate goal is to use all earthquakes in the global CMT catalogue within the magnitude range of our interest and data from all available seismic networks. To take the full advantage of computational resources, we need a solid framework to manage big data sets during numerical simulations, pre-processing (i.e., data requests and quality checks, processing data, window selection, etc.) and post-processing (i.e., pre-conditioning and smoothing kernels, etc.). We address the bottlenecks in our global seismic workflow, which are mainly coming from heavy I/O traffic during simulations and the pre- and post-processing stages, by defining new data

High-Performance Computing in Neuroscience for Data-Driven Discovery, Integration, and Dissemination

International Nuclear Information System (INIS)

Bouchard, Kristofer E.

2016-01-01

A lack of coherent plans to analyze, manage, and understand data threatens the various opportunities offered by new neuro-technologies. High-performance computing will allow exploratory analysis of massive datasets stored in standardized formats, hosted in open repositories, and integrated with simulations.

High Performance Computing - Power Application Programming Interface Specification Version 2.0.

Energy Technology Data Exchange (ETDEWEB)

Laros, James H. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Grant, Ryan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Levenhagen, Michael J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Olivier, Stephen Lecler [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Pedretti, Kevin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ward, H. Lee [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Younge, Andrew J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-03-01

Measuring and controlling the power and energy consumption of high performance computing systems by various components in the software stack is an active research area. Implementations in lower level software layers are beginning to emerge in some production systems, which is very welcome. To be most effective, a portable interface to measurement and control features would significantly facilitate participation by all levels of the software stack. We present a proposal for a standard power Application Programming Interface (API) that endeavors to cover the entire software space, from generic hardware interfaces to the input from the computer facility manager.

Computer versus paper--does it make any difference in test performance?

Science.gov (United States)

Karay, Yassin; Schauber, Stefan K; Stosch, Christoph; Schüttpelz-Brauns, Katrin

2015-01-01

CONSTRUCT: In this study, we examine the differences in test performance between the paper-based and the computer-based version of the Berlin formative Progress Test. In this context it is the first study that allows controlling for students' prior performance. Computer-based tests make possible a more efficient examination procedure for test administration and review. Although university staff will benefit largely from computer-based tests, the question arises if computer-based tests influence students' test performance. A total of 266 German students from the 9th and 10th semester of medicine (comparable with the 4th-year North American medical school schedule) participated in the study (paper = 132, computer = 134). The allocation of the test format was conducted as a randomized matched-pair design in which students were first sorted according to their prior test results. The organizational procedure, the examination conditions, the room, and seating arrangements, as well as the order of questions and answers, were identical in both groups. The sociodemographic variables and pretest scores of both groups were comparable. The test results from the paper and computer versions did not differ. The groups remained within the allotted time, but students using the computer version (particularly the high performers) needed significantly less time to complete the test. In addition, we found significant differences in guessing behavior. Low performers using the computer version guess significantly more than low-performing students in the paper-pencil version. Participants in computer-based tests are not at a disadvantage in terms of their test results. The computer-based test required less processing time. The reason for the longer processing time when using the paper-pencil version might be due to the time needed to write the answer down, controlling for transferring the answer correctly. It is still not known why students using the computer version (particularly low-performing

Super-scalar RAM-CPU cache compression

NARCIS (Netherlands)

M. Zukowski (Marcin); S. Héman (Sándor); N.J. Nes (Niels); P.A. Boncz (Peter)

2005-01-01

textabstractHigh-performance data-intensive query processing tasks like OLAP, data mining or scientific data analysis can be severely I/O bound, even when high-end RAID storage systems are used. Compression can alleviate this bottleneck only if encoding and decoding speeds significantly exceed RAID

Super-Scalar RAM-CPU Cache Compression

NARCIS (Netherlands)

M. Zukowski (Marcin); S. Héman (Sándor); N.J. Nes (Niels); P.A. Boncz (Peter)

2006-01-01

textabstractHigh-performance data-intensive query processing tasks like OLAP, data mining or scientific data analysis can be severely I/O bound, even when high-end RAID storage systems are used. Compression can alleviate this bottleneck only if encoding and decoding speeds significantly exceed RAID

BEAGLE: an application programming interface and high-performance computing library for statistical phylogenetics.

Science.gov (United States)

Ayres, Daniel L; Darling, Aaron; Zwickl, Derrick J; Beerli, Peter; Holder, Mark T; Lewis, Paul O; Huelsenbeck, John P; Ronquist, Fredrik; Swofford, David L; Cummings, Michael P; Rambaut, Andrew; Suchard, Marc A

2012-01-01

Phylogenetic inference is fundamental to our understanding of most aspects of the origin and evolution of life, and in recent years, there has been a concentration of interest in statistical approaches such as Bayesian inference and maximum likelihood estimation. Yet, for large data sets and realistic or interesting models of evolution, these approaches remain computationally demanding. High-throughput sequencing can yield data for thousands of taxa, but scaling to such problems using serial computing often necessitates the use of nonstatistical or approximate approaches. The recent emergence of graphics processing units (GPUs) provides an opportunity to leverage their excellent floating-point computational performance to accelerate statistical phylogenetic inference. A specialized library for phylogenetic calculation would allow existing software packages to make more effective use of available computer hardware, including GPUs. Adoption of a common library would also make it easier for other emerging computing architectures, such as field programmable gate arrays, to be used in the future. We present BEAGLE, an application programming interface (API) and library for high-performance statistical phylogenetic inference. The API provides a uniform interface for performing phylogenetic likelihood calculations on a variety of compute hardware platforms. The library includes a set of efficient implementations and can currently exploit hardware including GPUs using NVIDIA CUDA, central processing units (CPUs) with Streaming SIMD Extensions and related processor supplementary instruction sets, and multicore CPUs via OpenMP. To demonstrate the advantages of a common API, we have incorporated the library into several popular phylogenetic software packages. The BEAGLE library is free open source software licensed under the Lesser GPL and available from http://beagle-lib.googlecode.com. An example client program is available as public domain software.

Integrated State Estimation and Contingency Analysis Software Implementation using High Performance Computing Techniques

Energy Technology Data Exchange (ETDEWEB)

Chen, Yousu; Glaesemann, Kurt R.; Rice, Mark J.; Huang, Zhenyu

2015-12-31

Power system simulation tools are traditionally developed in sequential mode and codes are optimized for single core computing only. However, the increasing complexity in the power grid models requires more intensive computation. The traditional simulation tools will soon not be able to meet the grid operation requirements. Therefore, power system simulation tools need to evolve accordingly to provide faster and better results for grid operations. This paper presents an integrated state estimation and contingency analysis software implementation using high performance computing techniques. The software is able to solve large size state estimation problems within one second and achieve a near-linear speedup of 9,800 with 10,000 cores for contingency analysis application. The performance evaluation is presented to show its effectiveness.

Acquiring skills in malignant hyperthermia crisis management: comparison of high-fidelity simulation versus computer-based case study

Directory of Open Access Journals (Sweden)

Vilma Mejía

Full Text Available Abstract Introduction: The primary purpose of this study was to compare the effect of high fidelity simulation versus a computer-based case solving self-study, in skills acquisition about malignant hyperthermia on first year anesthesiology residents. Methods: After institutional ethical committee approval, 31 first year anesthesiology residents were enrolled in this prospective randomized single-blinded study. Participants were randomized to either a High Fidelity Simulation Scenario or a computer-based Case Study about malignant hyperthermia. After the intervention, all subjects' performance in was assessed through a high fidelity simulation scenario using a previously validated assessment rubric. Additionally, knowledge tests and a satisfaction survey were applied. Finally, a semi-structured interview was done to assess self-perception of reasoning process and decision-making. Results: 28 first year residents finished successfully the study. Resident's management skill scores were globally higher in High Fidelity Simulation versus Case Study, however they were significant in 4 of the 8 performance rubric elements: recognize signs and symptoms (p = 0.025, prioritization of initial actions of management (p = 0.003, recognize complications (p = 0.025 and communication (p = 0.025. Average scores from pre- and post-test knowledge questionnaires improved from 74% to 85% in the High Fidelity Simulation group, and decreased from 78% to 75% in the Case Study group (p = 0.032. Regarding the qualitative analysis, there was no difference in factors influencing the student's process of reasoning and decision-making with both teaching strategies. Conclusion: Simulation-based training with a malignant hyperthermia high-fidelity scenario was superior to computer-based case study, improving knowledge and skills in malignant hyperthermia crisis management, with a very good satisfaction level in anesthesia residents.

A database for CO2 Separation Performances of MOFs based on Computational Materials Screening.

Science.gov (United States)

Altintas, Cigdem; Avci, Gokay; Daglar, Hilal; Nemati Vesali Azar, Ayda; Velioglu, Sadiye; Erucar, Ilknur; Keskin, Seda

2018-05-03

Metal organic frameworks (MOFs) have been considered as great candidates for CO2 capture. Considering the very large number of available MOFs, high-throughput computational screening plays a critical role in identifying the top performing materials for target applications in a time-effective manner. In this work, we used molecular simulations to screen the most recent and complete MOF database for identifying the most promising materials for CO2 separation from flue gas (CO2/N2) and landfill gas (CO2/CH4) under realistic operating conditions. We first validated our approach by comparing the results of our molecular simulations for the CO2 uptakes, CO2/N2 and CO2/CH4 selectivities of various types of MOFs with the available experimental data. We then computed binary CO2/N2 and CO2/CH4 mixture adsorption data for the entire MOF database and used these results to calculate several adsorbent selection metrics such as selectivity, working capacity, adsorbent performance score, regenerability, and separation potential. MOFs were ranked based on the combination of these metrics and the top performing MOF adsorbents that can achieve CO2/N2 and CO2/CH4 separations with high performance were identified. Molecular simulations for the adsorption of a ternary CO2/N2/CH4 mixture were performed for these top materials in order to provide a more realistic performance assessment of MOF adsorbents. Structure-performance analysis showed that MOFs with ΔQ>30 kJ/mol, 3.8 A≤PLD≤5 A, 5 A≤LCD≤7.5 A, 0.5≤ϕ≤0.75, SA≤1,000 m2/g, ρ>1 g/cm 3 are the best candidates for selective separation of CO2 from flue gas and landfill gas. This information will be very useful to design novel MOFs with the desired structural features that can lead to high CO2 separation potentials. Finally, an online, freely accessible database https://cosmoserc.ku.edu.tr was established, for the first time in the literature, which reports all computed adsorbent metrics of 3,816 MOFs for CO2/N2, CO2/CH4

The Centre of High-Performance Scientific Computing, Geoverbund, ABC/J - Geosciences enabled by HPSC

Science.gov (United States)

Kollet, Stefan; Görgen, Klaus; Vereecken, Harry; Gasper, Fabian; Hendricks-Franssen, Harrie-Jan; Keune, Jessica; Kulkarni, Ketan; Kurtz, Wolfgang; Sharples, Wendy; Shrestha, Prabhakar; Simmer, Clemens; Sulis, Mauro; Vanderborght, Jan

2016-04-01

The Centre of High-Performance Scientific Computing (HPSC TerrSys) was founded 2011 to establish a centre of competence in high-performance scientific computing in terrestrial systems and the geosciences enabling fundamental and applied geoscientific research in the Geoverbund ABC/J (geoscientfic research alliance of the Universities of Aachen, Cologne, Bonn and the Research Centre Jülich, Germany). The specific goals of HPSC TerrSys are to achieve relevance at the national and international level in (i) the development and application of HPSC technologies in the geoscientific community; (ii) student education; (iii) HPSC services and support also to the wider geoscientific community; and in (iv) the industry and public sectors via e.g., useful applications and data products. A key feature of HPSC TerrSys is the Simulation Laboratory Terrestrial Systems, which is located at the Jülich Supercomputing Centre (JSC) and provides extensive capabilities with respect to porting, profiling, tuning and performance monitoring of geoscientific software in JSC's supercomputing environment. We will present a summary of success stories of HPSC applications including integrated terrestrial model development, parallel profiling and its application from watersheds to the continent; massively parallel data assimilation using physics-based models and ensemble methods; quasi-operational terrestrial water and energy monitoring; and convection permitting climate simulations over Europe. The success stories stress the need for a formalized education of students in the application of HPSC technologies in future.

Trends in high-performance computing for engineering calculations.

Science.gov (United States)

Giles, M B; Reguly, I

2014-08-13

High-performance computing has evolved remarkably over the past 20 years, and that progress is likely to continue. However, in recent years, this progress has been achieved through greatly increased hardware complexity with the rise of multicore and manycore processors, and this is affecting the ability of application developers to achieve the full potential of these systems. This article outlines the key developments on the hardware side, both in the recent past and in the near future, with a focus on two key issues: energy efficiency and the cost of moving data. It then discusses the much slower evolution of system software, and the implications of all of this for application developers. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Linear Subpixel Learning Algorithm for Land Cover Classification from WELD using High Performance Computing

Science.gov (United States)

Ganguly, S.; Kumar, U.; Nemani, R. R.; Kalia, S.; Michaelis, A.

2017-12-01

In this work, we use a Fully Constrained Least Squares Subpixel Learning Algorithm to unmix global WELD (Web Enabled Landsat Data) to obtain fractions or abundances of substrate (S), vegetation (V) and dark objects (D) classes. Because of the sheer nature of data and compute needs, we leveraged the NASA Earth Exchange (NEX) high performance computing architecture to optimize and scale our algorithm for large-scale processing. Subsequently, the S-V-D abundance maps were characterized into 4 classes namely, forest, farmland, water and urban areas (with NPP-VIIRS - national polar orbiting partnership visible infrared imaging radiometer suite nighttime lights data) over California, USA using Random Forest classifier. Validation of these land cover maps with NLCD (National Land Cover Database) 2011 products and NAFD (North American Forest Dynamics) static forest cover maps showed that an overall classification accuracy of over 91% was achieved, which is a 6% improvement in unmixing based classification relative to per-pixel based classification. As such, abundance maps continue to offer an useful alternative to high-spatial resolution data derived classification maps for forest inventory analysis, multi-class mapping for eco-climatic models and applications, fast multi-temporal trend analysis and for societal and policy-relevant applications needed at the watershed scale.

Design and Implementation of High-Performance GIS Dynamic Objects Rendering Engine

Science.gov (United States)

Zhong, Y.; Wang, S.; Li, R.; Yun, W.; Song, G.

2017-12-01

Spatio-temporal dynamic visualization is more vivid than static visualization. It important to use dynamic visualization techniques to reveal the variation process and trend vividly and comprehensively for the geographical phenomenon. To deal with challenges caused by dynamic visualization of both 2D and 3D spatial dynamic targets, especially for different spatial data types require high-performance GIS dynamic objects rendering engine. The main approach for improving the rendering engine with vast dynamic targets relies on key technologies of high-performance GIS, including memory computing, parallel computing, GPU computing and high-performance algorisms. In this study, high-performance GIS dynamic objects rendering engine is designed and implemented for solving the problem based on hybrid accelerative techniques. The high-performance GIS rendering engine contains GPU computing, OpenGL technology, and high-performance algorism with the advantage of 64-bit memory computing. It processes 2D, 3D dynamic target data efficiently and runs smoothly with vast dynamic target data. The prototype system of high-performance GIS dynamic objects rendering engine is developed based SuperMap GIS iObjects. The experiments are designed for large-scale spatial data visualization, the results showed that the high-performance GIS dynamic objects rendering engine have the advantage of high performance. Rendering two-dimensional and three-dimensional dynamic objects achieve 20 times faster on GPU than on CPU.

High Performance Motion-Planner Architecture for Hardware-In-the-Loop System Based on Position-Based-Admittance-Control

Directory of Open Access Journals (Sweden)

Francesco La Mura

2018-02-01

Full Text Available This article focuses on a Hardware-In-the-Loop application developed from the advanced energy field project LIFES50+. The aim is to replicate, inside a wind gallery test facility, the combined effect of aerodynamic and hydrodynamic loads on a floating wind turbine model for offshore energy production, using a force controlled robotic device, emulating floating substructure’s behaviour. In addition to well known real-time Hardware-In-the-Loop (HIL issues, the particular application presented has stringent safety requirements of the HIL equipment and difficult to predict operating conditions, so that extra computational efforts have to be spent running specific safety algorithms and achieving desired performance. To meet project requirements, a high performance software architecture based on Position-Based-Admittance-Control (PBAC is presented, combining low level motion interpolation techniques, efficient motion planning, based on buffer management and Time-base control, and advanced high level safety algorithms, implemented in a rapid real-time control architecture.

Replica-Based High-Performance Tuple Space Computing

DEFF Research Database (Denmark)

Andric, Marina; De Nicola, Rocco; Lluch Lafuente, Alberto

2015-01-01

of concurrency and data access. We investigate issues related to replica consistency, provide an operational semantics that guides the implementation of the language, and discuss the main synchronization mechanisms of our prototypical run-time framework. Finally, we provide a performance analysis, which includes...

Optical high-performance computing: introduction to the JOSA A and Applied Optics feature.

Science.gov (United States)

Caulfield, H John; Dolev, Shlomi; Green, William M J

2009-08-01

The feature issues in both Applied Optics and the Journal of the Optical Society of America A focus on topics of immediate relevance to the community working in the area of optical high-performance computing.

Performance Analysis of Ivshmem for High-Performance Computing in Virtual Machines

Science.gov (United States)

Ivanovic, Pavle; Richter, Harald

2018-01-01

High-Performance computing (HPC) is rarely accomplished via virtual machines (VMs). In this paper, we present a remake of ivshmem which can change this. Ivshmem was a shared memory (SHM) between virtual machines on the same server, with SHM-access synchronization included, until about 5 years ago when newer versions of Linux and its virtualization library libvirt evolved. We restored that SHM-access synchronization feature because it is indispensable for HPC and made ivshmem runnable with contemporary versions of Linux, libvirt, KVM, QEMU and especially MPICH, which is an implementation of MPI - the standard HPC communication library. Additionally, MPICH was transparently modified by us to get ivshmem included, resulting in a three to ten times performance improvement compared to TCP/IP. Furthermore, we have transparently replaced MPI_PUT, a single-side MPICH communication mechanism, by an own MPI_PUT wrapper. As a result, our ivshmem even surpasses non-virtualized SHM data transfers for block lengths greater than 512 KBytes, showing the benefits of virtualization. All improvements were possible without using SR-IOV.

Use of high performance computing to examine the effectiveness of aquifer remediation

International Nuclear Information System (INIS)

Tompson, A.F.B.; Ashby, S.F.; Falgout, R.D.; Smith, S.G.; Fogwell, T.W.; Loosmore, G.A.

1994-06-01

Large-scale simulation of fluid flow and chemical migration is being used to study the effectiveness of pump-and-treat restoration of a contaminated, saturated aquifer. A three-element approach focusing on geostatistical representations of heterogeneous aquifers, high-performance computing strategies for simulating flow, migration, and reaction processes in large three-dimensional systems, and highly-resolved simulations of flow and chemical migration in porous formations will be discussed. Results from a preliminary application of this approach to examine pumping behavior at a real, heterogeneous field site will be presented. Future activities will emphasize parallel computations in larger, dynamic, and nonlinear (two-phase) flow problems as well as improved interpretive methods for defining detailed material property distributions

Direct numerical simulation of reactor two-phase flows enabled by high-performance computing

Energy Technology Data Exchange (ETDEWEB)

Fang, Jun; Cambareri, Joseph J.; Brown, Cameron S.; Feng, Jinyong; Gouws, Andre; Li, Mengnan; Bolotnov, Igor A.

2018-04-01

Nuclear reactor two-phase flows remain a great engineering challenge, where the high-resolution two-phase flow database which can inform practical model development is still sparse due to the extreme reactor operation conditions and measurement difficulties. Owing to the rapid growth of computing power, the direct numerical simulation (DNS) is enjoying a renewed interest in investigating the related flow problems. A combination between DNS and an interface tracking method can provide a unique opportunity to study two-phase flows based on first principles calculations. More importantly, state-of-the-art high-performance computing (HPC) facilities are helping unlock this great potential. This paper reviews the recent research progress of two-phase flow DNS related to reactor applications. The progress in large-scale bubbly flow DNS has been focused not only on the sheer size of those simulations in terms of resolved Reynolds number, but also on the associated advanced modeling and analysis techniques. Specifically, the current areas of active research include modeling of sub-cooled boiling, bubble coalescence, as well as the advanced post-processing toolkit for bubbly flow simulations in reactor geometries. A novel bubble tracking method has been developed to track the evolution of bubbles in two-phase bubbly flow. Also, spectral analysis of DNS database in different geometries has been performed to investigate the modulation of the energy spectrum slope due to bubble-induced turbulence. In addition, the single-and two-phase analysis results are presented for turbulent flows within the pressurized water reactor (PWR) core geometries. The related simulations are possible to carry out only with the world leading HPC platforms. These simulations are allowing more complex turbulence model development and validation for use in 3D multiphase computational fluid dynamics (M-CFD) codes.

7th International Workshop on Parallel Tools for High Performance Computing

CERN Document Server

Gracia, José; Nagel, Wolfgang; Resch, Michael

2014-01-01

Current advances in High Performance Computing (HPC) increasingly impact efficient software development workflows. Programmers for HPC applications need to consider trends such as increased core counts, multiple levels of parallelism, reduced memory per core, and I/O system challenges in order to derive well performing and highly scalable codes. At the same time, the increasing complexity adds further sources of program defects. While novel programming paradigms and advanced system libraries provide solutions for some of these challenges, appropriate supporting tools are indispensable. Such tools aid application developers in debugging, performance analysis, or code optimization and therefore make a major contribution to the development of robust and efficient parallel software. This book introduces a selection of the tools presented and discussed at the 7th International Parallel Tools Workshop, held in Dresden, Germany, September 3-4, 2013.  

Low-cost, high-performance and efficiency computational photometer design

Science.gov (United States)

Siewert, Sam B.; Shihadeh, Jeries; Myers, Randall; Khandhar, Jay; Ivanov, Vitaly

2014-05-01

Researchers at the University of Alaska Anchorage and University of Colorado Boulder have built a low cost high performance and efficiency drop-in-place Computational Photometer (CP) to test in field applications ranging from port security and safety monitoring to environmental compliance monitoring and surveying. The CP integrates off-the-shelf visible spectrum cameras with near to long wavelength infrared detectors and high resolution digital snapshots in a single device. The proof of concept combines three or more detectors into a single multichannel imaging system that can time correlate read-out, capture, and image process all of the channels concurrently with high performance and energy efficiency. The dual-channel continuous read-out is combined with a third high definition digital snapshot capability and has been designed using an FPGA (Field Programmable Gate Array) to capture, decimate, down-convert, re-encode, and transform images from two standard definition CCD (Charge Coupled Device) cameras at 30Hz. The continuous stereo vision can be time correlated to megapixel high definition snapshots. This proof of concept has been fabricated as a fourlayer PCB (Printed Circuit Board) suitable for use in education and research for low cost high efficiency field monitoring applications that need multispectral and three dimensional imaging capabilities. Initial testing is in progress and includes field testing in ports, potential test flights in un-manned aerial systems, and future planned missions to image harsh environments in the arctic including volcanic plumes, ice formation, and arctic marine life.

Open source acceleration of wave optics simulations on energy efficient high-performance computing platforms

Science.gov (United States)

Beck, Jeffrey; Bos, Jeremy P.

2017-05-01

We compare several modifications to the open-source wave optics package, WavePy, intended to improve execution time. Specifically, we compare the relative performance of the Intel MKL, a CPU based OpenCV distribution, and GPU-based version. Performance is compared between distributions both on the same compute platform and between a fully-featured computing workstation and the NVIDIA Jetson TX1 platform. Comparisons are drawn in terms of both execution time and power consumption. We have found that substituting the Fast Fourier Transform operation from OpenCV provides a marked improvement on all platforms. In addition, we show that embedded platforms offer some possibility for extensive improvement in terms of efficiency compared to a fully featured workstation.

High performance systems

Energy Technology Data Exchange (ETDEWEB)

Vigil, M.B. [comp.

1995-03-01

This document provides a written compilation of the presentations and viewgraphs from the 1994 Conference on High Speed Computing given at the High Speed Computing Conference, {open_quotes}High Performance Systems,{close_quotes} held at Gleneden Beach, Oregon, on April 18 through 21, 1994.

Department of Energy Mathematical, Information, and Computational Sciences Division: High Performance Computing and Communications Program

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-11-01

This document is intended to serve two purposes. Its first purpose is that of a program status report of the considerable progress that the Department of Energy (DOE) has made since 1993, the time of the last such report (DOE/ER-0536, The DOE Program in HPCC), toward achieving the goals of the High Performance Computing and Communications (HPCC) Program. The second purpose is that of a summary report of the many research programs administered by the Mathematical, Information, and Computational Sciences (MICS) Division of the Office of Energy Research under the auspices of the HPCC Program and to provide, wherever relevant, easy access to pertinent information about MICS-Division activities via universal resource locators (URLs) on the World Wide Web (WWW).

A performance model for the communication in fast multipole methods on high-performance computing platforms

KAUST Repository

Ibeid, Huda

2016-03-04

Exascale systems are predicted to have approximately 1 billion cores, assuming gigahertz cores. Limitations on affordable network topologies for distributed memory systems of such massive scale bring new challenges to the currently dominant parallel programing model. Currently, there are many efforts to evaluate the hardware and software bottlenecks of exascale designs. It is therefore of interest to model application performance and to understand what changes need to be made to ensure extrapolated scalability. The fast multipole method (FMM) was originally developed for accelerating N-body problems in astrophysics and molecular dynamics but has recently been extended to a wider range of problems. Its high arithmetic intensity combined with its linear complexity and asynchronous communication patterns make it a promising algorithm for exascale systems. In this paper, we discuss the challenges for FMM on current parallel computers and future exascale architectures, with a focus on internode communication. We focus on the communication part only; the efficiency of the computational kernels are beyond the scope of the present study. We develop a performance model that considers the communication patterns of the FMM and observe a good match between our model and the actual communication time on four high-performance computing (HPC) systems, when latency, bandwidth, network topology, and multicore penalties are all taken into account. To our knowledge, this is the first formal characterization of internode communication in FMM that validates the model against actual measurements of communication time. The ultimate communication model is predictive in an absolute sense; however, on complex systems, this objective is often out of reach or of a difficulty out of proportion to its benefit when there exists a simpler model that is inexpensive and sufficient to guide coding decisions leading to improved scaling. The current model provides such guidance.

[Acquiring skills in malignant hyperthermia crisis management: comparison of high-fidelity simulation versus computer-based case study].

Science.gov (United States)

Mejía, Vilma; Gonzalez, Carlos; Delfino, Alejandro E; Altermatt, Fernando R; Corvetto, Marcia A

The primary purpose of this study was to compare the effect of high fidelity simulation versus a computer-based case solving self-study, in skills acquisition about malignant hyperthermia on first year anesthesiology residents. After institutional ethical committee approval, 31 first year anesthesiology residents were enrolled in this prospective randomized single-blinded study. Participants were randomized to either a High Fidelity Simulation Scenario or a computer-based Case Study about malignant hyperthermia. After the intervention, all subjects' performance in was assessed through a high fidelity simulation scenario using a previously validated assessment rubric. Additionally, knowledge tests and a satisfaction survey were applied. Finally, a semi-structured interview was done to assess self-perception of reasoning process and decision-making. 28 first year residents finished successfully the study. Resident's management skill scores were globally higher in High Fidelity Simulation versus Case Study, however they were significant in 4 of the 8 performance rubric elements: recognize signs and symptoms (p = 0.025), prioritization of initial actions of management (p = 0.003), recognize complications (p = 0.025) and communication (p = 0.025). Average scores from pre- and post-test knowledge questionnaires improved from 74% to 85% in the High Fidelity Simulation group, and decreased from 78% to 75% in the Case Study group (p = 0.032). Regarding the qualitative analysis, there was no difference in factors influencing the student's process of reasoning and decision-making with both teaching strategies. Simulation-based training with a malignant hyperthermia high-fidelity scenario was superior to computer-based case study, improving knowledge and skills in malignant hyperthermia crisis management, with a very good satisfaction level in anesthesia residents. Copyright © 2018 Sociedade Brasileira de Anestesiologia. Publicado por Elsevier Editora Ltda. All rights

Lightweight Provenance Service for High-Performance Computing

Energy Technology Data Exchange (ETDEWEB)

Dai, Dong; Chen, Yong; Carns, Philip; Jenkins, John; Ross, Robert

2017-09-09

Provenance describes detailed information about the history of a piece of data, containing the relationships among elements such as users, processes, jobs, and workflows that contribute to the existence of data. Provenance is key to supporting many data management functionalities that are increasingly important in operations such as identifying data sources, parameters, or assumptions behind a given result; auditing data usage; or understanding details about how inputs are transformed into outputs. Despite its importance, however, provenance support is largely underdeveloped in highly parallel architectures and systems. One major challenge is the demanding requirements of providing provenance service in situ. The need to remain lightweight and to be always on often conflicts with the need to be transparent and offer an accurate catalog of details regarding the applications and systems. To tackle this challenge, we introduce a lightweight provenance service, called LPS, for high-performance computing (HPC) systems. LPS leverages a kernel instrument mechanism to achieve transparency and introduces representative execution and flexible granularity to capture comprehensive provenance with controllable overhead. Extensive evaluations and use cases have confirmed its efficiency and usability. We believe that LPS can be integrated into current and future HPC systems to support a variety of data management needs.

Commercialization issues and funding opportunities for high-performance optoelectronic computing modules

Science.gov (United States)

Hessenbruch, John M.; Guilfoyle, Peter S.

1997-01-01

Low power, optoelectronic integrated circuits are being developed for high speed switching and data processing applications. These high performance optoelectronic computing modules consist of three primary components: vertical cavity surface emitting lasers, diffractive optical interconnect elements, and detector/amplifier/laser driver arrays. Following the design and fabrication of an HPOC module prototype, selected commercial funding sources will be evaluated to support a product development stage. These include the formation of a strategic alliance with one or more microprocessor or telecommunications vendors, and/or equity investment from one or more venture capital firms.

Introducing Computer-Based Testing in High-Stakes Exams in Higher Education: Results of a Field Experiment.

Science.gov (United States)

Boevé, Anja J; Meijer, Rob R; Albers, Casper J; Beetsma, Yta; Bosker, Roel J

2015-01-01

The introduction of computer-based testing in high-stakes examining in higher education is developing rather slowly due to institutional barriers (the need of extra facilities, ensuring test security) and teacher and student acceptance. From the existing literature it is unclear whether computer-based exams will result in similar results as paper-based exams and whether student acceptance can change as a result of administering computer-based exams. In this study, we compared results from a computer-based and paper-based exam in a sample of psychology students and found no differences in total scores across the two modes. Furthermore, we investigated student acceptance and change in acceptance of computer-based examining. After taking the computer-based exam, fifty percent of the students preferred paper-and-pencil exams over computer-based exams and about a quarter preferred a computer-based exam. We conclude that computer-based exam total scores are similar as paper-based exam scores, but that for the acceptance of high-stakes computer-based exams it is important that students practice and get familiar with this new mode of test administration.

Modeling Students' Problem Solving Performance in the Computer-Based Mathematics Learning Environment

Science.gov (United States)

Lee, Young-Jin

2017-01-01

Purpose: The purpose of this paper is to develop a quantitative model of problem solving performance of students in the computer-based mathematics learning environment. Design/methodology/approach: Regularized logistic regression was used to create a quantitative model of problem solving performance of students that predicts whether students can…

Quo vadis: Hydrologic inverse analyses using high-performance computing and a D-Wave quantum annealer

Science.gov (United States)

O'Malley, D.; Vesselinov, V. V.

2017-12-01

Classical microprocessors have had a dramatic impact on hydrology for decades, due largely to the exponential growth in computing power predicted by Moore's law. However, this growth is not expected to continue indefinitely and has already begun to slow. Quantum computing is an emerging alternative to classical microprocessors. Here, we demonstrated cutting edge inverse model analyses utilizing some of the best available resources in both worlds: high-performance classical computing and a D-Wave quantum annealer. The classical high-performance computing resources are utilized to build an advanced numerical model that assimilates data from O(10^5) observations, including water levels, drawdowns, and contaminant concentrations. The developed model accurately reproduces the hydrologic conditions at a Los Alamos National Laboratory contamination site, and can be leveraged to inform decision-making about site remediation. We demonstrate the use of a D-Wave 2X quantum annealer to solve hydrologic inverse problems. This work can be seen as an early step in quantum-computational hydrology. We compare and contrast our results with an early inverse approach in classical-computational hydrology that is comparable to the approach we use with quantum annealing. Our results show that quantum annealing can be useful for identifying regions of high and low permeability within an aquifer. While the problems we consider are small-scale compared to the problems that can be solved with modern classical computers, they are large compared to the problems that could be solved with early classical CPUs. Further, the binary nature of the high/low permeability problem makes it well-suited to quantum annealing, but challenging for classical computers.

9th International Workshop on Parallel Tools for High Performance Computing

CERN Document Server

Hilbrich, Tobias; Niethammer, Christoph; Gracia, José; Nagel, Wolfgang; Resch, Michael

2016-01-01

High Performance Computing (HPC) remains a driver that offers huge potentials and benefits for science and society. However, a profound understanding of the computational matters and specialized software is needed to arrive at effective and efficient simulations. Dedicated software tools are important parts of the HPC software landscape, and support application developers. Even though a tool is by definition not a part of an application, but rather a supplemental piece of software, it can make a fundamental difference during the development of an application. Such tools aid application developers in the context of debugging, performance analysis, and code optimization, and therefore make a major contribution to the development of robust and efficient parallel software. This book introduces a selection of the tools presented and discussed at the 9th International Parallel Tools Workshop held in Dresden, Germany, September 2-3, 2015, which offered an established forum for discussing the latest advances in paral...

High Performance Computing - Power Application Programming Interface Specification Version 1.4

Energy Technology Data Exchange (ETDEWEB)

Laros III, James H. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); DeBonis, David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Grant, Ryan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kelly, Suzanne M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Levenhagen, Michael J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Olivier, Stephen Lecler [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Pedretti, Kevin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2016-10-01

Measuring and controlling the power and energy consumption of high performance computing systems by various components in the software stack is an active research area [13, 3, 5, 10, 4, 21, 19, 16, 7, 17, 20, 18, 11, 1, 6, 14, 12]. Implementations in lower level software layers are beginning to emerge in some production systems, which is very welcome. To be most effective, a portable interface to measurement and control features would significantly facilitate participation by all levels of the software stack. We present a proposal for a standard power Application Programming Interface (API) that endeavors to cover the entire software space, from generic hardware interfaces to the input from the computer facility manager.

Computational design for a wide-angle cermet-based solar selective absorber for high temperature applications

International Nuclear Information System (INIS)

Sakurai, Atsushi; Tanikawa, Hiroya; Yamada, Makoto

2014-01-01

The purpose of this study is to computationally design a wide-angle cermet-based solar selective absorber for high temperature applications by using a characteristic matrix method and a genetic algorithm. The present study investigates a solar selective absorber with tungsten–silica (W–SiO 2 ) cermet. Multilayer structures of 1, 2, 3, and 4 layers and a wide range of metal volume fractions are optimized. The predicted radiative properties show good solar performance, i.e., thermal emittances, especially beyond 2 μm, are quite low, in contrast, solar absorptance levels are successfully high with wide angular range, so that solar photons are effectively absorbed and infrared radiative heat loss can be decreased. -- Highlights: • Electromagnetic simulation of radiative properties by characteristic matrix method. • Optimization for multilayered W–SiO 2 cermet-based absorber by a Genetic Algorithm. • We propose a successfully high solar performance of solar selective absorber

Enabling the ATLAS Experiment at the LHC for High Performance Computing

CERN Document Server

AUTHOR|(CDS)2091107; Ereditato, Antonio

In this thesis, I studied the feasibility of running computer data analysis programs from the Worldwide LHC Computing Grid, in particular large-scale simulations of the ATLAS experiment at the CERN LHC, on current general purpose High Performance Computing (HPC) systems. An approach for integrating HPC systems into the Grid is proposed, which has been implemented and tested on the „Todi” HPC machine at the Swiss National Supercomputing Centre (CSCS). Over the course of the test, more than 500000 CPU-hours of processing time have been provided to ATLAS, which is roughly equivalent to the combined computing power of the two ATLAS clusters at the University of Bern. This showed that current HPC systems can be used to efficiently run large-scale simulations of the ATLAS detector and of the detected physics processes. As a first conclusion of my work, one can argue that, in perspective, running large-scale tasks on a few large machines might be more cost-effective than running on relatively small dedicated com...

Computer holography: 3D digital art based on high-definition CGH

International Nuclear Information System (INIS)

Matsushima, K; Arima, Y; Nishi, H; Yamashita, H; Yoshizaki, Y; Ogawa, K; Nakahara, S

2013-01-01

Our recent works of high-definition computer-generated holograms (CGH) and the techniques used for the creation, such as the polygon-based method, silhouette method and digitized holography, are summarized and reviewed in this paper. The concept of computer holography is proposed in terms of integrating and crystalizing the techniques into novel digital art.

Introducing Computer-Based Testing in High-Stakes Exams in Higher Education: Results of a Field Experiment

Science.gov (United States)

Boevé, Anja J.; Meijer, Rob R.; Albers, Casper J.; Beetsma, Yta; Bosker, Roel J.

2015-01-01

The introduction of computer-based testing in high-stakes examining in higher education is developing rather slowly due to institutional barriers (the need of extra facilities, ensuring test security) and teacher and student acceptance. From the existing literature it is unclear whether computer-based exams will result in similar results as paper-based exams and whether student acceptance can change as a result of administering computer-based exams. In this study, we compared results from a computer-based and paper-based exam in a sample of psychology students and found no differences in total scores across the two modes. Furthermore, we investigated student acceptance and change in acceptance of computer-based examining. After taking the computer-based exam, fifty percent of the students preferred paper-and-pencil exams over computer-based exams and about a quarter preferred a computer-based exam. We conclude that computer-based exam total scores are similar as paper-based exam scores, but that for the acceptance of high-stakes computer-based exams it is important that students practice and get familiar with this new mode of test administration. PMID:26641632

High performance parallel computing of flows in complex geometries: I. Methods

International Nuclear Information System (INIS)

Gourdain, N; Gicquel, L; Montagnac, M; Vermorel, O; Staffelbach, G; Garcia, M; Boussuge, J-F; Gazaix, M; Poinsot, T

2009-01-01

Efficient numerical tools coupled with high-performance computers, have become a key element of the design process in the fields of energy supply and transportation. However flow phenomena that occur in complex systems such as gas turbines and aircrafts are still not understood mainly because of the models that are needed. In fact, most computational fluid dynamics (CFD) predictions as found today in industry focus on a reduced or simplified version of the real system (such as a periodic sector) and are usually solved with a steady-state assumption. This paper shows how to overcome such barriers and how such a new challenge can be addressed by developing flow solvers running on high-end computing platforms, using thousands of computing cores. Parallel strategies used by modern flow solvers are discussed with particular emphases on mesh-partitioning, load balancing and communication. Two examples are used to illustrate these concepts: a multi-block structured code and an unstructured code. Parallel computing strategies used with both flow solvers are detailed and compared. This comparison indicates that mesh-partitioning and load balancing are more straightforward with unstructured grids than with multi-block structured meshes. However, the mesh-partitioning stage can be challenging for unstructured grids, mainly due to memory limitations of the newly developed massively parallel architectures. Finally, detailed investigations show that the impact of mesh-partitioning on the numerical CFD solutions, due to rounding errors and block splitting, may be of importance and should be accurately addressed before qualifying massively parallel CFD tools for a routine industrial use.

High performance statistical computing with parallel R: applications to biology and climate modelling

International Nuclear Information System (INIS)

Samatova, Nagiza F; Branstetter, Marcia; Ganguly, Auroop R; Hettich, Robert; Khan, Shiraj; Kora, Guruprasad; Li, Jiangtian; Ma, Xiaosong; Pan, Chongle; Shoshani, Arie; Yoginath, Srikanth

2006-01-01

Ultrascale computing and high-throughput experimental technologies have enabled the production of scientific data about complex natural phenomena. With this opportunity, comes a new problem - the massive quantities of data so produced. Answers to fundamental questions about the nature of those phenomena remain largely hidden in the produced data. The goal of this work is to provide a scalable high performance statistical data analysis framework to help scientists perform interactive analyses of these raw data to extract knowledge. Towards this goal we have been developing an open source parallel statistical analysis package, called Parallel R, that lets scientists employ a wide range of statistical analysis routines on high performance shared and distributed memory architectures without having to deal with the intricacies of parallelizing these routines

Cloud object store for checkpoints of high performance computing applications using decoupling middleware

Science.gov (United States)

Bent, John M.; Faibish, Sorin; Grider, Gary

2016-04-19

Cloud object storage is enabled for checkpoints of high performance computing applications using a middleware process. A plurality of files, such as checkpoint files, generated by a plurality of processes in a parallel computing system are stored by obtaining said plurality of files from said parallel computing system; converting said plurality of files to objects using a log structured file system middleware process; and providing said objects for storage in a cloud object storage system. The plurality of processes may run, for example, on a plurality of compute nodes. The log structured file system middleware process may be embodied, for example, as a Parallel Log-Structured File System (PLFS). The log structured file system middleware process optionally executes on a burst buffer node.

PERFORMANCE OF A COMPUTER-BASED ASSESSMENT OF COGNITIVE FUNCTION MEASURES IN TWO COHORTS OF SENIORS

Science.gov (United States)

Espeland, Mark A.; Katula, Jeffrey A.; Rushing, Julia; Kramer, Arthur F.; Jennings, Janine M.; Sink, Kaycee M.; Nadkarni, Neelesh K.; Reid, Kieran F.; Castro, Cynthia M.; Church, Timothy; Kerwin, Diana R.; Williamson, Jeff D.; Marottoli, Richard A.; Rushing, Scott; Marsiske, Michael; Rapp, Stephen R.

2013-01-01

Background Computer-administered assessment of cognitive function is being increasingly incorporated in clinical trials, however its performance in these settings has not been systematically evaluated. Design The Seniors Health and Activity Research Program (SHARP) pilot trial (N=73) developed a computer-based tool for assessing memory performance and executive functioning. The Lifestyle Interventions and Independence for Seniors (LIFE) investigators incorporated this battery in a full scale multicenter clinical trial (N=1635). We describe relationships that test scores have with those from interviewer-administered cognitive function tests and risk factors for cognitive deficits and describe performance measures (completeness, intra-class correlations). Results Computer-based assessments of cognitive function had consistent relationships across the pilot and full scale trial cohorts with interviewer-administered assessments of cognitive function, age, and a measure of physical function. In the LIFE cohort, their external validity was further demonstrated by associations with other risk factors for cognitive dysfunction: education, hypertension, diabetes, and physical function. Acceptable levels of data completeness (>83%) were achieved on all computer-based measures, however rates of missing data were higher among older participants (odds ratio=1.06 for each additional year; p<0.001) and those who reported no current computer use (odds ratio=2.71; p<0.001). Intra-class correlations among clinics were at least as low (ICC≤0.013) as for interviewer measures (ICC≤0.023), reflecting good standardization. All cognitive measures loaded onto the first principal component (global cognitive function), which accounted for 40% of the overall variance. Conclusion Our results support the use of computer-based tools for assessing cognitive function in multicenter clinical trials of older individuals. PMID:23589390

High-Bandwidth Tactical-Network Data Analysis in a High-Performance-Computing (HPC) Environment: Transport Protocol (Transmission Control Protocol/User Datagram Protocol [TCP/UDP]) Analysis

Science.gov (United States)

2015-09-01

the network Mac8 Medium Access Control ( Mac ) (Ethernet) address observed as destination for outgoing packets subsessionid8 Zero-based index of...15. SUBJECT TERMS tactical networks, data reduction, high-performance computing, data analysis, big data 16. SECURITY CLASSIFICATION OF: 17...Integer index of row cts_deid Device (instrument) Identifier where observation took place cts_collpt Collection point or logical observation point on

ClustalXeed: a GUI-based grid computation version for high performance and terabyte size multiple sequence alignment

Directory of Open Access Journals (Sweden)

Kim Taeho

2010-09-01

Full Text Available Abstract Background There is an increasing demand to assemble and align large-scale biological sequence data sets. The commonly used multiple sequence alignment programs are still limited in their ability to handle very large amounts of sequences because the system lacks a scalable high-performance computing (HPC environment with a greatly extended data storage capacity. Results We designed ClustalXeed, a software system for multiple sequence alignment with incremental improvements over previous versions of the ClustalX and ClustalW-MPI software. The primary advantage of ClustalXeed over other multiple sequence alignment software is its ability to align a large family of protein or nucleic acid sequences. To solve the conventional memory-dependency problem, ClustalXeed uses both physical random access memory (RAM and a distributed file-allocation system for distance matrix construction and pair-align computation. The computation efficiency of disk-storage system was markedly improved by implementing an efficient load-balancing algorithm, called "idle node-seeking task algorithm" (INSTA. The new editing option and the graphical user interface (GUI provide ready access to a parallel-computing environment for users who seek fast and easy alignment of large DNA and protein sequence sets. Conclusions ClustalXeed can now compute a large volume of biological sequence data sets, which were not tractable in any other parallel or single MSA program. The main developments include: 1 the ability to tackle larger sequence alignment problems than possible with previous systems through markedly improved storage-handling capabilities. 2 Implementing an efficient task load-balancing algorithm, INSTA, which improves overall processing times for multiple sequence alignment with input sequences of non-uniform length. 3 Support for both single PC and distributed cluster systems.

High performance computing in power and energy systems

Energy Technology Data Exchange (ETDEWEB)

Khaitan, Siddhartha Kumar [Iowa State Univ., Ames, IA (United States); Gupta, Anshul (eds.) [IBM Watson Research Center, Yorktown Heights, NY (United States)

2013-07-01

The twin challenge of meeting global energy demands in the face of growing economies and populations and restricting greenhouse gas emissions is one of the most daunting ones that humanity has ever faced. Smart electrical generation and distribution infrastructure will play a crucial role in meeting these challenges. We would need to develop capabilities to handle large volumes of data generated by the power system components like PMUs, DFRs and other data acquisition devices as well as by the capacity to process these data at high resolution via multi-scale and multi-period simulations, cascading and security analysis, interaction between hybrid systems (electric, transport, gas, oil, coal, etc.) and so on, to get meaningful information in real time to ensure a secure, reliable and stable power system grid. Advanced research on development and implementation of market-ready leading-edge high-speed enabling technologies and algorithms for solving real-time, dynamic, resource-critical problems will be required for dynamic security analysis targeted towards successful implementation of Smart Grid initiatives. This books aims to bring together some of the latest research developments as well as thoughts on the future research directions of the high performance computing applications in electric power systems planning, operations, security, markets, and grid integration of alternate sources of energy, etc.

High performance computer code for molecular dynamics simulations

International Nuclear Information System (INIS)

Levay, I.; Toekesi, K.

2007-01-01

Complete text of publication follows. Molecular Dynamics (MD) simulation is a widely used technique for modeling complicated physical phenomena. Since 2005 we are developing a MD simulations code for PC computers. The computer code is written in C++ object oriented programming language. The aim of our work is twofold: a) to develop a fast computer code for the study of random walk of guest atoms in Be crystal, b) 3 dimensional (3D) visualization of the particles motion. In this case we mimic the motion of the guest atoms in the crystal (diffusion-type motion), and the motion of atoms in the crystallattice (crystal deformation). Nowadays, it is common to use Graphics Devices in intensive computational problems. There are several ways to use this extreme processing performance, but never before was so easy to programming these devices as now. The CUDA (Compute Unified Device) Architecture introduced by nVidia Corporation in 2007 is a very useful for every processor hungry application. A Unified-architecture GPU include 96-128, or more stream processors, so the raw calculation performance is 576(!) GFLOPS. It is ten times faster, than the fastest dual Core CPU [Fig.1]. Our improved MD simulation software uses this new technology, which speed up our software and the code run 10 times faster in the critical calculation code segment. Although the GPU is a very powerful tool, it has a strongly paralleled structure. It means, that we have to create an algorithm, which works on several processors without deadlock. Our code currently uses 256 threads, shared and constant on-chip memory, instead of global memory, which is 100 times slower than others. It is possible to implement the total algorithm on GPU, therefore we do not need to download and upload the data in every iteration. On behalf of maximal throughput, every thread run with the same instructions

Cognitive Correlates of Performance in Algorithms in a Computer Science Course for High School

Science.gov (United States)

Avancena, Aimee Theresa; Nishihara, Akinori

2014-01-01

Computer science for high school faces many challenging issues. One of these is whether the students possess the appropriate cognitive ability for learning the fundamentals of computer science. Online tests were created based on known cognitive factors and fundamental algorithms and were implemented among the second grade students in the…

InfoMall: An Innovative Strategy for High-Performance Computing and Communications Applications Development.

Science.gov (United States)

Mills, Kim; Fox, Geoffrey

1994-01-01

Describes the InfoMall, a program led by the Northeast Parallel Architectures Center (NPAC) at Syracuse University (New York). The InfoMall features a partnership of approximately 24 organizations offering linked programs in High Performance Computing and Communications (HPCC) technology integration, software development, marketing, education and…

Performance of a computer-based assessment of cognitive function measures in two cohorts of seniors

Science.gov (United States)

Computer-administered assessment of cognitive function is being increasingly incorporated in clinical trials, however its performance in these settings has not been systematically evaluated. The Seniors Health and Activity Research Program (SHARP) pilot trial (N=73) developed a computer-based tool f...

A C++11 implementation of arbitrary-rank tensors for high-performance computing

Science.gov (United States)

Aragón, Alejandro M.

2014-11-01

This article discusses an efficient implementation of tensors of arbitrary rank by using some of the idioms introduced by the recently published C++ ISO Standard (C++11). With the aims at providing a basic building block for high-performance computing, a single Array class template is carefully crafted, from which vectors, matrices, and even higher-order tensors can be created. An expression template facility is also built around the array class template to provide convenient mathematical syntax. As a result, by using templates, an extra high-level layer is added to the C++ language when dealing with algebraic objects and their operations, without compromising performance. The implementation is tested running on both CPU and GPU.

A high performance, low power computational platform for complex sensing operations in smart cities

KAUST Repository

Jiang, Jiming; Claudel, Christian

2017-01-01

This paper presents a new wireless platform designed for an integrated traffic/flash flood monitoring system. The sensor platform is built around a 32-bit ARM Cortex M4 microcontroller and a 2.4GHz 802.15.4802.15.4 ISM compliant radio module. It can be interfaced with fixed traffic sensors, or receive data from vehicle transponders. This platform is specifically designed for solar-powered, low bandwidth, high computational performance wireless sensor network applications. A self-recovering unit is designed to increase reliability and allow periodic hard resets, an essential requirement for sensor networks. A radio monitoring circuitry is proposed to monitor incoming and outgoing transmissions, simplifying software debugging. We illustrate the performance of this wireless sensor platform on complex problems arising in smart cities, such as traffic flow monitoring, machine-learning-based flash flood monitoring or Kalman-filter based vehicle trajectory estimation. All design files have been uploaded and shared in an open science framework, and can be accessed from [1]. The hardware design is under CERN Open Hardware License v1.2.

A high performance, low power computational platform for complex sensing operations in smart cities

KAUST Repository

Jiang, Jiming

2017-02-02

This paper presents a new wireless platform designed for an integrated traffic/flash flood monitoring system. The sensor platform is built around a 32-bit ARM Cortex M4 microcontroller and a 2.4GHz 802.15.4802.15.4 ISM compliant radio module. It can be interfaced with fixed traffic sensors, or receive data from vehicle transponders. This platform is specifically designed for solar-powered, low bandwidth, high computational performance wireless sensor network applications. A self-recovering unit is designed to increase reliability and allow periodic hard resets, an essential requirement for sensor networks. A radio monitoring circuitry is proposed to monitor incoming and outgoing transmissions, simplifying software debugging. We illustrate the performance of this wireless sensor platform on complex problems arising in smart cities, such as traffic flow monitoring, machine-learning-based flash flood monitoring or Kalman-filter based vehicle trajectory estimation. All design files have been uploaded and shared in an open science framework, and can be accessed from [1]. The hardware design is under CERN Open Hardware License v1.2.

US QCD computational performance studies with PERI

International Nuclear Information System (INIS)

Zhang, Y; Fowler, R; Huck, K; Malony, A; Porterfield, A; Reed, D; Shende, S; Taylor, V; Wu, X

2007-01-01

We report on some of the interactions between two SciDAC projects: The National Computational Infrastructure for Lattice Gauge Theory (USQCD), and the Performance Engineering Research Institute (PERI). Many modern scientific programs consistently report the need for faster computational resources to maintain global competitiveness. However, as the size and complexity of emerging high end computing (HEC) systems continue to rise, achieving good performance on such systems is becoming ever more challenging. In order to take full advantage of the resources, it is crucial to understand the characteristics of relevant scientific applications and the systems these applications are running on. Using tools developed under PERI and by other performance measurement researchers, we studied the performance of two applications, MILC and Chroma, on several high performance computing systems at DOE laboratories. In the case of Chroma, we discuss how the use of C++ and modern software engineering and programming methods are driving the evolution of performance tools

Computer based workstation for development of software for high energy physics experiments

International Nuclear Information System (INIS)

Ivanchenko, I.M.; Sedykh, Yu.V.

1987-01-01

Methodical principles and results of a successful attempt to create on the base of IBM-PC/AT personal computer of effective means for development of programs for high energy physics experiments are analysed. The obtained results permit to combine the best properties and a positive materialized experience accumulated on the existing time sharing collective systems with a high quality of data representation, reliability and convenience of personal computer applications

Using the Eclipse Parallel Tools Platform to Assist Earth Science Model Development and Optimization on High Performance Computers

Science.gov (United States)

Alameda, J. C.

2011-12-01

Development and optimization of computational science models, particularly on high performance computers, and with the advent of ubiquitous multicore processor systems, practically on every system, has been accomplished with basic software tools, typically, command-line based compilers, debuggers, performance tools that have not changed substantially from the days of serial and early vector computers. However, model complexity, including the complexity added by modern message passing libraries such as MPI, and the need for hybrid code models (such as openMP and MPI) to be able to take full advantage of high performance computers with an increasing core count per shared memory node, has made development and optimization of such codes an increasingly arduous task. Additional architectural developments, such as many-core processors, only complicate the situation further. In this paper, we describe how our NSF-funded project, "SI2-SSI: A Productive and Accessible Development Workbench for HPC Applications Using the Eclipse Parallel Tools Platform" (WHPC) seeks to improve the Eclipse Parallel Tools Platform, an environment designed to support scientific code development targeted at a diverse set of high performance computing systems. Our WHPC project to improve Eclipse PTP takes an application-centric view to improve PTP. We are using a set of scientific applications, each with a variety of challenges, and using PTP to drive further improvements to both the scientific application, as well as to understand shortcomings in Eclipse PTP from an application developer perspective, to drive our list of improvements we seek to make. We are also partnering with performance tool providers, to drive higher quality performance tool integration. We have partnered with the Cactus group at Louisiana State University to improve Eclipse's ability to work with computational frameworks and extremely complex build systems, as well as to develop educational materials to incorporate into

Towards Portable Large-Scale Image Processing with High-Performance Computing.

Science.gov (United States)

Huo, Yuankai; Blaber, Justin; Damon, Stephen M; Boyd, Brian D; Bao, Shunxing; Parvathaneni, Prasanna; Noguera, Camilo Bermudez; Chaganti, Shikha; Nath, Vishwesh; Greer, Jasmine M; Lyu, Ilwoo; French, William R; Newton, Allen T; Rogers, Baxter P; Landman, Bennett A

2018-05-03

High-throughput, large-scale medical image computing demands tight integration of high-performance computing (HPC) infrastructure for data storage, job distribution, and image processing. The Vanderbilt University Institute for Imaging Science (VUIIS) Center for Computational Imaging (CCI) has constructed a large-scale image storage and processing infrastructure that is composed of (1) a large-scale image database using the eXtensible Neuroimaging Archive Toolkit (XNAT), (2) a content-aware job scheduling platform using the Distributed Automation for XNAT pipeline automation tool (DAX), and (3) a wide variety of encapsulated image processing pipelines called "spiders." The VUIIS CCI medical image data storage and processing infrastructure have housed and processed nearly half-million medical image volumes with Vanderbilt Advanced Computing Center for Research and Education (ACCRE), which is the HPC facility at the Vanderbilt University. The initial deployment was natively deployed (i.e., direct installations on a bare-metal server) within the ACCRE hardware and software environments, which lead to issues of portability and sustainability. First, it could be laborious to deploy the entire VUIIS CCI medical image data storage and processing infrastructure to another HPC center with varying hardware infrastructure, library availability, and software permission policies. Second, the spiders were not developed in an isolated manner, which has led to software dependency issues during system upgrades or remote software installation. To address such issues, herein, we describe recent innovations using containerization techniques with XNAT/DAX which are used to isolate the VUIIS CCI medical image data storage and processing infrastructure from the underlying hardware and software environments. The newly presented XNAT/DAX solution has the following new features: (1) multi-level portability from system level to the application level, (2) flexible and dynamic software

Study on High Performance of MPI-Based Parallel FDTD from WorkStation to Super Computer Platform

Directory of Open Access Journals (Sweden)

Z. L. He

2012-01-01

Full Text Available Parallel FDTD method is applied to analyze the electromagnetic problems of the electrically large targets on super computer. It is well known that the more the number of processors the less computing time consumed. Nevertheless, with the same number of processors, computing efficiency is affected by the scheme of the MPI virtual topology. Then, the influence of different virtual topology schemes on parallel performance of parallel FDTD is studied in detail. The general rules are presented on how to obtain the highest efficiency of parallel FDTD algorithm by optimizing MPI virtual topology. To show the validity of the presented method, several numerical results are given in the later part. Various comparisons are made and some useful conclusions are summarized.

Towards the development of run times leveraging virtualization for high performance computing

International Nuclear Information System (INIS)

Diakhate, F.

2010-12-01

In recent years, there has been a growing interest in using virtualization to improve the efficiency of data centers. This success is rooted in virtualization's excellent fault tolerance and isolation properties, in the overall flexibility it brings, and in its ability to exploit multi-core architectures efficiently. These characteristics also make virtualization an ideal candidate to tackle issues found in new compute cluster architectures. However, in spite of recent improvements in virtualization technology, overheads in the execution of parallel applications remain, which prevent its use in the field of high performance computing. In this thesis, we propose a virtual device dedicated to message passing between virtual machines, so as to improve the performance of parallel applications executed in a cluster of virtual machines. We also introduce a set of techniques facilitating the deployment of virtualized parallel applications. These functionalities have been implemented as part of a runtime system which allows to benefit from virtualization's properties in a way that is as transparent as possible to the user while minimizing performance overheads. (author)

High performance data transfer

Science.gov (United States)

Cottrell, R.; Fang, C.; Hanushevsky, A.; Kreuger, W.; Yang, W.

2017-10-01

The exponentially increasing need for high speed data transfer is driven by big data, and cloud computing together with the needs of data intensive science, High Performance Computing (HPC), defense, the oil and gas industry etc. We report on the Zettar ZX software. This has been developed since 2013 to meet these growing needs by providing high performance data transfer and encryption in a scalable, balanced, easy to deploy and use way while minimizing power and space utilization. In collaboration with several commercial vendors, Proofs of Concept (PoC) consisting of clusters have been put together using off-the- shelf components to test the ZX scalability and ability to balance services using multiple cores, and links. The PoCs are based on SSD flash storage that is managed by a parallel file system. Each cluster occupies 4 rack units. Using the PoCs, between clusters we have achieved almost 200Gbps memory to memory over two 100Gbps links, and 70Gbps parallel file to parallel file with encryption over a 5000 mile 100Gbps link.

High-Performance Computer Modeling of the Cosmos-Iridium Collision

Energy Technology Data Exchange (ETDEWEB)

Olivier, S; Cook, K; Fasenfest, B; Jefferson, D; Jiang, M; Leek, J; Levatin, J; Nikolaev, S; Pertica, A; Phillion, D; Springer, K; De Vries, W

2009-08-28

This paper describes the application of a new, integrated modeling and simulation framework, encompassing the space situational awareness (SSA) enterprise, to the recent Cosmos-Iridium collision. This framework is based on a flexible, scalable architecture to enable efficient simulation of the current SSA enterprise, and to accommodate future advancements in SSA systems. In particular, the code is designed to take advantage of massively parallel, high-performance computer systems available, for example, at Lawrence Livermore National Laboratory. We will describe the application of this framework to the recent collision of the Cosmos and Iridium satellites, including (1) detailed hydrodynamic modeling of the satellite collision and resulting debris generation, (2) orbital propagation of the simulated debris and analysis of the increased risk to other satellites (3) calculation of the radar and optical signatures of the simulated debris and modeling of debris detection with space surveillance radar and optical systems (4) determination of simulated debris orbits from modeled space surveillance observations and analysis of the resulting orbital accuracy, (5) comparison of these modeling and simulation results with Space Surveillance Network observations. We will also discuss the use of this integrated modeling and simulation framework to analyze the risks and consequences of future satellite collisions and to assess strategies for mitigating or avoiding future incidents, including the addition of new sensor systems, used in conjunction with the Space Surveillance Network, for improving space situational awareness.

International Conference on Modern Mathematical Methods and High Performance Computing in Science and Technology

CERN Document Server

Srivastava, HM; Venturino, Ezio; Resch, Michael; Gupta, Vijay

2016-01-01

The book discusses important results in modern mathematical models and high performance computing, such as applied operations research, simulation of operations, statistical modeling and applications, invisibility regions and regular meta-materials, unmanned vehicles, modern radar techniques/SAR imaging, satellite remote sensing, coding, and robotic systems. Furthermore, it is valuable as a reference work and as a basis for further study and research. All contributing authors are respected academicians, scientists and researchers from around the globe. All the papers were presented at the international conference on Modern Mathematical Methods and High Performance Computing in Science & Technology (M3HPCST 2015), held at Raj Kumar Goel Institute of Technology, Ghaziabad, India, from 27–29 December 2015, and peer-reviewed by international experts. The conference provided an exceptional platform for leading researchers, academicians, developers, engineers and technocrats from a broad range of disciplines ...

Implementing Molecular Dynamics for Hybrid High Performance Computers - 1. Short Range Forces

International Nuclear Information System (INIS)

Brown, W. Michael; Wang, Peng; Plimpton, Steven J.; Tharrington, Arnold N.

2011-01-01

The use of accelerators such as general-purpose graphics processing units (GPGPUs) have become popular in scientific computing applications due to their low cost, impressive floating-point capabilities, high memory bandwidth, and low electrical power requirements. Hybrid high performance computers, machines with more than one type of floating-point processor, are now becoming more prevalent due to these advantages. In this work, we discuss several important issues in porting a large molecular dynamics code for use on parallel hybrid machines - (1) choosing a hybrid parallel decomposition that works on central processing units (CPUs) with distributed memory and accelerator cores with shared memory, (2) minimizing the amount of code that must be ported for efficient acceleration, (3) utilizing the available processing power from both many-core CPUs and accelerators, and (4) choosing a programming model for acceleration. We present our solution to each of these issues for short-range force calculation in the molecular dynamics package LAMMPS. We describe algorithms for efficient short range force calculation on hybrid high performance machines. We describe a new approach for dynamic load balancing of work between CPU and accelerator cores. We describe the Geryon library that allows a single code to compile with both CUDA and OpenCL for use on a variety of accelerators. Finally, we present results on a parallel test cluster containing 32 Fermi GPGPUs and 180 CPU cores.

Technologies and tools for high-performance distributed computing. Final report

Energy Technology Data Exchange (ETDEWEB)

Karonis, Nicholas T.

2000-05-01

In this project we studied the practical use of the MPI message-passing interface in advanced distributed computing environments. We built on the existing software infrastructure provided by the Globus Toolkit{trademark}, the MPICH portable implementation of MPI, and the MPICH-G integration of MPICH with Globus. As a result of this project we have replaced MPICH-G with its successor MPICH-G2, which is also an integration of MPICH with Globus. MPICH-G2 delivers significant improvements in message passing performance when compared to its predecessor MPICH-G and was based on superior software design principles resulting in a software base that was much easier to make the functional extensions and improvements we did. Using Globus services we replaced the default implementation of MPI's collective operations in MPICH-G2 with more efficient multilevel topology-aware collective operations which, in turn, led to the development of a new timing methodology for broadcasts [8]. MPICH-G2 was extended to include client/server functionality from the MPI-2 standard [23] to facilitate remote visualization applications and, through the use of MPI idioms, MPICH-G2 provided application-level control of quality-of-service parameters as well as application-level discovery of underlying Grid-topology information. Finally, MPICH-G2 was successfully used in a number of applications including an award-winning record-setting computation in numerical relativity. In the sections that follow we describe in detail the accomplishments of this project, we present experimental results quantifying the performance improvements, and conclude with a discussion of our applications experiences. This project resulted in a significant increase in the utility of MPICH-G2.

Polymer waveguides for electro-optical integration in data centers and high-performance computers.

Science.gov (United States)

Dangel, Roger; Hofrichter, Jens; Horst, Folkert; Jubin, Daniel; La Porta, Antonio; Meier, Norbert; Soganci, Ibrahim Murat; Weiss, Jonas; Offrein, Bert Jan

2015-02-23

To satisfy the intra- and inter-system bandwidth requirements of future data centers and high-performance computers, low-cost low-power high-throughput optical interconnects will become a key enabling technology. To tightly integrate optics with the computing hardware, particularly in the context of CMOS-compatible silicon photonics, optical printed circuit boards using polymer waveguides are considered as a formidable platform. IBM Research has already demonstrated the essential silicon photonics and interconnection building blocks. A remaining challenge is electro-optical packaging, i.e., the connection of the silicon photonics chips with the system. In this paper, we present a new single-mode polymer waveguide technology and a scalable method for building the optical interface between silicon photonics chips and single-mode polymer waveguides.

Power/energy use cases for high performance computing

Energy Technology Data Exchange (ETDEWEB)

Laros, James H. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kelly, Suzanne M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hammond, Steven [National Renewable Energy Lab. (NREL), Golden, CO (United States); Elmore, Ryan [National Renewable Energy Lab. (NREL), Golden, CO (United States); Munch, Kristin [National Renewable Energy Lab. (NREL), Golden, CO (United States)

2013-12-01

Power and Energy have been identified as a first order challenge for future extreme scale high performance computing (HPC) systems. In practice the breakthroughs will need to be provided by the hardware vendors. But to make the best use of the solutions in an HPC environment, it will likely require periodic tuning by facility operators and software components. This document describes the actions and interactions needed to maximize power resources. It strives to cover the entire operational space in which an HPC system occupies. The descriptions are presented as formal use cases, as documented in the Unified Modeling Language Specification [1]. The document is intended to provide a common understanding to the HPC community of the necessary management and control capabilities. Assuming a common understanding can be achieved, the next step will be to develop a set of Application Programing Interfaces (APIs) to which hardware vendors and software developers could utilize to steer power consumption.

High-efficiency photorealistic computer-generated holograms based on the backward ray-tracing technique

Science.gov (United States)

Wang, Yuan; Chen, Zhidong; Sang, Xinzhu; Li, Hui; Zhao, Linmin

2018-03-01

Holographic displays can provide the complete optical wave field of a three-dimensional (3D) scene, including the depth perception. However, it often takes a long computation time to produce traditional computer-generated holograms (CGHs) without more complex and photorealistic rendering. The backward ray-tracing technique is able to render photorealistic high-quality images, which noticeably reduce the computation time achieved from the high-degree parallelism. Here, a high-efficiency photorealistic computer-generated hologram method is presented based on the ray-tracing technique. Rays are parallelly launched and traced under different illuminations and circumstances. Experimental results demonstrate the effectiveness of the proposed method. Compared with the traditional point cloud CGH, the computation time is decreased to 24 s to reconstruct a 3D object of 100 ×100 rays with continuous depth change.

PENGEMBANGAN MODEL COMPUTER-BASED E-LEARNING UNTUK MENINGKATKAN KEMAMPUAN HIGH ORDER MATHEMATICAL THINKING SISWA SMA

OpenAIRE

Jarnawi Afgani Dahlan; Yaya Sukjaya Kusumah; Mr Heri Sutarno

2011-01-01

The focus of this research is on the development of mathematics teaching and learning activity which is based on the application of computer software. The aim of research is as follows : 1) to identify some mathematics topics which feasible to be presented by computer-based e-learning, 2) design, develop, and implement computer-based e-learning on mathematics, and 3) analyze the impact of computer-based e-learning in the enhancement of SMA students’ high order mathematical thinking. All activ...

High Performance Computing and Storage Requirements for Nuclear Physics: Target 2017

Energy Technology Data Exchange (ETDEWEB)

Gerber, Richard [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Wasserman, Harvey [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2014-04-30

In April 2014, NERSC, ASCR, and the DOE Office of Nuclear Physics (NP) held a review to characterize high performance computing (HPC) and storage requirements for NP research through 2017. This review is the 12th in a series of reviews held by NERSC and Office of Science program offices that began in 2009. It is the second for NP, and the final in the second round of reviews that covered the six Office of Science program offices. This report is the result of that review

Analysis and modeling of social influence in high performance computing workloads

KAUST Repository

Zheng, Shuai

2011-01-01

Social influence among users (e.g., collaboration on a project) creates bursty behavior in the underlying high performance computing (HPC) workloads. Using representative HPC and cluster workload logs, this paper identifies, analyzes, and quantifies the level of social influence across HPC users. We show the existence of a social graph that is characterized by a pattern of dominant users and followers. This pattern also follows a power-law distribution, which is consistent with those observed in mainstream social networks. Given its potential impact on HPC workloads prediction and scheduling, we propose a fast-converging, computationally-efficient online learning algorithm for identifying social groups. Extensive evaluation shows that our online algorithm can (1) quickly identify the social relationships by using a small portion of incoming jobs and (2) can efficiently track group evolution over time. © 2011 Springer-Verlag.

Peer-to-peer computing for secure high performance data copying

International Nuclear Information System (INIS)

Hanushevsky, A.; Trunov, A.; Cottrell, L.

2001-01-01

The BaBar Copy Program (bbcp) is an excellent representative of peer-to-peer (P2P) computing. It is also a pioneering application of its type in the P2P arena. Built upon the foundation of its predecessor, Secure Fast Copy (sfcp), bbcp incorporates significant improvements performance and usability. As with sfcp, bbcp uses ssh for authentication; providing an elegant and simple working model--if you can ssh to a location, you can copy files to or from that location. To fully support this notion, bbcp transparently supports 3rd party copy operations. The program also incorporates several mechanism to deal with firewall security; the bane of P2P computing. To achieve high performance in a wide area network, bbcp allows a user to independently specify, the number of parallel network streams, tcp window size, and the file I/O blocking factor. Using these parameters, data is pipelined from source to target to provide a uniform traffic pattern that maximizes router efficiency. For improved recoverability, bbcp also keeps track of copy operations so that an operation can be restarted from the point of failure at a later time; minimizing the amount of network traffic in the event of a copy failure. Here, the authors present the bbcp architecture, it's various features, and the reasons for their inclusion

Peer-to-Peer Computing for Secure High Performance Data Copying

International Nuclear Information System (INIS)

2002-01-01

The BaBar Copy Program (bbcp) is an excellent representative of peer-to-peer (P2P) computing. It is also a pioneering application of its type in the P2P arena. Built upon the foundation of its predecessor, Secure Fast Copy (sfcp), bbcp incorporates significant improvements performance and usability. As with sfcp, bbcp uses ssh for authentication; providing an elegant and simple working model -- if you can ssh to a location, you can copy files to or from that location. To fully support this notion, bbcp transparently supports 3rd party copy operations. The program also incorporates several mechanism to deal with firewall security; the bane of P2P computing. To achieve high performance in a wide area network, bbcp allows a user to independently specify, the number of parallel network streams, tcp window size, and the file I/O blocking factor. Using these parameters, data is pipelined from source to target to provide a uniform traffic pattern that maximizes router efficiency. For improved recoverability, bbcp also keeps track of copy operations so that an operation can be restarted from the point of failure at a later time; minimizing the amount of network traffic in the event of a copy failure. Here, we preset the bbcp architecture, it's various features, and the reasons for their inclusion

Using High Performance Computing to Examine the Processes of Neurogenesis Underlying Pattern Separation/Completion of Episodic Information.

Energy Technology Data Exchange (ETDEWEB)

Aimone, James Bradley [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Betty, Rita [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-03-01

Using High Performance Computing to Examine the Processes of Neurogenesis Underlying Pattern Separation/Completion of Episodic Information - Sandia researchers developed novel methods and metrics for studying the computational function of neurogenesis, thus generating substantial impact to the neuroscience and neural computing communities. This work could benefit applications in machine learning and other analysis activities.

Analysis of Application Power and Schedule Composition in a High Performance Computing Environment

Energy Technology Data Exchange (ETDEWEB)

Elmore, Ryan [National Renewable Energy Lab. (NREL), Golden, CO (United States); Gruchalla, Kenny [National Renewable Energy Lab. (NREL), Golden, CO (United States); Phillips, Caleb [National Renewable Energy Lab. (NREL), Golden, CO (United States); Purkayastha, Avi [National Renewable Energy Lab. (NREL), Golden, CO (United States); Wunder, Nick [National Renewable Energy Lab. (NREL), Golden, CO (United States)

2016-01-05

As the capacity of high performance computing (HPC) systems continues to grow, small changes in energy management have the potential to produce significant energy savings. In this paper, we employ an extensive informatics system for aggregating and analyzing real-time performance and power use data to evaluate energy footprints of jobs running in an HPC data center. We look at the effects of algorithmic choices for a given job on the resulting energy footprints, and analyze application-specific power consumption, and summarize average power use in the aggregate. All of these views reveal meaningful power variance between classes of applications as well as chosen methods for a given job. Using these data, we discuss energy-aware cost-saving strategies based on reordering the HPC job schedule. Using historical job and power data, we present a hypothetical job schedule reordering that: (1) reduces the facility's peak power draw and (2) manages power in conjunction with a large-scale photovoltaic array. Lastly, we leverage this data to understand the practical limits on predicting key power use metrics at the time of submission.

PREPS2 - a PC-based computer program for performing economic analysis of capital projects

International Nuclear Information System (INIS)

Blake, M.W.; Brand, D.O.; Chastain, E.T.; Johnson, E.D.

1990-01-01

In these times of increased spending to finance new capacity and to meet clean air act legislation, many electric utilities are giving a high priority to controlling capital expenditures at existing generating facilities. Determining the level of capital expenditures which are economically justified is very difficult; units which have higher capacity factors are worth more to the utility. Therefore, the utility can more readily justify higher capital expenditures to improve or maintain reliability and heat rate than on units with lower capacity factors. This paper describes a PC-based computer program (PREPS2) which performs an economic analysis of individual capital projects. The program incorporates tables which describe the worth to the system of making improvements in each unit. This computer program is currently being used by the six Southern Company operating companies to evaluate all production capital projects over $50,000. Approximately 500 projects representing about $300 million are being analyzed each year

Computational fluid dynamics (CFD) assisted performance evaluation of the Twincer™ disposable high-dose dry powder inhaler.

Science.gov (United States)

de Boer, Anne H; Hagedoorn, Paul; Woolhouse, Robert; Wynn, Ed

2012-09-01

To use computational fluid dynamics (CFD) for evaluating and understanding the performance of the high-dose disposable Twincer™ dry powder inhaler, as well as to learn the effect of design modifications on dose entrainment, powder dispersion and retention behaviour. Comparison of predicted flow and particle behaviour from CFD computations with experimental data obtained with cascade impactor and laser diffraction analysis. Inhaler resistance, flow split, particle trajectories and particle residence times can well be predicted with CFD for a multiple classifier based inhaler like the Twincer™. CFD computations showed that the flow split of the Twincer™ is independent of the pressure drop across the inhaler and that the total flow rate can be decreased without affecting the dispersion efficacy or retention behaviour. They also showed that classifier symmetry can be improved by reducing the resistance of one of the classifier bypass channels, which for the current concept does not contribute to the swirl in the classifier chamber. CFD is a highly valuable tool for development and optimisation of dry powder inhalers. CFD can assist adapting the inhaler design to specific physico-chemical properties of the drug formulation with respect to dispersion and retention behaviour. © 2012 The Authors. JPP © 2012 Royal Pharmaceutical Society.

Scalability of DL_POLY on High Performance Computing Platform

CSIR Research Space (South Africa)

Mabakane, Mabule S

2017-12-01

Full Text Available stream_source_info Mabakanea_19979_2017.pdf.txt stream_content_type text/plain stream_size 33716 Content-Encoding UTF-8 stream_name Mabakanea_19979_2017.pdf.txt Content-Type text/plain; charset=UTF-8 SACJ 29(3) December... when using many processors within the compute nodes of the supercomputer. The type of the processors of compute nodes and their memory also play an important role in the overall performance of the parallel application running on a supercomputer. DL...

An energy efficient and high speed architecture for convolution computing based on binary resistive random access memory

Science.gov (United States)

Liu, Chen; Han, Runze; Zhou, Zheng; Huang, Peng; Liu, Lifeng; Liu, Xiaoyan; Kang, Jinfeng

2018-04-01

In this work we present a novel convolution computing architecture based on metal oxide resistive random access memory (RRAM) to process the image data stored in the RRAM arrays. The proposed image storage architecture shows performances of better speed-device consumption efficiency compared with the previous kernel storage architecture. Further we improve the architecture for a high accuracy and low power computing by utilizing the binary storage and the series resistor. For a 28 × 28 image and 10 kernels with a size of 3 × 3, compared with the previous kernel storage approach, the newly proposed architecture shows excellent performances including: 1) almost 100% accuracy within 20% LRS variation and 90% HRS variation; 2) more than 67 times speed boost; 3) 71.4% energy saving.

Benchmark Tests on the New IBM RISC System/6000 590 Workstation

Directory of Open Access Journals (Sweden)

Harvey J. Wasserman

1995-01-01

Full Text Available The results of benchmark tests on the superscalar IBM RISC System/6000 Model 590 are presented. A set of well-characterized Fortran benchmarks spanning a range of computational characteristics was used for the study. The data from the 590 system are compared with those from a single-processor CRAY C90 system as well as with other microprocessor-based systems, such as the Digital Equipment Corporation AXP 3000/500X and the Hewlett-Packard HP/735.

FY 1996 Blue Book: High Performance Computing and Communications: Foundations for America`s Information Future

Data.gov (United States)

Networking and Information Technology Research and Development, Executive Office of the President — The Federal High Performance Computing and Communications HPCC Program will celebrate its fifth anniversary in October 1996 with an impressive array of...

FY 1997 Blue Book: High Performance Computing and Communications: Advancing the Frontiers of Information Technology

Data.gov (United States)

Networking and Information Technology Research and Development, Executive Office of the President — The Federal High Performance Computing and Communications HPCC Program will celebrate its fifth anniversary in October 1996 with an impressive array of...

Challenges and opportunities of modeling plasma–surface interactions in tungsten using high-performance computing

Energy Technology Data Exchange (ETDEWEB)

Wirth, Brian D., E-mail: bdwirth@utk.edu [Department of Nuclear Engineering, University of Tennessee, Knoxville, TN 37996 (United States); Nuclear Science and Engineering Directorate, Oak Ridge National Laboratory, Oak Ridge, TN (United States); Hammond, K.D. [Department of Nuclear Engineering, University of Tennessee, Knoxville, TN 37996 (United States); Krasheninnikov, S.I. [University of California, San Diego, La Jolla, CA (United States); Maroudas, D. [University of Massachusetts, Amherst, Amherst, MA 01003 (United States)

2015-08-15

The performance of plasma facing components (PFCs) is critical for ITER and future magnetic fusion reactors. The ITER divertor will be tungsten, which is the primary candidate material for future reactors. Recent experiments involving tungsten exposure to low-energy helium plasmas reveal significant surface modification, including the growth of nanometer-scale tendrils of “fuzz” and formation of nanometer-sized bubbles in the near-surface region. The large span of spatial and temporal scales governing plasma surface interactions are among the challenges to modeling divertor performance. Fortunately, recent innovations in computational modeling, increasingly powerful high-performance computers, and improved experimental characterization tools provide a path toward self-consistent, experimentally validated models of PFC and divertor performance. Recent advances in understanding tungsten–helium interactions are reviewed, including such processes as helium clustering, which serve as nuclei for gas bubbles; and trap mutation, dislocation loop punching and bubble bursting; which together initiate surface morphological modification.

Challenges and opportunities of modeling plasma–surface interactions in tungsten using high-performance computing

International Nuclear Information System (INIS)

Wirth, Brian D.; Hammond, K.D.; Krasheninnikov, S.I.; Maroudas, D.

2015-01-01

The performance of plasma facing components (PFCs) is critical for ITER and future magnetic fusion reactors. The ITER divertor will be tungsten, which is the primary candidate material for future reactors. Recent experiments involving tungsten exposure to low-energy helium plasmas reveal significant surface modification, including the growth of nanometer-scale tendrils of “fuzz” and formation of nanometer-sized bubbles in the near-surface region. The large span of spatial and temporal scales governing plasma surface interactions are among the challenges to modeling divertor performance. Fortunately, recent innovations in computational modeling, increasingly powerful high-performance computers, and improved experimental characterization tools provide a path toward self-consistent, experimentally validated models of PFC and divertor performance. Recent advances in understanding tungsten–helium interactions are reviewed, including such processes as helium clustering, which serve as nuclei for gas bubbles; and trap mutation, dislocation loop punching and bubble bursting; which together initiate surface morphological modification

High performance computations using dynamical nucleation theory

International Nuclear Information System (INIS)

Windus, T L; Crosby, L D; Kathmann, S M

2008-01-01

Chemists continue to explore the use of very large computations to perform simulations that describe the molecular level physics of critical challenges in science. In this paper, we describe the Dynamical Nucleation Theory Monte Carlo (DNTMC) model - a model for determining molecular scale nucleation rate constants - and its parallel capabilities. The potential for bottlenecks and the challenges to running on future petascale or larger resources are delineated. A 'master-slave' solution is proposed to scale to the petascale and will be developed in the NWChem software. In addition, mathematical and data analysis challenges are described

A high level language for a high performance computer

Science.gov (United States)

Perrott, R. H.

1978-01-01

The proposed computational aerodynamic facility will join the ranks of the supercomputers due to its architecture and increased execution speed. At present, the languages used to program these supercomputers have been modifications of programming languages which were designed many years ago for sequential machines. A new programming language should be developed based on the techniques which have proved valuable for sequential programming languages and incorporating the algorithmic techniques required for these supercomputers. The design objectives for such a language are outlined.

Security personnel training using a computer-based game

International Nuclear Information System (INIS)

Ralph, J.; Bickner, L.

1987-01-01

Security personnel training is an integral part of a total physical security program, and is essential in enabling security personnel to perform their function effectively. Several training tools are currently available for use by security supervisors, including: textbook study, classroom instruction, and live simulations. However, due to shortcomings inherent in each of these tools, a need exists for the development of low-cost alternative training methods. This paper discusses one such alternative: a computer-based, game-type security training system. This system would be based on a personal computer with high-resolution graphics. Key features of this system include: a high degree of realism; flexibility in use and maintenance; high trainee motivation; and low cost

Exploring Subpixel Learning Algorithms for Estimating Global Land Cover Fractions from Satellite Data Using High Performance Computing

Directory of Open Access Journals (Sweden)

Uttam Kumar

2017-10-01

Full Text Available Land cover (LC refers to the physical and biological cover present over the Earth’s surface in terms of the natural environment such as vegetation, water, bare soil, etc. Most LC features occur at finer spatial scales compared to the resolution of primary remote sensing satellites. Therefore, observed data are a mixture of spectral signatures of two or more LC features resulting in mixed pixels. One solution to the mixed pixel problem is the use of subpixel learning algorithms to disintegrate the pixel spectrum into its constituent spectra. Despite the popularity and existing research conducted on the topic, the most appropriate approach is still under debate. As an attempt to address this question, we compared the performance of several subpixel learning algorithms based on least squares, sparse regression, signal–subspace and geometrical methods. Analysis of the results obtained through computer-simulated and Landsat data indicated that fully constrained least squares (FCLS outperformed the other techniques. Further, FCLS was used to unmix global Web-Enabled Landsat Data to obtain abundances of substrate (S, vegetation (V and dark object (D classes. Due to the sheer nature of data and computational needs, we leveraged the NASA Earth Exchange (NEX high-performance computing architecture to optimize and scale our algorithm for large-scale processing. Subsequently, the S-V-D abundance maps were characterized into four classes, namely forest, farmland, water and urban areas (in conjunction with nighttime lights data over California, USA using a random forest classifier. Validation of these LC maps with the National Land Cover Database 2011 products and North American Forest Dynamics static forest map shows a 6% improvement in unmixing-based classification relative to per-pixel classification. As such, abundance maps continue to offer a useful alternative to high-spatial-resolution classified maps for forest inventory analysis, multi

Data Mining Based on Cloud-Computing Technology

Directory of Open Access Journals (Sweden)

Ren Ying

2016-01-01

Full Text Available There are performance bottlenecks and scalability problems when traditional data-mining system is used in cloud computing. In this paper, we present a data-mining platform based on cloud computing. Compared with a traditional data mining system, this platform is highly scalable, has massive data processing capacities, is service-oriented, and has low hardware cost. This platform can support the design and applications of a wide range of distributed data-mining systems.

Application of High Performance Computing to Earthquake Hazard and Disaster Estimation in Urban Area

Directory of Open Access Journals (Sweden)

Muneo Hori

2018-02-01

Full Text Available Integrated earthquake simulation (IES is a seamless simulation of analyzing all processes of earthquake hazard and disaster. There are two difficulties in carrying out IES, namely, the requirement of large-scale computation and the requirement of numerous analysis models for structures in an urban area, and they are solved by taking advantage of high performance computing (HPC and by developing a system of automated model construction. HPC is a key element in developing IES, as it needs to analyze wave propagation and amplification processes in an underground structure; a model of high fidelity for the underground structure exceeds a degree-of-freedom larger than 100 billion. Examples of IES for Tokyo Metropolis are presented; the numerical computation is made by using K computer, the supercomputer of Japan. The estimation of earthquake hazard and disaster for a given earthquake scenario is made by the ground motion simulation and the urban area seismic response simulation, respectively, for the target area of 10,000 m × 10,000 m.

Development of a Computational Steering Framework for High Performance Computing Environments on Blue Gene/P Systems

KAUST Repository

Danani, Bob K.

2012-07-01

Computational steering has revolutionized the traditional workflow in high performance computing (HPC) applications. The standard workflow that consists of preparation of an application’s input, running of a simulation, and visualization of simulation results in a post-processing step is now transformed into a real-time interactive workflow that significantly reduces development and testing time. Computational steering provides the capability to direct or re-direct the progress of a simulation application at run-time. It allows modification of application-defined control parameters at run-time using various user-steering applications. In this project, we propose a computational steering framework for HPC environments that provides an innovative solution and easy-to-use platform, which allows users to connect and interact with running application(s) in real-time. This framework uses RealityGrid as the underlying steering library and adds several enhancements to the library to enable steering support for Blue Gene systems. Included in the scope of this project is the development of a scalable and efficient steering relay server that supports many-to-many connectivity between multiple steered applications and multiple steering clients. Steered applications can range from intermediate simulation and physical modeling applications to complex computational fluid dynamics (CFD) applications or advanced visualization applications. The Blue Gene supercomputer presents special challenges for remote access because the compute nodes reside on private networks. This thesis presents an implemented solution and demonstrates it on representative applications. Thorough implementation details and application enablement steps are also presented in this thesis to encourage direct usage of this framework.

High-Throughput Computing on High-Performance Platforms: A Case Study

Energy Technology Data Exchange (ETDEWEB)

Oleynik, D [University of Texas at Arlington; Panitkin, S [Brookhaven National Laboratory (BNL); Matteo, Turilli [Rutgers University; Angius, Alessio [Rutgers University; Oral, H Sarp [ORNL; De, K [University of Texas at Arlington; Klimentov, A [Brookhaven National Laboratory (BNL); Wells, Jack C. [ORNL; Jha, S [Rutgers University

2017-10-01

The computing systems used by LHC experiments has historically consisted of the federation of hundreds to thousands of distributed resources, ranging from small to mid-size resource. In spite of the impressive scale of the existing distributed computing solutions, the federation of small to mid-size resources will be insufficient to meet projected future demands. This paper is a case study of how the ATLAS experiment has embraced Titan -- a DOE leadership facility in conjunction with traditional distributed high- throughput computing to reach sustained production scales of approximately 52M core-hours a years. The three main contributions of this paper are: (i) a critical evaluation of design and operational considerations to support the sustained, scalable and production usage of Titan; (ii) a preliminary characterization of a next generation executor for PanDA to support new workloads and advanced execution modes; and (iii) early lessons for how current and future experimental and observational systems can be integrated with production supercomputers and other platforms in a general and extensible manner.

Cloud object store for archive storage of high performance computing data using decoupling middleware

Science.gov (United States)

Bent, John M.; Faibish, Sorin; Grider, Gary

2015-06-30

Cloud object storage is enabled for archived data, such as checkpoints and results, of high performance computing applications using a middleware process. A plurality of archived files, such as checkpoint files and results, generated by a plurality of processes in a parallel computing system are stored by obtaining the plurality of archived files from the parallel computing system; converting the plurality of archived files to objects using a log structured file system middleware process; and providing the objects for storage in a cloud object storage system. The plurality of processes may run, for example, on a plurality of compute nodes. The log structured file system middleware process may be embodied, for example, as a Parallel Log-Structured File System (PLFS). The log structured file system middleware process optionally executes on a burst buffer node.

Matrix multiplication operations with data pre-conditioning in a high performance computing architecture

Science.gov (United States)

Eichenberger, Alexandre E; Gschwind, Michael K; Gunnels, John A

2013-11-05

Mechanisms for performing matrix multiplication operations with data pre-conditioning in a high performance computing architecture are provided. A vector load operation is performed to load a first vector operand of the matrix multiplication operation to a first target vector register. A load and splat operation is performed to load an element of a second vector operand and replicating the element to each of a plurality of elements of a second target vector register. A multiply add operation is performed on elements of the first target vector register and elements of the second target vector register to generate a partial product of the matrix multiplication operation. The partial product of the matrix multiplication operation is accumulated with other partial products of the matrix multiplication operation.

Sepsis reconsidered: Identifying novel metrics for behavioral landscape characterization with a high-performance computing implementation of an agent-based model.

Science.gov (United States)

Cockrell, Chase; An, Gary

2017-10-07

Sepsis affects nearly 1 million people in the United States per year, has a mortality rate of 28-50% and requires more than $20 billion a year in hospital costs. Over a quarter century of research has not yielded a single reliable diagnostic test or a directed therapeutic agent for sepsis. Central to this insufficiency is the fact that sepsis remains a clinical/physiological diagnosis representing a multitude of molecularly heterogeneous pathological trajectories. Advances in computational capabilities offered by High Performance Computing (HPC) platforms call for an evolution in the investigation of sepsis to attempt to define the boundaries of traditional research (bench, clinical and computational) through the use of computational proxy models. We present a novel investigatory and analytical approach, derived from how HPC resources and simulation are used in the physical sciences, to identify the epistemic boundary conditions of the study of clinical sepsis via the use of a proxy agent-based model of systemic inflammation. Current predictive models for sepsis use correlative methods that are limited by patient heterogeneity and data sparseness. We address this issue by using an HPC version of a system-level validated agent-based model of sepsis, the Innate Immune Response ABM (IIRBM), as a proxy system in order to identify boundary conditions for the possible behavioral space for sepsis. We then apply advanced analysis derived from the study of Random Dynamical Systems (RDS) to identify novel means for characterizing system behavior and providing insight into the tractability of traditional investigatory methods. The behavior space of the IIRABM was examined by simulating over 70 million sepsis patients for up to 90 days in a sweep across the following parameters: cardio-respiratory-metabolic resilience; microbial invasiveness; microbial toxigenesis; and degree of nosocomial exposure. In addition to using established methods for describing parameter space, we

High performance computing, supercomputing, náročné počítání

Czech Academy of Sciences Publication Activity Database

Okrouhlík, Miloslav

2003-01-01

Roč. 10, č. 5 (2003), s. 429-438 ISSN 1210-2717 R&D Projects: GA ČR GA101/02/0072 Institutional research plan: CEZ:AV0Z2076919 Keywords : high performance computing * vector and parallel computers * programing tools for parellelization Subject RIV: BI - Acoustics

Performing stencil computations

Energy Technology Data Exchange (ETDEWEB)

Donofrio, David

2018-01-16

A method and apparatus for performing stencil computations efficiently are disclosed. In one embodiment, a processor receives an offset, and in response, retrieves a value from a memory via a single instruction, where the retrieving comprises: identifying, based on the offset, one of a plurality of registers of the processor; loading an address stored in the identified register; and retrieving from the memory the value at the address.

Porting the 3D Gyrokinetic Particle-in-cell Code GTC to the CRAY/NEC SX-6 Vector Architecture: Perspectives and Challenges

International Nuclear Information System (INIS)

Ethier, S.; Lin, Z.

2003-01-01

Several years of optimization on the super-scalar architecture has made it more difficult to port the current version of the 3D particle-in-cell code GTC to the CRAY/NEC SX-6 vector architecture. This paper explains the initial work that has been done to port this code to the SX-6 computer and to optimize the most time consuming parts. Early performance results are shown and compared to the same test done on the IBM SP Power 3 and Power 4 machines

Requirements for high performance computing for lattice QCD. Report of the ECFA working panel

International Nuclear Information System (INIS)

Jegerlehner, F.; Kenway, R.D.; Martinelli, G.; Michael, C.; Pene, O.; Petersson, B.; Petronzio, R.; Sachrajda, C.T.; Schilling, K.

2000-01-01

This report, prepared at the request of the European Committee for Future Accelerators (ECFA), contains an assessment of the High Performance Computing resources which will be required in coming years by European physicists working in Lattice Field Theory and a review of the scientific opportunities which these resources would open. (orig.)

Department of Energy: MICS (Mathematical Information, and Computational Sciences Division). High performance computing and communications program

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-06-01

This document is intended to serve two purposes. Its first purpose is that of a program status report of the considerable progress that the Department of Energy (DOE) has made since 1993, the time of the last such report (DOE/ER-0536, {open_quotes}The DOE Program in HPCC{close_quotes}), toward achieving the goals of the High Performance Computing and Communications (HPCC) Program. The second purpose is that of a summary report of the many research programs administered by the Mathematical, Information, and Computational Sciences (MICS) Division of the Office of Energy Research under the auspices of the HPCC Program and to provide, wherever relevant, easy access to pertinent information about MICS-Division activities via universal resource locators (URLs) on the World Wide Web (WWW). The information pointed to by the URL is updated frequently, and the interested reader is urged to access the WWW for the latest information.

Analysis and Modeling of Social In uence in High Performance Computing Workloads

KAUST Repository

Zheng, Shuai

2011-06-01

High Performance Computing (HPC) is becoming a common tool in many research areas. Social influence (e.g., project collaboration) among increasing users of HPC systems creates bursty behavior in underlying workloads. This bursty behavior is increasingly common with the advent of grid computing and cloud computing. Mining the user bursty behavior is important for HPC workloads prediction and scheduling, which has direct impact on overall HPC computing performance. A representative work in this area is the Mixed User Group Model (MUGM), which clusters users according to the resource demand features of their submissions, such as duration time and parallelism. However, MUGM has some difficulties when implemented in real-world system. First, representing user behaviors by the features of their resource demand is usually difficult. Second, these features are not always available. Third, measuring the similarities among users is not a well-defined problem. In this work, we propose a Social Influence Model (SIM) to identify, analyze, and quantify the level of social influence across HPC users. The advantage of the SIM model is that it finds HPC communities by analyzing user job submission time, thereby avoiding the difficulties of MUGM. An offline algorithm and a fast-converging, computationally-efficient online learning algorithm for identifying social groups are proposed. Both offline and online algorithms are applied on several HPC and grid workloads, including Grid 5000, EGEE 2005 and 2007, and KAUST Supercomputing Lab (KSL) BGP data. From the experimental results, we show the existence of a social graph, which is characterized by a pattern of dominant users and followers. In order to evaluate the effectiveness of identified user groups, we show the pattern discovered by the offline algorithm follows a power-law distribution, which is consistent with those observed in mainstream social networks. We finally conclude the thesis and discuss future directions of our work.

High performance stream computing for particle beam transport simulations

International Nuclear Information System (INIS)

Appleby, R; Bailey, D; Higham, J; Salt, M

2008-01-01

Understanding modern particle accelerators requires simulating charged particle transport through the machine elements. These simulations can be very time consuming due to the large number of particles and the need to consider many turns of a circular machine. Stream computing offers an attractive way to dramatically improve the performance of such simulations by calculating the simultaneous transport of many particles using dedicated hardware. Modern Graphics Processing Units (GPUs) are powerful and affordable stream computing devices. The results of simulations of particle transport through the booster-to-storage-ring transfer line of the DIAMOND synchrotron light source using an NVidia GeForce 7900 GPU are compared to the standard transport code MAD. It is found that particle transport calculations are suitable for stream processing and large performance increases are possible. The accuracy and potential speed gains are compared and the prospects for future work in the area are discussed

A Cloud-Computing-Based Data Placement Strategy in High-Speed Railway

Directory of Open Access Journals (Sweden)

Hanning Wang

2012-01-01

Full Text Available As an important component of China’s transportation data sharing system, high-speed railway data sharing is a typical application of data-intensive computing. Currently, most high-speed railway data is shared in cloud computing environment. Thus, there is an urgent need for an effective cloud-computing-based data placement strategy in high-speed railway. In this paper, a new data placement strategy named hierarchical structure data placement strategy is proposed. The proposed method combines the semidefinite programming algorithm with the dynamic interval mapping algorithm. The semi-definite programming algorithm is suitable for the placement of files with various replications, ensuring that different replications of a file are placed on different storage devices, while the dynamic interval mapping algorithm ensures better self-adaptability of the data storage system. A hierarchical data placement strategy is proposed for large-scale networks. In this paper, a new theoretical analysis is provided, which is put in comparison with several other previous data placement approaches, showing the efficacy of the new analysis in several experiments.

Impedance computations and beam-based measurements: A problem of discrepancy

Science.gov (United States)

Smaluk, Victor

2018-04-01

High intensity of particle beams is crucial for high-performance operation of modern electron-positron storage rings, both colliders and light sources. The beam intensity is limited by the interaction of the beam with self-induced electromagnetic fields (wake fields) proportional to the vacuum chamber impedance. For a new accelerator project, the total broadband impedance is computed by element-wise wake-field simulations using computer codes. For a machine in operation, the impedance can be measured experimentally using beam-based techniques. In this article, a comparative analysis of impedance computations and beam-based measurements is presented for 15 electron-positron storage rings. The measured data and the predictions based on the computed impedance budgets show a significant discrepancy. Three possible reasons for the discrepancy are discussed: interference of the wake fields excited by a beam in adjacent components of the vacuum chamber, effect of computation mesh size, and effect of insufficient bandwidth of the computed impedance.

Performance Management of High Performance Computing for Medical Image Processing in Amazon Web Services.

Science.gov (United States)

Bao, Shunxing; Damon, Stephen M; Landman, Bennett A; Gokhale, Aniruddha

2016-02-27

Adopting high performance cloud computing for medical image processing is a popular trend given the pressing needs of large studies. Amazon Web Services (AWS) provide reliable, on-demand, and inexpensive cloud computing services. Our research objective is to implement an affordable, scalable and easy-to-use AWS framework for the Java Image Science Toolkit (JIST). JIST is a plugin for Medical-Image Processing, Analysis, and Visualization (MIPAV) that provides a graphical pipeline implementation allowing users to quickly test and develop pipelines. JIST is DRMAA-compliant allowing it to run on portable batch system grids. However, as new processing methods are implemented and developed, memory may often be a bottleneck for not only lab computers, but also possibly some local grids. Integrating JIST with the AWS cloud alleviates these possible restrictions and does not require users to have deep knowledge of programming in Java. Workflow definition/management and cloud configurations are two key challenges in this research. Using a simple unified control panel, users have the ability to set the numbers of nodes and select from a variety of pre-configured AWS EC2 nodes with different numbers of processors and memory storage. Intuitively, we configured Amazon S3 storage to be mounted by pay-for-use Amazon EC2 instances. Hence, S3 storage is recognized as a shared cloud resource. The Amazon EC2 instances provide pre-installs of all necessary packages to run JIST. This work presents an implementation that facilitates the integration of JIST with AWS. We describe the theoretical cost/benefit formulae to decide between local serial execution versus cloud computing and apply this analysis to an empirical diffusion tensor imaging pipeline.

Performance management of high performance computing for medical image processing in Amazon Web Services

Science.gov (United States)

Bao, Shunxing; Damon, Stephen M.; Landman, Bennett A.; Gokhale, Aniruddha

2016-03-01

Adopting high performance cloud computing for medical image processing is a popular trend given the pressing needs of large studies. Amazon Web Services (AWS) provide reliable, on-demand, and inexpensive cloud computing services. Our research objective is to implement an affordable, scalable and easy-to-use AWS framework for the Java Image Science Toolkit (JIST). JIST is a plugin for Medical- Image Processing, Analysis, and Visualization (MIPAV) that provides a graphical pipeline implementation allowing users to quickly test and develop pipelines. JIST is DRMAA-compliant allowing it to run on portable batch system grids. However, as new processing methods are implemented and developed, memory may often be a bottleneck for not only lab computers, but also possibly some local grids. Integrating JIST with the AWS cloud alleviates these possible restrictions and does not require users to have deep knowledge of programming in Java. Workflow definition/management and cloud configurations are two key challenges in this research. Using a simple unified control panel, users have the ability to set the numbers of nodes and select from a variety of pre-configured AWS EC2 nodes with different numbers of processors and memory storage. Intuitively, we configured Amazon S3 storage to be mounted by pay-for- use Amazon EC2 instances. Hence, S3 storage is recognized as a shared cloud resource. The Amazon EC2 instances provide pre-installs of all necessary packages to run JIST. This work presents an implementation that facilitates the integration of JIST with AWS. We describe the theoretical cost/benefit formulae to decide between local serial execution versus cloud computing and apply this analysis to an empirical diffusion tensor imaging pipeline.

THE IMPROVEMENT OF COMPUTER NETWORK PERFORMANCE WITH BANDWIDTH MANAGEMENT IN KEMURNIAN II SENIOR HIGH SCHOOL

Directory of Open Access Journals (Sweden)

Bayu Kanigoro

2012-05-01

Full Text Available This research describes the improvement of computer network performance with bandwidth management in Kemurnian II Senior High School. The main issue of this research is the absence of bandwidth division on computer, which makes user who is downloading data, the provided bandwidth will be absorbed by the user. It leads other users do not get the bandwidth. Besides that, it has been done IP address division on each room, such as computer, teacher and administration room for supporting learning process in Kemurnian II Senior High School, so wireless network is needed. The method is location observation and interview with related parties in Kemurnian II Senior High School, the network analysis has run and designed a new topology network including the wireless network along with its configuration and separation bandwidth on microtic router and its limitation. The result is network traffic on Kemurnian II Senior High School can be shared evenly to each user; IX and IIX traffic are separated, which improve the speed on network access at school and the implementation of wireless network.Keywords: Bandwidth Management; Wireless Network

Contributing to the design of run-time systems dedicated to high performance computing

International Nuclear Information System (INIS)

Perache, M.

2006-10-01

In the field of intensive scientific computing, the quest for performance has to face the increasing complexity of parallel architectures. Nowadays, these machines exhibit a deep memory hierarchy which complicates the design of efficient parallel applications. This thesis proposes a programming environment allowing to design efficient parallel programs on top of clusters of multi-processors. It features a programming model centered around collective communications and synchronizations, and provides load balancing facilities. The programming interface, named MPC, provides high level paradigms which are optimized according to the underlying architecture. The environment is fully functional and used within the CEA/DAM (TERANOVA) computing center. The evaluations presented in this document confirm the relevance of our approach. (author)

Frequency selective surfaces based high performance microstrip antenna

CERN Document Server

Narayan, Shiv; Jha, Rakesh Mohan

2016-01-01

This book focuses on performance enhancement of printed antennas using frequency selective surfaces (FSS) technology. The growing demand of stealth technology in strategic areas requires high-performance low-RCS (radar cross section) antennas. Such requirements may be accomplished by incorporating FSS into the antenna structure either in its ground plane or as the superstrate, due to the filter characteristics of FSS structure. In view of this, a novel approach based on FSS technology is presented in this book to enhance the performance of printed antennas including out-of-band structural RCS reduction. In this endeavor, the EM design of microstrip patch antennas (MPA) loaded with FSS-based (i) high impedance surface (HIS) ground plane, and (ii) the superstrates are discussed in detail. The EM analysis of proposed FSS-based antenna structures have been carried out using transmission line analogy, in combination with the reciprocity theorem. Further, various types of novel FSS structures are considered in desi...

Improving self-regulated learning junior high school students through computer-based learning

Science.gov (United States)

Nurjanah; Dahlan, J. A.

2018-05-01

This study is back grounded by the importance of self-regulated learning as an affective aspect that determines the success of students in learning mathematics. The purpose of this research is to see how the improvement of junior high school students' self-regulated learning through computer based learning is reviewed in whole and school level. This research used a quasi-experimental research method. This is because individual sample subjects are not randomly selected. The research design used is Pretest-and-Posttest Control Group Design. Subjects in this study were students of grade VIII junior high school in Bandung taken from high school (A) and middle school (B). The results of this study showed that the increase of the students' self-regulated learning who obtain learning with computer-based learning is higher than students who obtain conventional learning. School-level factors have a significant effect on increasing of the students' self-regulated learning.

Unified, Cross-Platform, Open-Source Library Package for High-Performance Computing

Energy Technology Data Exchange (ETDEWEB)

Kozacik, Stephen [EM Photonics, Inc., Newark, DE (United States)

2017-05-15

Compute power is continually increasing, but this increased performance is largely found in sophisticated computing devices and supercomputer resources that are difficult to use, resulting in under-utilization. We developed a unified set of programming tools that will allow users to take full advantage of the new technology by allowing them to work at a level abstracted away from the platform specifics, encouraging the use of modern computing systems, including government-funded supercomputer facilities.

A Case Study on Neural Inspired Dynamic Memory Management Strategies for High Performance Computing.

Energy Technology Data Exchange (ETDEWEB)

Vineyard, Craig Michael [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Verzi, Stephen Joseph [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-09-01

As high performance computing architectures pursue more computational power there is a need for increased memory capacity and bandwidth as well. A multi-level memory (MLM) architecture addresses this need by combining multiple memory types with different characteristics as varying levels of the same architecture. How to efficiently utilize this memory infrastructure is an unknown challenge, and in this research we sought to investigate whether neural inspired approaches can meaningfully help with memory management. In particular we explored neurogenesis inspired re- source allocation, and were able to show a neural inspired mixed controller policy can beneficially impact how MLM architectures utilize memory.

A high performance image processing platform based on CPU-GPU heterogeneous cluster with parallel image reconstroctions for micro-CT

International Nuclear Information System (INIS)

Ding Yu; Qi Yujin; Zhang Xuezhu; Zhao Cuilan

2011-01-01

In this paper, we report the development of a high-performance image processing platform, which is based on CPU-GPU heterogeneous cluster. Currently, it consists of a Dell Precision T7500 and HP XW8600 workstations with parallel programming and runtime environment, using the message-passing interface (MPI) and CUDA (Compute Unified Device Architecture). We succeeded in developing parallel image processing techniques for 3D image reconstruction of X-ray micro-CT imaging. The results show that a GPU provides a computing efficiency of about 194 times faster than a single CPU, and the CPU-GPU clusters provides a computing efficiency of about 46 times faster than the CPU clusters. These meet the requirements of rapid 3D image reconstruction and real time image display. In conclusion, the use of CPU-GPU heterogeneous cluster is an effective way to build high-performance image processing platform. (authors)

High-performance whole core Pin-by-Pin calculation based on EFEN-SP_3 method

International Nuclear Information System (INIS)

Yang Wen; Zheng Youqi; Wu Hongchun; Cao Liangzhi; Li Yunzhao

2014-01-01

The EFEN code for high-performance PWR whole core pin-by-pin calculation based on the EFEN-SP_3 method can be achieved by employing spatial parallelization based on MPI. To take advantage of the advanced computing and storage power, the entire problem spatial domain can be appropriately decomposed into sub-domains and the assigned to parallel CPUs to balance the computing load and minimize communication cost. Meanwhile, Red-Black Gauss-Seidel nodal sweeping scheme is employed to avoid the within-group iteration deterioration due to spatial parallelization. Numerical results based on whole core pin-by-pin problems designed according to commercial PWRs demonstrate the following conclusions: The EFEN code can provide results with acceptable accuracy; Communication period impacts neither the accuracy nor the parallel efficiency; Domain decomposition methods with smaller surface to volume ratio leads to greater parallel efficiency; A PWR whole core pin-by-pin calculation with a spatial mesh 289 × 289 × 218 and 4 energy groups could be completed about 900 s by using 125 CPUs, and its parallel efficiency is maintained at about 90%. (authors)

Heads in the Cloud: A Primer on Neuroimaging Applications of High Performance Computing.

Science.gov (United States)

Shatil, Anwar S; Younas, Sohail; Pourreza, Hossein; Figley, Chase R

2015-01-01

With larger data sets and more sophisticated analyses, it is becoming increasingly common for neuroimaging researchers to push (or exceed) the limitations of standalone computer workstations. Nonetheless, although high-performance computing platforms such as clusters, grids and clouds are already in routine use by a small handful of neuroimaging researchers to increase their storage and/or computational power, the adoption of such resources by the broader neuroimaging community remains relatively uncommon. Therefore, the goal of the current manuscript is to: 1) inform prospective users about the similarities and differences between computing clusters, grids and clouds; 2) highlight their main advantages; 3) discuss when it may (and may not) be advisable to use them; 4) review some of their potential problems and barriers to access; and finally 5) give a few practical suggestions for how interested new users can start analyzing their neuroimaging data using cloud resources. Although the aim of cloud computing is to hide most of the complexity of the infrastructure management from end-users, we recognize that this can still be an intimidating area for cognitive neuroscientists, psychologists, neurologists, radiologists, and other neuroimaging researchers lacking a strong computational background. Therefore, with this in mind, we have aimed to provide a basic introduction to cloud computing in general (including some of the basic terminology, computer architectures, infrastructure and service models, etc.), a practical overview of the benefits and drawbacks, and a specific focus on how cloud resources can be used for various neuroimaging applications.

Improving the Computational Performance of Ontology-Based Classification Using Graph Databases

Directory of Open Access Journals (Sweden)

Thomas J. Lampoltshammer

2015-07-01

Full Text Available The increasing availability of very high-resolution remote sensing imagery (i.e., from satellites, airborne laser scanning, or aerial photography represents both a blessing and a curse for researchers. The manual classification of these images, or other similar geo-sensor data, is time-consuming and leads to subjective and non-deterministic results. Due to this fact, (semi- automated classification approaches are in high demand in affected research areas. Ontologies provide a proper way of automated classification for various kinds of sensor data, including remotely sensed data. However, the processing of data entities—so-called individuals—is one of the most cost-intensive computational operations within ontology reasoning. Therefore, an approach based on graph databases is proposed to overcome the issue of a high time consumption regarding the classification task. The introduced approach shifts the classification task from the classical Protégé environment and its common reasoners to the proposed graph-based approaches. For the validation, the authors tested the approach on a simulation scenario based on a real-world example. The results demonstrate a quite promising improvement of classification speed—up to 80,000 times faster than the Protégé-based approach.

High performance in software development

CERN Multimedia

CERN. Geneva; Haapio, Petri; Liukkonen, Juha-Matti

2015-01-01

What are the ingredients of high-performing software? Software development, especially for large high-performance systems, is one the most complex tasks mankind has ever tried. Technological change leads to huge opportunities but challenges our old ways of working. Processing large data sets, possibly in real time or with other tight computational constraints, requires an efficient solution architecture. Efficiency requirements span from the distributed storage and large-scale organization of computation and data onto the lowest level of processor and data bus behavior. Integrating performance behavior over these levels is especially important when the computation is resource-bounded, as it is in numerics: physical simulation, machine learning, estimation of statistical models, etc. For example, memory locality and utilization of vector processing are essential for harnessing the computing power of modern processor architectures due to the deep memory hierarchies of modern general-purpose computers. As a r...

Leveraging the Power of High Performance Computing for Next Generation Sequencing Data Analysis: Tricks and Twists from a High Throughput Exome Workflow

Science.gov (United States)

Wonczak, Stephan; Thiele, Holger; Nieroda, Lech; Jabbari, Kamel; Borowski, Stefan; Sinha, Vishal; Gunia, Wilfried; Lang, Ulrich; Achter, Viktor; Nürnberg, Peter

2015-01-01

Next generation sequencing (NGS) has been a great success and is now a standard method of research in the life sciences. With this technology, dozens of whole genomes or hundreds of exomes can be sequenced in rather short time, producing huge amounts of data. Complex bioinformatics analyses are required to turn these data into scientific findings. In order to run these analyses fast, automated workflows implemented on high performance computers are state of the art. While providing sufficient compute power and storage to meet the NGS data challenge, high performance computing (HPC) systems require special care when utilized for high throughput processing. This is especially true if the HPC system is shared by different users. Here, stability, robustness and maintainability are as important for automated workflows as speed and throughput. To achieve all of these aims, dedicated solutions have to be developed. In this paper, we present the tricks and twists that we utilized in the implementation of our exome data processing workflow. It may serve as a guideline for other high throughput data analysis projects using a similar infrastructure. The code implementing our solutions is provided in the supporting information files. PMID:25942438

Computer-Aided Chemical Product Design Framework: Design of High Performance and Environmentally Friendly Refrigerants

DEFF Research Database (Denmark)

Cignitti, Stefano; Zhang, Lei; Gani, Rafiqul

properties and needs should carefully be selected for a given heat pump cycle to ensure that an optimum refrigerant is found? How can cycle performance and environmental criteria be integrated at the product design stage and not in post-design analysis? Computer-aided product design methods enable...... the possibility of designing novel molecules, mixtures and blends, such as refrigerants through a systematic framework (Cignitti et al., 2015; Yunus et al., 2014). In this presentation a computer-aided framework is presented for chemical product design through mathematical optimization. Here, molecules, mixtures...... and blends, are systematically designed through a decomposition based solution method. Given a problem definition, computer-aided molecular design (CAMD) problem is defined, which is formulated into a mixed integer nonlinear program (MINLP). The decomposed solution method then sequentially divides the MINLP...

High-performance floating-point image computing workstation for medical applications

Science.gov (United States)

Mills, Karl S.; Wong, Gilman K.; Kim, Yongmin

1990-07-01

The medical imaging field relies increasingly on imaging and graphics techniques in diverse applications with needs similar to (or more stringent than) those of the military, industrial and scientific communities. However, most image processing and graphics systems available for use in medical imaging today are either expensive, specialized, or in most cases both. High performance imaging and graphics workstations which can provide real-time results for a number of applications, while maintaining affordability and flexibility, can facilitate the application of digital image computing techniques in many different areas. This paper describes the hardware and software architecture of a medium-cost floating-point image processing and display subsystem for the NeXT computer, and its applications as a medical imaging workstation. Medical imaging applications of the workstation include use in a Picture Archiving and Communications System (PACS), in multimodal image processing and 3-D graphics workstation for a broad range of imaging modalities, and as an electronic alternator utilizing its multiple monitor display capability and large and fast frame buffer. The subsystem provides a 2048 x 2048 x 32-bit frame buffer (16 Mbytes of image storage) and supports both 8-bit gray scale and 32-bit true color images. When used to display 8-bit gray scale images, up to four different 256-color palettes may be used for each of four 2K x 2K x 8-bit image frames. Three of these image frames can be used simultaneously to provide pixel selectable region of interest display. A 1280 x 1024 pixel screen with 1: 1 aspect ratio can be windowed into the frame buffer for display of any portion of the processed image or images. In addition, the system provides hardware support for integer zoom and an 82-color cursor. This subsystem is implemented on an add-in board occupying a single slot in the NeXT computer. Up to three boards may be added to the NeXT for multiple display capability (e

Electromagnetic Modeling of Human Body Using High Performance Computing

Science.gov (United States)

Ng, Cho-Kuen; Beall, Mark; Ge, Lixin; Kim, Sanghoek; Klaas, Ottmar; Poon, Ada

Realistic simulation of electromagnetic wave propagation in the actual human body can expedite the investigation of the phenomenon of harvesting implanted devices using wireless powering coupled from external sources. The parallel electromagnetics code suite ACE3P developed at SLAC National Accelerator Laboratory is based on the finite element method for high fidelity accelerator simulation, which can be enhanced to model electromagnetic wave propagation in the human body. Starting with a CAD model of a human phantom that is characterized by a number of tissues, a finite element mesh representing the complex geometries of the individual tissues is built for simulation. Employing an optimal power source with a specific pattern of field distribution, the propagation and focusing of electromagnetic waves in the phantom has been demonstrated. Substantial speedup of the simulation is achieved by using multiple compute cores on supercomputers.

Fog computing job scheduling optimization based on bees swarm

Science.gov (United States)

Bitam, Salim; Zeadally, Sherali; Mellouk, Abdelhamid

2018-04-01

Fog computing is a new computing architecture, composed of a set of near-user edge devices called fog nodes, which collaborate together in order to perform computational services such as running applications, storing an important amount of data, and transmitting messages. Fog computing extends cloud computing by deploying digital resources at the premise of mobile users. In this new paradigm, management and operating functions, such as job scheduling aim at providing high-performance, cost-effective services requested by mobile users and executed by fog nodes. We propose a new bio-inspired optimization approach called Bees Life Algorithm (BLA) aimed at addressing the job scheduling problem in the fog computing environment. Our proposed approach is based on the optimized distribution of a set of tasks among all the fog computing nodes. The objective is to find an optimal tradeoff between CPU execution time and allocated memory required by fog computing services established by mobile users. Our empirical performance evaluation results demonstrate that the proposal outperforms the traditional particle swarm optimization and genetic algorithm in terms of CPU execution time and allocated memory.

HiGIS: An Open Framework for High Performance Geographic Information System

Directory of Open Access Journals (Sweden)

XIONG, W.

2015-08-01

Full Text Available Big data era expose many challenges to geospatial data management, geocomputation and cartography. There is no exception in geographic information systems (GIS community. Technologies and facilities of high performance computing (HPC become more and more feasible to researchers, while mobile computing, ubiquitous computing, and cloud computing are emerging. But traditional GIS need to be improved to take advantages of all these evolutions. We proposed and implemented a GIS married with high performance computing, which is called HiGIS. The goal of HiGIS is to promote the performance of geocomputation by leveraging the power of HPC, and to build an open framework for geospatial data storing, processing, displaying and sharing. In this paper the architecture, data model and modules of the HiGIS system are introduced. A geocomputation scheduling engine based on communicating sequential process was designed to exploit spatial analysis and processing. Parallel I/O strategy using file view was proposed to improve the performance of geospatial raster data access. In order to support web-based online mapping, an interactive cartographic script was provided to represent a map. A demostration of locating house was used to manifest the characteristics of HiGIS. Parallel and concurrency performance experiments show the feasibility of this system.

SISYPHUS: A high performance seismic inversion factory

Science.gov (United States)

Gokhberg, Alexey; Simutė, Saulė; Boehm, Christian; Fichtner, Andreas

2016-04-01

branches for the static process setup, inversion iterations, and solver runs, each branch specifying information at the event, station and channel levels. The workflow management framework is based on an embedded scripting engine that allows definition of various workflow scenarios using a high-level scripting language and provides access to all available inversion components represented as standard library functions. At present the SES3D wave propagation solver is integrated in the solution; the work is in progress for interfacing with SPECFEM3D. A separate framework is designed for interoperability with an optimization module; the workflow manager and optimization process run in parallel and cooperate by exchanging messages according to a specially designed protocol. A library of high-performance modules implementing signal pre-processing, misfit and adjoint computations according to established good practices is included. Monitoring is based on information stored in the inversion state database and at present implements a command line interface; design of a graphical user interface is in progress. The software design fits well into the common massively parallel system architecture featuring a large number of computational nodes running distributed applications under control of batch-oriented resource managers. The solution prototype has been implemented on the "Piz Daint" supercomputer provided by the Swiss Supercomputing Centre (CSCS).

The effect of metacognitive monitoring feedback on performance in a computer-based training simulation.

Science.gov (United States)

Kim, Jung Hyup

2018-02-01

This laboratory experiment was designed to study the effect of metacognitive monitoring feedback on performance in a computer-based training simulation. According to prior research on metacognition, the accurate checking of learning is a critical part of improving the quality of human performance. However, only rarely have researchers studied the learning effects of the accurate checking of retrospective confidence judgments (RCJs) during a computer-based military training simulation. In this study, we provided participants feedback screens after they had completed a warning task and identification task in a radar monitoring simulation. There were two groups in this experiment. One group (group A) viewed the feedback screens with the flight path of all target aircraft and the triangular graphs of both RCJ scores and human performance together. The other group (group B) only watched the feedback screens with the flight path of all target aircraft. There was no significant difference in performance improvement between groups A and B for the warning task (Day 1: group A - 0.347, group B - 0.305; Day 2: group A - 0.488, group B - 0.413). However, the identification task yielded a significant difference in performance improvement between these groups (Day 1: group A - 0.174, group B - 0.1555; Day 2: group A - 0.324, group B - 0.199). The results show that debiasing self-judgment of the identification task produces a positive training effect on learners. The findings of this study will be beneficial for designing an advanced instructional strategy in a simulation-based training environment. Copyright © 2017 Elsevier Ltd. All rights reserved.

Running Interactive Jobs on Peregrine | High-Performance Computing | NREL

Science.gov (United States)

shell prompt, which allows users to execute commands and scripts as they would on the login nodes. Login performed on the compute nodes rather than on login nodes. This page provides instructions and examples of , start GUIs etc. and the commands will execute on that node instead of on the login node. The -V option

HIGH PERFORMANCE CERIA BASED OXYGEN MEMBRANE

DEFF Research Database (Denmark)

2014-01-01

The invention describes a new class of highly stable mixed conducting materials based on acceptor doped cerium oxide (CeO2-8 ) in which the limiting electronic conductivity is significantly enhanced by co-doping with a second element or co- dopant, such as Nb, W and Zn, so that cerium and the co......-dopant have an ionic size ratio between 0.5 and 1. These materials can thereby improve the performance and extend the range of operating conditions of oxygen permeation membranes (OPM) for different high temperature membrane reactor applications. The invention also relates to the manufacturing of supported...

Brain inspired high performance electronics on flexible silicon

KAUST Repository

Sevilla, Galo T.

2014-06-01

Brain\\'s stunning speed, energy efficiency and massive parallelism makes it the role model for upcoming high performance computation systems. Although human brain components are a million times slower than state of the art silicon industry components [1], they can perform 1016 operations per second while consuming less power than an electrical light bulb. In order to perform the same amount of computation with today\\'s most advanced computers, the output of an entire power station would be needed. In that sense, to obtain brain like computation, ultra-fast devices with ultra-low power consumption will have to be integrated in extremely reduced areas, achievable only if brain folded structure is mimicked. Therefore, to allow brain-inspired computation, flexible and transparent platform will be needed to achieve foldable structures and their integration on asymmetric surfaces. In this work, we show a new method to fabricate 3D and planar FET architectures in flexible and semitransparent silicon fabric without comprising performance and maintaining cost/yield advantage offered by silicon-based electronics.

GRID computing for experimental high energy physics

International Nuclear Information System (INIS)

Moloney, G.R.; Martin, L.; Seviour, E.; Taylor, G.N.; Moorhead, G.F.

2002-01-01

Full text: The Large Hadron Collider (LHC), to be completed at the CERN laboratory in 2006, will generate 11 petabytes of data per year. The processing of this large data stream requires a large, distributed computing infrastructure. A recent innovation in high performance distributed computing, the GRID, has been identified as an important tool in data analysis for the LHC. GRID computing has actual and potential application in many fields which require computationally intensive analysis of large, shared data sets. The Australian experimental High Energy Physics community has formed partnerships with the High Performance Computing community to establish a GRID node at the University of Melbourne. Through Australian membership of the ATLAS experiment at the LHC, Australian researchers have an opportunity to be involved in the European DataGRID project. This presentation will include an introduction to the GRID, and it's application to experimental High Energy Physics. We will present the results of our studies, including participation in the first LHC data challenge

Threshold-based queuing system for performance analysis of cloud computing system with dynamic scaling

Energy Technology Data Exchange (ETDEWEB)

Shorgin, Sergey Ya.; Pechinkin, Alexander V. [Institute of Informatics Problems, Russian Academy of Sciences (Russian Federation); Samouylov, Konstantin E.; Gaidamaka, Yuliya V.; Gudkova, Irina A.; Sopin, Eduard S. [Telecommunication Systems Department, Peoples’ Friendship University of Russia (Russian Federation)

2015-03-10

Cloud computing is promising technology to manage and improve utilization of computing center resources to deliver various computing and IT services. For the purpose of energy saving there is no need to unnecessarily operate many servers under light loads, and they are switched off. On the other hand, some servers should be switched on in heavy load cases to prevent very long delays. Thus, waiting times and system operating cost can be maintained on acceptable level by dynamically adding or removing servers. One more fact that should be taken into account is significant server setup costs and activation times. For better energy efficiency, cloud computing system should not react on instantaneous increase or instantaneous decrease of load. That is the main motivation for using queuing systems with hysteresis for cloud computing system modelling. In the paper, we provide a model of cloud computing system in terms of multiple server threshold-based infinite capacity queuing system with hysteresis and noninstantanuous server activation. For proposed model, we develop a method for computing steady-state probabilities that allow to estimate a number of performance measures.

Threshold-based queuing system for performance analysis of cloud computing system with dynamic scaling

International Nuclear Information System (INIS)

Shorgin, Sergey Ya.; Pechinkin, Alexander V.; Samouylov, Konstantin E.; Gaidamaka, Yuliya V.; Gudkova, Irina A.; Sopin, Eduard S.

2015-01-01

Cloud computing is promising technology to manage and improve utilization of computing center resources to deliver various computing and IT services. For the purpose of energy saving there is no need to unnecessarily operate many servers under light loads, and they are switched off. On the other hand, some servers should be switched on in heavy load cases to prevent very long delays. Thus, waiting times and system operating cost can be maintained on acceptable level by dynamically adding or removing servers. One more fact that should be taken into account is significant server setup costs and activation times. For better energy efficiency, cloud computing system should not react on instantaneous increase or instantaneous decrease of load. That is the main motivation for using queuing systems with hysteresis for cloud computing system modelling. In the paper, we provide a model of cloud computing system in terms of multiple server threshold-based infinite capacity queuing system with hysteresis and noninstantanuous server activation. For proposed model, we develop a method for computing steady-state probabilities that allow to estimate a number of performance measures

Computational Model-Based Prediction of Human Episodic Memory Performance Based on Eye Movements

Science.gov (United States)

Sato, Naoyuki; Yamaguchi, Yoko

Subjects' episodic memory performance is not simply reflected by eye movements. We use a ‘theta phase coding’ model of the hippocampus to predict subjects' memory performance from their eye movements. Results demonstrate the ability of the model to predict subjects' memory performance. These studies provide a novel approach to computational modeling in the human-machine interface.

Heads in the Cloud: A Primer on Neuroimaging Applications of High Performance Computing

Science.gov (United States)

Shatil, Anwar S.; Younas, Sohail; Pourreza, Hossein; Figley, Chase R.

2015-01-01

With larger data sets and more sophisticated analyses, it is becoming increasingly common for neuroimaging researchers to push (or exceed) the limitations of standalone computer workstations. Nonetheless, although high-performance computing platforms such as clusters, grids and clouds are already in routine use by a small handful of neuroimaging researchers to increase their storage and/or computational power, the adoption of such resources by the broader neuroimaging community remains relatively uncommon. Therefore, the goal of the current manuscript is to: 1) inform prospective users about the similarities and differences between computing clusters, grids and clouds; 2) highlight their main advantages; 3) discuss when it may (and may not) be advisable to use them; 4) review some of their potential problems and barriers to access; and finally 5) give a few practical suggestions for how interested new users can start analyzing their neuroimaging data using cloud resources. Although the aim of cloud computing is to hide most of the complexity of the infrastructure management from end-users, we recognize that this can still be an intimidating area for cognitive neuroscientists, psychologists, neurologists, radiologists, and other neuroimaging researchers lacking a strong computational background. Therefore, with this in mind, we have aimed to provide a basic introduction to cloud computing in general (including some of the basic terminology, computer architectures, infrastructure and service models, etc.), a practical overview of the benefits and drawbacks, and a specific focus on how cloud resources can be used for various neuroimaging applications. PMID:27279746

Heads in the Cloud: A Primer on Neuroimaging Applications of High Performance Computing

Directory of Open Access Journals (Sweden)

Anwar S. Shatil

2015-01-01

Full Text Available With larger data sets and more sophisticated analyses, it is becoming increasingly common for neuroimaging researchers to push (or exceed the limitations of standalone computer workstations. Nonetheless, although high-performance computing platforms such as clusters, grids and clouds are already in routine use by a small handful of neuroimaging researchers to increase their storage and/or computational power, the adoption of such resources by the broader neuroimaging community remains relatively uncommon. Therefore, the goal of the current manuscript is to: 1 inform prospective users about the similarities and differences between computing clusters, grids and clouds; 2 highlight their main advantages; 3 discuss when it may (and may not be advisable to use them; 4 review some of their potential problems and barriers to access; and finally 5 give a few practical suggestions for how interested new users can start analyzing their neuroimaging data using cloud resources. Although the aim of cloud computing is to hide most of the complexity of the infrastructure management from end-users, we recognize that this can still be an intimidating area for cognitive neuroscientists, psychologists, neurologists, radiologists, and other neuroimaging researchers lacking a strong computational background. Therefore, with this in mind, we have aimed to provide a basic introduction to cloud computing in general (including some of the basic terminology, computer architectures, infrastructure and service models, etc., a practical overview of the benefits and drawbacks, and a specific focus on how cloud resources can be used for various neuroimaging applications.

Accelerated Synchrotron X-ray Diffraction Data Analysis on a Heterogeneous High Performance Computing System

Energy Technology Data Exchange (ETDEWEB)

Qin, J; Bauer, M A, E-mail: qin.jinhui@gmail.com, E-mail: bauer@uwo.ca [Computer Science Department, University of Western Ontario, London, ON N6A 5B7 (Canada)

2010-11-01

The analysis of synchrotron X-ray Diffraction (XRD) data has been used by scientists and engineers to understand and predict properties of materials. However, the large volume of XRD image data and the intensive computations involved in the data analysis makes it hard for researchers to quickly reach any conclusions about the images from an experiment when using conventional XRD data analysis software. Synchrotron time is valuable and delays in XRD data analysis can impact decisions about subsequent experiments or about materials that they are investigating. In order to improve the data analysis performance, ideally to achieve near real time data analysis during an XRD experiment, we designed and implemented software for accelerated XRD data analysis. The software has been developed for a heterogeneous high performance computing (HPC) system, comprised of IBM PowerXCell 8i processors and Intel quad-core Xeon processors. This paper describes the software and reports on the improved performance. The results indicate that it is possible for XRD data to be analyzed at the rate it is being produced.

Accelerated Synchrotron X-ray Diffraction Data Analysis on a Heterogeneous High Performance Computing System

International Nuclear Information System (INIS)

Qin, J; Bauer, M A

2010-01-01

The analysis of synchrotron X-ray Diffraction (XRD) data has been used by scientists and engineers to understand and predict properties of materials. However, the large volume of XRD image data and the intensive computations involved in the data analysis makes it hard for researchers to quickly reach any conclusions about the images from an experiment when using conventional XRD data analysis software. Synchrotron time is valuable and delays in XRD data analysis can impact decisions about subsequent experiments or about materials that they are investigating. In order to improve the data analysis performance, ideally to achieve near real time data analysis during an XRD experiment, we designed and implemented software for accelerated XRD data analysis. The software has been developed for a heterogeneous high performance computing (HPC) system, comprised of IBM PowerXCell 8i processors and Intel quad-core Xeon processors. This paper describes the software and reports on the improved performance. The results indicate that it is possible for XRD data to be analyzed at the rate it is being produced.

High-performance secure multi-party computation for data mining applications

DEFF Research Database (Denmark)

Bogdanov, Dan; Niitsoo, Margus; Toft, Tomas

2012-01-01

Secure multi-party computation (MPC) is a technique well suited for privacy-preserving data mining. Even with the recent progress in two-party computation techniques such as fully homomorphic encryption, general MPC remains relevant as it has shown promising performance metrics in real...... operations such as multiplication and comparison. Secondly, the confidential processing of financial data requires the use of more complex primitives, including a secure division operation. This paper describes new protocols in the Sharemind model for secure multiplication, share conversion, equality, bit...

Performative Computation-aided Design Optimization

Directory of Open Access Journals (Sweden)

Ming Tang

2012-12-01

Full Text Available This article discusses a collaborative research and teaching project between the University of Cincinnati, Perkins+Will’s Tech Lab, and the University of North Carolina Greensboro. The primary investigation focuses on the simulation, optimization, and generation of architectural designs using performance-based computational design approaches. The projects examine various design methods, including relationships between building form, performance and the use of proprietary software tools for parametric design.

The effect of dynamic workstations on the performance of various computer and office-based tasks

NARCIS (Netherlands)

Burford, E.M.; Botter, J.; Commissaris, D.; Könemann, R.; Hiemstra-Van Mastrigt, S.; Ellegast, R.P.

2013-01-01

The effect of different workstations, conventional and dynamic, on different types of performance measures for several different office and computer based task was investigated in this research paper. The two dynamic workstations assessed were the Lifespan Treadmill Desk and the RightAngle

Additive Manufacturing and High-Performance Computing: a Disruptive Latent Technology

Science.gov (United States)

Goodwin, Bruce

2015-03-01

This presentation will discuss the relationship between recent advances in Additive Manufacturing (AM) technology, High-Performance Computing (HPC) simulation and design capabilities, and related advances in Uncertainty Quantification (UQ), and then examines their impacts upon national and international security. The presentation surveys how AM accelerates the fabrication process, while HPC combined with UQ provides a fast track for the engineering design cycle. The combination of AM and HPC/UQ almost eliminates the engineering design and prototype iterative cycle, thereby dramatically reducing cost of production and time-to-market. These methods thereby present significant benefits for US national interests, both civilian and military, in an age of austerity. Finally, considering cyber security issues and the advent of the ``cloud,'' these disruptive, currently latent technologies may well enable proliferation and so challenge both nuclear and non-nuclear aspects of international security.

Software Applications on the Peregrine System | High-Performance Computing

Science.gov (United States)

Algebraic Modeling System (GAMS) Statistics and analysis High-level modeling system for mathematical reactivity. Gurobi Optimizer Statistics and analysis Solver for mathematical programming LAMMPS Chemistry and , reactivities, and vibrational, electronic and NMR spectra. R Statistical Computing Environment Statistics and

Homemade Buckeye-Pi: A Learning Many-Node Platform for High-Performance Parallel Computing

Science.gov (United States)

Amooie, M. A.; Moortgat, J.

2017-12-01

We report on the "Buckeye-Pi" cluster, the supercomputer developed in The Ohio State University School of Earth Sciences from 128 inexpensive Raspberry Pi (RPi) 3 Model B single-board computers. Each RPi is equipped with fast Quad Core 1.2GHz ARMv8 64bit processor, 1GB of RAM, and 32GB microSD card for local storage. Therefore, the cluster has a total RAM of 128GB that is distributed on the individual nodes and a flash capacity of 4TB with 512 processors, while it benefits from low power consumption, easy portability, and low total cost. The cluster uses the Message Passing Interface protocol to manage the communications between each node. These features render our platform the most powerful RPi supercomputer to date and suitable for educational applications in high-performance-computing (HPC) and handling of large datasets. In particular, we use the Buckeye-Pi to implement optimized parallel codes in our in-house simulator for subsurface media flows with the goal of achieving a massively-parallelized scalable code. We present benchmarking results for the computational performance across various number of RPi nodes. We believe our project could inspire scientists and students to consider the proposed unconventional cluster architecture as a mainstream and a feasible learning platform for challenging engineering and scientific problems.

Computer-Related Task Performance

DEFF Research Database (Denmark)

Longstreet, Phil; Xiao, Xiao; Sarker, Saonee

2016-01-01

The existing information system (IS) literature has acknowledged computer self-efficacy (CSE) as an important factor contributing to enhancements in computer-related task performance. However, the empirical results of CSE on performance have not always been consistent, and increasing an individual......'s CSE is often a cumbersome process. Thus, we introduce the theoretical concept of self-prophecy (SP) and examine how this social influence strategy can be used to improve computer-related task performance. Two experiments are conducted to examine the influence of SP on task performance. Results show...... that SP and CSE interact to influence performance. Implications are then discussed in terms of organizations’ ability to increase performance....

A comprehensive approach to decipher biological computation to achieve next generation high-performance exascale computing.

Energy Technology Data Exchange (ETDEWEB)

James, Conrad D.; Schiess, Adrian B.; Howell, Jamie; Baca, Michael J.; Partridge, L. Donald; Finnegan, Patrick Sean; Wolfley, Steven L.; Dagel, Daryl James; Spahn, Olga Blum; Harper, Jason C.; Pohl, Kenneth Roy; Mickel, Patrick R.; Lohn, Andrew; Marinella, Matthew

2013-10-01

The human brain (volume=1200cm3) consumes 20W and is capable of performing > 10^16 operations/s. Current supercomputer technology has reached 1015 operations/s, yet it requires 1500m^3 and 3MW, giving the brain a 10^12 advantage in operations/s/W/cm^3. Thus, to reach exascale computation, two achievements are required: 1) improved understanding of computation in biological tissue, and 2) a paradigm shift towards neuromorphic computing where hardware circuits mimic properties of neural tissue. To address 1), we will interrogate corticostriatal networks in mouse brain tissue slices, specifically with regard to their frequency filtering capabilities as a function of input stimulus. To address 2), we will instantiate biological computing characteristics such as multi-bit storage into hardware devices with future computational and memory applications. Resistive memory devices will be modeled, designed, and fabricated in the MESA facility in consultation with our internal and external collaborators.

Hot Chips and Hot Interconnects for High End Computing Systems

Science.gov (United States)

Saini, Subhash

2005-01-01

I will discuss several processors: 1. The Cray proprietary processor used in the Cray X1; 2. The IBM Power 3 and Power 4 used in an IBM SP 3 and IBM SP 4 systems; 3. The Intel Itanium and Xeon, used in the SGI Altix systems and clusters respectively; 4. IBM System-on-a-Chip used in IBM BlueGene/L; 5. HP Alpha EV68 processor used in DOE ASCI Q cluster; 6. SPARC64 V processor, which is used in the Fujitsu PRIMEPOWER HPC2500; 7. An NEC proprietary processor, which is used in NEC SX-6/7; 8. Power 4+ processor, which is used in Hitachi SR11000; 9. NEC proprietary processor, which is used in Earth Simulator. The IBM POWER5 and Red Storm Computing Systems will also be discussed. The architectures of these processors will first be presented, followed by interconnection networks and a description of high-end computer systems based on these processors and networks. The performance of various hardware/programming model combinations will then be compared, based on latest NAS Parallel Benchmark results (MPI, OpenMP/HPF and hybrid (MPI + OpenMP). The tutorial will conclude with a discussion of general trends in the field of high performance computing, (quantum computing, DNA computing, cellular engineering, and neural networks).

Performance Issues in High Performance Fortran Implementations of Sensor-Based Applications

Directory of Open Access Journals (Sweden)

David R. O'hallaron

1997-01-01

Full Text Available Applications that get their inputs from sensors are an important and often overlooked application domain for High Performance Fortran (HPF. Such sensor-based applications typically perform regular operations on dense arrays, and often have latency and through put requirements that can only be achieved with parallel machines. This article describes a study of sensor-based applications, including the fast Fourier transform, synthetic aperture radar imaging, narrowband tracking radar processing, multibaseline stereo imaging, and medical magnetic resonance imaging. The applications are written in a dialect of HPF developed at Carnegie Mellon, and are compiled by the Fx compiler for the Intel Paragon. The main results of the study are that (1 it is possible to realize good performance for realistic sensor-based applications written in HPF and (2 the performance of the applications is determined by the performance of three core operations: independent loops (i.e., loops with no dependences between iterations, reductions, and index permutations. The article discusses the implications for HPF implementations and introduces some simple tests that implementers and users can use to measure the efficiency of the loops, reductions, and index permutations generated by an HPF compiler.

Building a High Performance Computing Infrastructure for Novosibirsk Scientific Center

International Nuclear Information System (INIS)

Adakin, A; Chubarov, D; Nikultsev, V; Belov, S; Kaplin, V; Sukharev, A; Zaytsev, A; Kalyuzhny, V; Kuchin, N; Lomakin, S

2011-01-01

Novosibirsk Scientific Center (NSC), also known worldwide as Akademgorodok, is one of the largest Russian scientific centers hosting Novosibirsk State University (NSU) and more than 35 research organizations of the Siberian Branch of Russian Academy of Sciences including Budker Institute of Nuclear Physics (BINP), Institute of Computational Technologies (ICT), and Institute of Computational Mathematics and Mathematical Geophysics (ICM and MG). Since each institute has specific requirements on the architecture of the computing farms involved in its research field, currently we've got several computing facilities hosted by NSC institutes, each optimized for the particular set of tasks, of which the largest are the NSU Supercomputer Center, Siberian Supercomputer Center (ICM and MG), and a Grid Computing Facility of BINP. Recently a dedicated optical network with the initial bandwidth of 10 Gbps connecting these three facilities was built in order to make it possible to share the computing resources among the research communities of participating institutes, thus providing a common platform for building the computing infrastructure for various scientific projects. Unification of the computing infrastructure is achieved by extensive use of virtualization technologies based on XEN and KVM platforms. The solution implemented was tested thoroughly within the computing environment of KEDR detector experiment which is being carried out at BINP, and foreseen to be applied to the use cases of other HEP experiments in the upcoming future.

High temperature performance of soy-based adhesives

Science.gov (United States)

Jane L. O’Dell; Christopher G. Hunt; Charles R. Frihart

2013-01-01

We studied the high temperature performance of soy meal processed to different protein concentrations (flour, concentrate, and isolate), as well as formulated soy-based adhesives, and commercial nonsoy adhesives for comparison. No thermal transitions were seen in phenol-resorcinol-formaldehyde (PRF) or soy-phenol-formaldehyde (SoyPF) or in as-received soy flour...

A COTS-based single board radiation-hardened computer for space applications

International Nuclear Information System (INIS)

Stewart, S.; Hillman, R.; Layton, P.; Krawzsenek, D.

1999-01-01

There is great community interest in the ability to use COTS (Commercial-Off-The-Shelf) technology in radiation environments. Space Electronics, Inc. has developed a high performance COTS-based radiation hardened computer. COTS approaches were selected for both hardware and software. Through parts testing, selection and packaging, all requirements have been met without parts or process development. Reliability, total ionizing dose and single event performance are attractive. The characteristics, performance and radiation resistance of the single board computer will be presented. (authors)

What happens during a Join? - Dissecting CPU and Memory Optimization Effects

NARCIS (Netherlands)

S. Manegold (Stefan); P.A. Boncz (Peter); M.L. Kersten (Martin)

2000-01-01

textabstractPerformance of modern hardware increasingly depends on proper utilization of both the memory cache hierarchy and parallel execution possibilities in todays super-scalar CPUs. Recent database research has demonstrated that database system performance severely suffers from poor utilization

Optimization and large scale computation of an entropy-based moment closure

Science.gov (United States)

Kristopher Garrett, C.; Hauck, Cory; Hill, Judith

2015-12-01

We present computational advances and results in the implementation of an entropy-based moment closure, MN, in the context of linear kinetic equations, with an emphasis on heterogeneous and large-scale computing platforms. Entropy-based closures are known in several cases to yield more accurate results than closures based on standard spectral approximations, such as PN, but the computational cost is generally much higher and often prohibitive. Several optimizations are introduced to improve the performance of entropy-based algorithms over previous implementations. These optimizations include the use of GPU acceleration and the exploitation of the mathematical properties of spherical harmonics, which are used as test functions in the moment formulation. To test the emerging high-performance computing paradigm of communication bound simulations, we present timing results at the largest computational scales currently available. These results show, in particular, load balancing issues in scaling the MN algorithm that do not appear for the PN algorithm. We also observe that in weak scaling tests, the ratio in time to solution of MN to PN decreases.

High performance GPU processing for inversion using uniform grid searches

Science.gov (United States)

Venetis, Ioannis E.; Saltogianni, Vasso; Stiros, Stathis; Gallopoulos, Efstratios

2017-04-01

Many geophysical problems are described by systems of redundant, highly non-linear systems of ordinary equations with constant terms deriving from measurements and hence representing stochastic variables. Solution (inversion) of such problems is based on numerical, optimization methods, based on Monte Carlo sampling or on exhaustive searches in cases of two or even three "free" unknown variables. Recently the TOPological INVersion (TOPINV) algorithm, a grid search-based technique in the Rn space, has been proposed. TOPINV is not based on the minimization of a certain cost function and involves only forward computations, hence avoiding computational errors. The basic concept is to transform observation equations into inequalities on the basis of an optimization parameter k and of their standard errors, and through repeated "scans" of n-dimensional search grids for decreasing values of k to identify the optimal clusters of gridpoints which satisfy observation inequalities and by definition contain the "true" solution. Stochastic optimal solutions and their variance-covariance matrices are then computed as first and second statistical moments. Such exhaustive uniform searches produce an excessive computational load and are extremely time consuming for common computers based on a CPU. An alternative is to use a computing platform based on a GPU, which nowadays is affordable to the research community, which provides a much higher computing performance. Using the CUDA programming language to implement TOPINV allows the investigation of the attained speedup in execution time on such a high performance platform. Based on synthetic data we compared the execution time required for two typical geophysical problems, modeling magma sources and seismic faults, described with up to 18 unknown variables, on both CPU/FORTRAN and GPU/CUDA platforms. The same problems for several different sizes of search grids (up to 1012 gridpoints) and numbers of unknown variables were solved on

Computational aeroelasticity using a pressure-based solver

Science.gov (United States)

Kamakoti, Ramji

A computational methodology for performing fluid-structure interaction computations for three-dimensional elastic wing geometries is presented. The flow solver used is based on an unsteady Reynolds-Averaged Navier-Stokes (RANS) model. A well validated k-ε turbulence model with wall function treatment for near wall region was used to perform turbulent flow calculations. Relative merits of alternative flow solvers were investigated. The predictor-corrector-based Pressure Implicit Splitting of Operators (PISO) algorithm was found to be computationally economic for unsteady flow computations. Wing structure was modeled using Bernoulli-Euler beam theory. A fully implicit time-marching scheme (using the Newmark integration method) was used to integrate the equations of motion for structure. Bilinear interpolation and linear extrapolation techniques were used to transfer necessary information between fluid and structure solvers. Geometry deformation was accounted for by using a moving boundary module. The moving grid capability was based on a master/slave concept and transfinite interpolation techniques. Since computations were performed on a moving mesh system, the geometric conservation law must be preserved. This is achieved by appropriately evaluating the Jacobian values associated with each cell. Accurate computation of contravariant velocities for unsteady flows using the momentum interpolation method on collocated, curvilinear grids was also addressed. Flutter computations were performed for the AGARD 445.6 wing at subsonic, transonic and supersonic Mach numbers. Unsteady computations were performed at various dynamic pressures to predict the flutter boundary. Results showed favorable agreement of experiment and previous numerical results. The computational methodology exhibited capabilities to predict both qualitative and quantitative features of aeroelasticity.

High-Performance Networking

CERN Multimedia

CERN. Geneva

2003-01-01

The series will start with an historical introduction about what people saw as high performance message communication in their time and how that developed to the now to day known "standard computer network communication". It will be followed by a far more technical part that uses the High Performance Computer Network standards of the 90's, with 1 Gbit/sec systems as introduction for an in depth explanation of the three new 10 Gbit/s network and interconnect technology standards that exist already or emerge. If necessary for a good understanding some sidesteps will be included to explain important protocols as well as some necessary details of concerned Wide Area Network (WAN) standards details including some basics of wavelength multiplexing (DWDM). Some remarks will be made concerning the rapid expanding applications of networked storage.

A methodology for performing computer security reviews

International Nuclear Information System (INIS)

Hunteman, W.J.

1991-01-01

DOE Order 5637.1, ''Classified Computer Security,'' requires regular reviews of the computer security activities for an ADP system and for a site. Based on experiences gained in the Los Alamos computer security program through interactions with DOE facilities, we have developed a methodology to aid a site or security officer in performing a comprehensive computer security review. The methodology is designed to aid a reviewer in defining goals of the review (e.g., preparation for inspection), determining security requirements based on DOE policies, determining threats/vulnerabilities based on DOE and local threat guidance, and identifying critical system components to be reviewed. Application of the methodology will result in review procedures and checklists oriented to the review goals, the target system, and DOE policy requirements. The review methodology can be used to prepare for an audit or inspection and as a periodic self-check tool to determine the status of the computer security program for a site or specific ADP system. 1 tab

A methodology for performing computer security reviews

International Nuclear Information System (INIS)

Hunteman, W.J.

1991-01-01

This paper reports on DIE Order 5637.1, Classified Computer Security, which requires regular reviews of the computer security activities for an ADP system and for a site. Based on experiences gained in the Los Alamos computer security program through interactions with DOE facilities, the authors have developed a methodology to aid a site or security officer in performing a comprehensive computer security review. The methodology is designed to aid a reviewer in defining goals of the review (e.g., preparation for inspection), determining security requirements based on DOE policies, determining threats/vulnerabilities based on DOE and local threat guidance, and identifying critical system components to be reviewed. Application of the methodology will result in review procedures and checklists oriented to the review goals, the target system, and DOE policy requirements. The review methodology can be used to prepare for an audit or inspection and as a periodic self-check tool to determine the status of the computer security program for a site or specific ADP system

Human performance models for computer-aided engineering

Science.gov (United States)

Elkind, Jerome I. (Editor); Card, Stuart K. (Editor); Hochberg, Julian (Editor); Huey, Beverly Messick (Editor)

1989-01-01

This report discusses a topic important to the field of computational human factors: models of human performance and their use in computer-based engineering facilities for the design of complex systems. It focuses on a particular human factors design problem -- the design of cockpit systems for advanced helicopters -- and on a particular aspect of human performance -- vision and related cognitive functions. By focusing in this way, the authors were able to address the selected topics in some depth and develop findings and recommendations that they believe have application to many other aspects of human performance and to other design domains.

Nonlinear Multivariate Spline-Based Control Allocation for High-Performance Aircraft

OpenAIRE

Tol, H.J.; De Visser, C.C.; Van Kampen, E.; Chu, Q.P.

2014-01-01

High performance flight control systems based on the nonlinear dynamic inversion (NDI) principle require highly accurate models of aircraft aerodynamics. In general, the accuracy of the internal model determines to what degree the system nonlinearities can be canceled; the more accurate the model, the better the cancellation, and with that, the higher the performance of the controller. In this paper a new control system is presented that combines NDI with multivariate simplex spline based con...

Efficacy of Code Optimization on Cache-based Processors

Science.gov (United States)

VanderWijngaart, Rob F.; Chancellor, Marisa K. (Technical Monitor)

1997-01-01

The current common wisdom in the U.S. is that the powerful, cost-effective supercomputers of tomorrow will be based on commodity (RISC) micro-processors with cache memories. Already, most distributed systems in the world use such hardware as building blocks. This shift away from vector supercomputers and towards cache-based systems has brought about a change in programming paradigm, even when ignoring issues of parallelism. Vector machines require inner-loop independence and regular, non-pathological memory strides (usually this means: non-power-of-two strides) to allow efficient vectorization of array operations. Cache-based systems require spatial and temporal locality of data, so that data once read from main memory and stored in high-speed cache memory is used optimally before being written back to main memory. This means that the most cache-friendly array operations are those that feature zero or unit stride, so that each unit of data read from main memory (a cache line) contains information for the next iteration in the loop. Moreover, loops ought to be 'fat', meaning that as many operations as possible are performed on cache data-provided instruction caches do not overflow and enough registers are available. If unit stride is not possible, for example because of some data dependency, then care must be taken to avoid pathological strides, just ads on vector computers. For cache-based systems the issues are more complex, due to the effects of associativity and of non-unit block (cache line) size. But there is more to the story. Most modern micro-processors are superscalar, which means that they can issue several (arithmetic) instructions per clock cycle, provided that there are enough independent instructions in the loop body. This is another argument for providing fat loop bodies. With these restrictions, it appears fairly straightforward to produce code that will run efficiently on any cache-based system. It can be argued that although some of the important

Applying GIS and high performance agent-based simulation for managing an Old World Screwworm fly invasion of Australia.

Science.gov (United States)

Welch, M C; Kwan, P W; Sajeev, A S M

2014-10-01

Agent-based modelling has proven to be a promising approach for developing rich simulations for complex phenomena that provide decision support functions across a broad range of areas including biological, social and agricultural sciences. This paper demonstrates how high performance computing technologies, namely General-Purpose Computing on Graphics Processing Units (GPGPU), and commercial Geographic Information Systems (GIS) can be applied to develop a national scale, agent-based simulation of an incursion of Old World Screwworm fly (OWS fly) into the Australian mainland. The development of this simulation model leverages the combination of massively data-parallel processing capabilities supported by NVidia's Compute Unified Device Architecture (CUDA) and the advanced spatial visualisation capabilities of GIS. These technologies have enabled the implementation of an individual-based, stochastic lifecycle and dispersal algorithm for the OWS fly invasion. The simulation model draws upon a wide range of biological data as input to stochastically determine the reproduction and survival of the OWS fly through the different stages of its lifecycle and dispersal of gravid females. Through this model, a highly efficient computational platform has been developed for studying the effectiveness of control and mitigation strategies and their associated economic impact on livestock industries can be materialised. Copyright © 2014 International Atomic Energy Agency 2014. Published by Elsevier B.V. All rights reserved.

Auto-Scaling of Geo-Based Image Processing in an OpenStack Cloud Computing Environment

Directory of Open Access Journals (Sweden)

Sanggoo Kang

2016-08-01

Full Text Available Cloud computing is a base platform for the distribution of large volumes of data and high-performance image processing on the Web. Despite wide applications in Web-based services and their many benefits, geo-spatial applications based on cloud computing technology are still developing. Auto-scaling realizes automatic scalability, i.e., the scale-out and scale-in processing of virtual servers in a cloud computing environment. This study investigates the applicability of auto-scaling to geo-based image processing algorithms by comparing the performance of a single virtual server and multiple auto-scaled virtual servers under identical experimental conditions. In this study, the cloud computing environment is built with OpenStack, and four algorithms from the Orfeo toolbox are used for practical geo-based image processing experiments. The auto-scaling results from all experimental performance tests demonstrate applicable significance with respect to cloud utilization concerning response time. Auto-scaling contributes to the development of web-based satellite image application services using cloud-based technologies.

High-performance noncontact thermal diode via asymmetric nanostructures

Science.gov (United States)

Shen, Jiadong; Liu, Xianglei; He, Huan; Wu, Weitao; Liu, Baoan

2018-05-01

Electric diodes, though laying the foundation of modern electronics and information processing industries, suffer from ineffectiveness and even failure at high temperatures. Thermal diodes are promising alternatives to relieve above limitations, but usually possess low rectification ratios, and how to obtain a high-performance thermal rectification effect is still an open question. This paper proposes an efficient contactless thermal diode based on the near-field thermal radiation of asymmetric doped silicon nanostructures. The rectification ratio computed via exact scattering theories is demonstrated to be as high as 10 at a nanoscale gap distance and period, outperforming the counterpart flat-plate diode by more than one order of magnitude. This extraordinary performance mainly lies in the higher forward and lower reverse radiative heat flux within the low frequency band compared with the counterpart flat-plate diode, which is caused by a lower loss and smaller cut-off wavevector of nanostructures for the forward and reversed scheme, respectively. This work opens new routes to realize high performance thermal diodes, and may have wide applications in efficient thermal computing, thermal information processing, and thermal management.

An adaptive multi-spline refinement algorithm in simulation based sailboat trajectory optimization using onboard multi-core computer systems

Directory of Open Access Journals (Sweden)

Dębski Roman

2016-06-01

Full Text Available A new dynamic programming based parallel algorithm adapted to on-board heterogeneous computers for simulation based trajectory optimization is studied in the context of “high-performance sailing”. The algorithm uses a new discrete space of continuously differentiable functions called the multi-splines as its search space representation. A basic version of the algorithm is presented in detail (pseudo-code, time and space complexity, search space auto-adaptation properties. Possible extensions of the basic algorithm are also described. The presented experimental results show that contemporary heterogeneous on-board computers can be effectively used for solving simulation based trajectory optimization problems. These computers can be considered micro high performance computing (HPC platforms-they offer high performance while remaining energy and cost efficient. The simulation based approach can potentially give highly accurate results since the mathematical model that the simulator is built upon may be as complex as required. The approach described is applicable to many trajectory optimization problems due to its black-box represented performance measure and use of OpenCL.

Neuroanatomical correlates of brain-computer interface performance.

Science.gov (United States)

Kasahara, Kazumi; DaSalla, Charles Sayo; Honda, Manabu; Hanakawa, Takashi

2015-04-15

Brain-computer interfaces (BCIs) offer a potential means to replace or restore lost motor function. However, BCI performance varies considerably between users, the reasons for which are poorly understood. Here we investigated the relationship between sensorimotor rhythm (SMR)-based BCI performance and brain structure. Participants were instructed to control a computer cursor using right- and left-hand motor imagery, which primarily modulated their left- and right-hemispheric SMR powers, respectively. Although most participants were able to control the BCI with success rates significantly above chance level even at the first encounter, they also showed substantial inter-individual variability in BCI success rate. Participants also underwent T1-weighted three-dimensional structural magnetic resonance imaging (MRI). The MRI data were subjected to voxel-based morphometry using BCI success rate as an independent variable. We found that BCI performance correlated with gray matter volume of the supplementary motor area, supplementary somatosensory area, and dorsal premotor cortex. We suggest that SMR-based BCI performance is associated with development of non-primary somatosensory and motor areas. Advancing our understanding of BCI performance in relation to its neuroanatomical correlates may lead to better customization of BCIs based on individual brain structure. Copyright © 2015 Elsevier Inc. All rights reserved.

High performance matrix inversion based on LU factorization for multicore architectures

KAUST Repository

Dongarra, Jack

2011-01-01

The goal of this paper is to present an efficient implementation of an explicit matrix inversion of general square matrices on multicore computer architecture. The inversion procedure is split into four steps: 1) computing the LU factorization, 2) inverting the upper triangular U factor, 3) solving a linear system, whose solution yields inverse of the original matrix and 4) applying backward column pivoting on the inverted matrix. Using a tile data layout, which represents the matrix in the system memory with an optimized cache-aware format, the computation of the four steps is decomposed into computational tasks. A directed acyclic graph is generated on the fly which represents the program data flow. Its nodes represent tasks and edges the data dependencies between them. Previous implementations of matrix inversions, available in the state-of-the-art numerical libraries, are suffer from unnecessary synchronization points, which are non-existent in our implementation in order to fully exploit the parallelism of the underlying hardware. Our algorithmic approach allows to remove these bottlenecks and to execute the tasks with loose synchronization. A runtime environment system called QUARK is necessary to dynamically schedule our numerical kernels on the available processing units. The reported results from our LU-based matrix inversion implementation significantly outperform the state-of-the-art numerical libraries such as LAPACK (5x), MKL (5x) and ScaLAPACK (2.5x) on a contemporary AMD platform with four sockets and the total of 48 cores for a matrix of size 24000. A power consumption analysis shows that our high performance implementation is also energy efficient and substantially consumes less power than its competitors. © 2011 ACM.

OpenMSI: A High-Performance Web-Based Platform for Mass Spectrometry Imaging

Energy Technology Data Exchange (ETDEWEB)

Rubel, Oliver; Greiner, Annette; Cholia, Shreyas; Louie, Katherine; Bethel, E. Wes; Northen, Trent R.; Bowen, Benjamin P.

2013-10-02

Mass spectrometry imaging (MSI) enables researchers to directly probe endogenous molecules directly within the architecture of the biological matrix. Unfortunately, efficient access, management, and analysis of the data generated by MSI approaches remain major challenges to this rapidly developing field. Despite the availability of numerous dedicated file formats and software packages, it is a widely held viewpoint that the biggest challenge is simply opening, sharing, and analyzing a file without loss of information. Here we present OpenMSI, a software framework and platform that addresses these challenges via an advanced, high-performance, extensible file format and Web API for remote data access (http://openmsi.nersc.gov). The OpenMSI file format supports storage of raw MSI data, metadata, and derived analyses in a single, self-describing format based on HDF5 and is supported by a large range of analysis software (e.g., Matlab and R) and programming languages (e.g., C++, Fortran, and Python). Careful optimization of the storage layout of MSI data sets using chunking, compression, and data replication accelerates common, selective data access operations while minimizing data storage requirements and are critical enablers of rapid data I/O. The OpenMSI file format has shown to provide >2000-fold improvement for image access operations, enabling spectrum and image retrieval in less than 0.3 s across the Internet even for 50 GB MSI data sets. To make remote high-performance compute resources accessible for analysis and to facilitate data sharing and collaboration, we describe an easy-to-use yet powerful Web API, enabling fast and convenient access to MSI data, metadata, and derived analysis results stored remotely to facilitate high-performance data analysis and enable implementation of Web based data sharing, visualization, and analysis.

The ongoing investigation of high performance parallel computing in HEP

CERN Document Server

Peach, Kenneth J; Böck, R K; Dobinson, Robert W; Hansroul, M; Norton, Alan Robert; Willers, Ian Malcolm; Baud, J P; Carminati, F; Gagliardi, F; McIntosh, E; Metcalf, M; Robertson, L; CERN. Geneva. Detector Research and Development Committee

1993-01-01

Past and current exploitation of parallel computing in High Energy Physics is summarized and a list of R & D projects in this area is presented. The applicability of new parallel hardware and software to physics problems is investigated, in the light of the requirements for computing power of LHC experiments and the current trends in the computer industry. Four main themes are discussed (possibilities for a finer grain of parallelism; fine-grain communication mechanism; usable parallel programming environment; different programming models and architectures, using standard commercial products). Parallel computing technology is potentially of interest for offline and vital for real time applications in LHC. A substantial investment in applications development and evaluation of state of the art hardware and software products is needed. A solid development environment is required at an early stage, before mainline LHC program development begins.

A data acquisition computer for high energy physics applications DAFNE:- hardware manual

International Nuclear Information System (INIS)

Barlow, J.; Seller, P.; De-An, W.

1983-07-01

A high performance stand alone computer system based on the Motorola 68000 micro processor has been built at the Rutherford Appleton Laboratory. Although the design was strongly influenced by the requirement to provide a compact data acquisition computer for the high energy physics environment, the system is sufficiently general to find applications in a wider area. It provides colour graphics and tape and disc storage together with access to CAMAC systems. This report is the hardware manual of the data acquisition computer, DAFNE (Data Acquisition For Nuclear Experiments), and as such contains a full description of the hardware structure of the computer system. (author)

DOE High Performance Computing Operational Review (HPCOR): Enabling Data-Driven Scientific Discovery at HPC Facilities

Energy Technology Data Exchange (ETDEWEB)

Gerber, Richard; Allcock, William; Beggio, Chris; Campbell, Stuart; Cherry, Andrew; Cholia, Shreyas; Dart, Eli; England, Clay; Fahey, Tim; Foertter, Fernanda; Goldstone, Robin; Hick, Jason; Karelitz, David; Kelly, Kaki; Monroe, Laura; Prabhat,; Skinner, David; White, Julia

2014-10-17

U.S. Department of Energy (DOE) High Performance Computing (HPC) facilities are on the verge of a paradigm shift in the way they deliver systems and services to science and engineering teams. Research projects are producing a wide variety of data at unprecedented scale and level of complexity, with community-specific services that are part of the data collection and analysis workflow. On June 18-19, 2014 representatives from six DOE HPC centers met in Oakland, CA at the DOE High Performance Operational Review (HPCOR) to discuss how they can best provide facilities and services to enable large-scale data-driven scientific discovery at the DOE national laboratories. The report contains findings from that review.

Individual versus Interactive Task-Based Performance through Voice-Based Computer-Mediated Communication

Science.gov (United States)

Granena, Gisela

2016-01-01

Interaction is a necessary condition for second language (L2) learning (Long, 1980, 1996). Research in computer-mediated communication has shown that interaction opportunities make learners pay attention to form in a variety of ways that promote L2 learning. This research has mostly investigated text-based rather than voice-based interaction. The…

Filter bank canonical correlation analysis for implementing a high-speed SSVEP-based brain-computer interface

Science.gov (United States)

Chen, Xiaogang; Wang, Yijun; Gao, Shangkai; Jung, Tzyy-Ping; Gao, Xiaorong

2015-08-01

Objective. Recently, canonical correlation analysis (CCA) has been widely used in steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) due to its high efficiency, robustness, and simple implementation. However, a method with which to make use of harmonic SSVEP components to enhance the CCA-based frequency detection has not been well established. Approach. This study proposed a filter bank canonical correlation analysis (FBCCA) method to incorporate fundamental and harmonic frequency components to improve the detection of SSVEPs. A 40-target BCI speller based on frequency coding (frequency range: 8-15.8 Hz, frequency interval: 0.2 Hz) was used for performance evaluation. To optimize the filter bank design, three methods (M1: sub-bands with equally spaced bandwidths; M2: sub-bands corresponding to individual harmonic frequency bands; M3: sub-bands covering multiple harmonic frequency bands) were proposed for comparison. Classification accuracy and information transfer rate (ITR) of the three FBCCA methods and the standard CCA method were estimated using an offline dataset from 12 subjects. Furthermore, an online BCI speller adopting the optimal FBCCA method was tested with a group of 10 subjects. Main results. The FBCCA methods significantly outperformed the standard CCA method. The method M3 achieved the highest classification performance. At a spelling rate of ˜33.3 characters/min, the online BCI speller obtained an average ITR of 151.18 ± 20.34 bits min-1. Significance. By incorporating the fundamental and harmonic SSVEP components in target identification, the proposed FBCCA method significantly improves the performance of the SSVEP-based BCI, and thereby facilitates its practical applications such as high-speed spelling.

Computational Thinking and Practice - A Generic Approach to Computing in Danish High Schools

DEFF Research Database (Denmark)

Caspersen, Michael E.; Nowack, Palle

2014-01-01

Internationally, there is a growing awareness on the necessity of providing relevant computing education in schools, particularly high schools. We present a new and generic approach to Computing in Danish High Schools based on a conceptual framework derived from ideas related to computational thi...

Flashing characters with famous faces improves ERP-based brain-computer interface performance

Science.gov (United States)

Kaufmann, T.; Schulz, S. M.; Grünzinger, C.; Kübler, A.

2011-10-01

Currently, the event-related potential (ERP)-based spelling device, often referred to as P300-Speller, is the most commonly used brain-computer interface (BCI) for enhancing communication of patients with impaired speech or motor function. Among numerous improvements, a most central feature has received little attention, namely optimizing the stimulus used for eliciting ERPs. Therefore we compared P300-Speller performance with the standard stimulus (flashing characters) against performance with stimuli known for eliciting particularly strong ERPs due to their psychological salience, i.e. flashing familiar faces transparently superimposed on characters. Our results not only indicate remarkably increased ERPs in response to familiar faces but also improved P300-Speller performance due to a significant reduction of stimulus sequences needed for correct character classification. These findings demonstrate a promising new approach for improving the speed and thus fluency of BCI-enhanced communication with the widely used P300-Speller.

A high-performance Riccati based solver for tree-structured quadratic programs

DEFF Research Database (Denmark)

Frison, Gianluca; Kouzoupis, Dimitris; Diehl, Moritz

2017-01-01

the online solution of such problems challenging and the development of tailored solvers crucial. In this paper, an interior point method is presented that can solve Quadratic Programs (QPs) arising in multi-stage MPC efficiently by means of a tree-structured Riccati recursion and a high-performance linear...... algebra library. A performance comparison with code-generated and general purpose sparse QP solvers shows that the computation times can be significantly reduced for all problem sizes that are practically relevant in embedded MPC applications. The presented implementation is freely available as part...

SAME4HPC: A Promising Approach in Building a Scalable and Mobile Environment for High-Performance Computing

Energy Technology Data Exchange (ETDEWEB)

Karthik, Rajasekar [ORNL

2014-01-01

In this paper, an architecture for building Scalable And Mobile Environment For High-Performance Computing with spatial capabilities called SAME4HPC is described using cutting-edge technologies and standards such as Node.js, HTML5, ECMAScript 6, and PostgreSQL 9.4. Mobile devices are increasingly becoming powerful enough to run high-performance apps. At the same time, there exist a significant number of low-end and older devices that rely heavily on the server or the cloud infrastructure to do the heavy lifting. Our architecture aims to support both of these types of devices to provide high-performance and rich user experience. A cloud infrastructure consisting of OpenStack with Ubuntu, GeoServer, and high-performance JavaScript frameworks are some of the key open-source and industry standard practices that has been adopted in this architecture.

Enabling Efficient Climate Science Workflows in High Performance Computing Environments

Science.gov (United States)

Krishnan, H.; Byna, S.; Wehner, M. F.; Gu, J.; O'Brien, T. A.; Loring, B.; Stone, D. A.; Collins, W.; Prabhat, M.; Liu, Y.; Johnson, J. N.; Paciorek, C. J.

2015-12-01

A typical climate science workflow often involves a combination of acquisition of data, modeling, simulation, analysis, visualization, publishing, and storage of results. Each of these tasks provide a myriad of challenges when running on a high performance computing environment such as Hopper or Edison at NERSC. Hurdles such as data transfer and management, job scheduling, parallel analysis routines, and publication require a lot of forethought and planning to ensure that proper quality control mechanisms are in place. These steps require effectively utilizing a combination of well tested and newly developed functionality to move data, perform analysis, apply statistical routines, and finally, serve results and tools to the greater scientific community. As part of the CAlibrated and Systematic Characterization, Attribution and Detection of Extremes (CASCADE) project we highlight a stack of tools our team utilizes and has developed to ensure that large scale simulation and analysis work are commonplace and provide operations that assist in everything from generation/procurement of data (HTAR/Globus) to automating publication of results to portals like the Earth Systems Grid Federation (ESGF), all while executing everything in between in a scalable environment in a task parallel way (MPI). We highlight the use and benefit of these tools by showing several climate science analysis use cases they have been applied to.

Mixed-Language High-Performance Computing for Plasma Simulations

Directory of Open Access Journals (Sweden)

Quanming Lu

2003-01-01

Full Text Available Java is receiving increasing attention as the most popular platform for distributed computing. However, programmers are still reluctant to embrace Java as a tool for writing scientific and engineering applications due to its still noticeable performance drawbacks compared with other programming languages such as Fortran or C. In this paper, we present a hybrid Java/Fortran implementation of a parallel particle-in-cell (PIC algorithm for plasma simulations. In our approach, the time-consuming components of this application are designed and implemented as Fortran subroutines, while less calculation-intensive components usually involved in building the user interface are written in Java. The two types of software modules have been glued together using the Java native interface (JNI. Our mixed-language PIC code was tested and its performance compared with pure Java and Fortran versions of the same algorithm on a Sun E6500 SMP system and a Linux cluster of Pentium~III machines.

A true minimally invasive approach for cochlear implantation: high accuracy in cranial base navigation through flat-panel-based volume computed tomography.

Science.gov (United States)

Majdani, Omid; Bartling, Soenke H; Leinung, Martin; Stöver, Timo; Lenarz, Minoo; Dullin, Christian; Lenarz, Thomas

2008-02-01

High-precision intraoperative navigation using high-resolution flat-panel volume computed tomography makes feasible the possibility of minimally invasive cochlear implant surgery, including cochleostomy. Conventional cochlear implant surgery is typically performed via mastoidectomy with facial recess to identify and avoid damage to vital anatomic landmarks. To accomplish this procedure via a minimally invasive approach--without performing mastoidectomy--in a precise fashion, image-guided technology is necessary. With such an approach, surgical time and expertise may be reduced, and hearing preservation may be improved. Flat-panel volume computed tomography was used to scan 4 human temporal bones. A drilling channel was planned preoperatively from the mastoid surface to the round window niche, providing a margin of safety to all functional important structures (e.g., facial nerve, chorda tympani, incus). Postoperatively, computed tomographic imaging and conventional surgical exploration of the drilled route to the cochlea were performed. All 4 specimens showed a cochleostomy located at the scala tympani anterior inferior to the round window. The chorda tympani was damaged in 1 specimen--this was preoperatively planned as a narrow facial recess was encountered. Using flat-panel volume computed tomography for image-guided surgical navigation, we were able to perform minimally invasive cochlear implant surgery defined as a narrow, single-channel mastoidotomy with cochleostomy. Although this finding is preliminary, it is technologically achievable.

Tackling some of the most intricate geophysical challenges via high-performance computing

Science.gov (United States)

Khosronejad, A.

2016-12-01

Recently, world has been witnessing significant enhancements in computing power of supercomputers. Computer clusters in conjunction with the advanced mathematical algorithms has set the stage for developing and applying powerful numerical tools to tackle some of the most intricate geophysical challenges that today`s engineers face. One such challenge is to understand how turbulent flows, in real-world settings, interact with (a) rigid and/or mobile complex bed bathymetry of waterways and sea-beds in the coastal areas; (b) objects with complex geometry that are fully or partially immersed; and (c) free-surface of waterways and water surface waves in the coastal area. This understanding is especially important because the turbulent flows in real-world environments are often bounded by geometrically complex boundaries, which dynamically deform and give rise to multi-scale and multi-physics transport phenomena, and characterized by multi-lateral interactions among various phases (e.g. air/water/sediment phases). Herein, I present some of the multi-scale and multi-physics geophysical fluid mechanics processes that I have attempted to study using an in-house high-performance computational model, the so-called VFS-Geophysics. More specifically, I will present the simulation results of turbulence/sediment/solute/turbine interactions in real-world settings. Parts of the simulations I present are performed to gain scientific insights into the processes such as sand wave formation (A. Khosronejad, and F. Sotiropoulos, (2014), Numerical simulation of sand waves in a turbulent open channel flow, Journal of Fluid Mechanics, 753:150-216), while others are carried out to predict the effects of climate change and large flood events on societal infrastructures ( A. Khosronejad, et al., (2016), Large eddy simulation of turbulence and solute transport in a forested headwater stream, Journal of Geophysical Research:, doi: 10.1002/2014JF003423).

Parallel processing using an optical delay-based reservoir computer

Science.gov (United States)

Van der Sande, Guy; Nguimdo, Romain Modeste; Verschaffelt, Guy

2016-04-01

Delay systems subject to delayed optical feedback have recently shown great potential in solving computationally hard tasks. By implementing a neuro-inspired computational scheme relying on the transient response to optical data injection, high processing speeds have been demonstrated. However, reservoir computing systems based on delay dynamics discussed in the literature are designed by coupling many different stand-alone components which lead to bulky, lack of long-term stability, non-monolithic systems. Here we numerically investigate the possibility of implementing reservoir computing schemes based on semiconductor ring lasers. Semiconductor ring lasers are semiconductor lasers where the laser cavity consists of a ring-shaped waveguide. SRLs are highly integrable and scalable, making them ideal candidates for key components in photonic integrated circuits. SRLs can generate light in two counterpropagating directions between which bistability has been demonstrated. We demonstrate that two independent machine learning tasks , even with different nature of inputs with different input data signals can be simultaneously computed using a single photonic nonlinear node relying on the parallelism offered by photonics. We illustrate the performance on simultaneous chaotic time series prediction and a classification of the Nonlinear Channel Equalization. We take advantage of different directional modes to process individual tasks. Each directional mode processes one individual task to mitigate possible crosstalk between the tasks. Our results indicate that prediction/classification with errors comparable to the state-of-the-art performance can be obtained even with noise despite the two tasks being computed simultaneously. We also find that a good performance is obtained for both tasks for a broad range of the parameters. The results are discussed in detail in [Nguimdo et al., IEEE Trans. Neural Netw. Learn. Syst. 26, pp. 3301-3307, 2015

Computational fluid dynamics (CFD) assisted performance evaluation of the Twincer (TM) disposable high-dose dry powder inhaler

NARCIS (Netherlands)

de Boer, Anne H.; Hagedoorn, Paul; Woolhouse, Robert; Wynn, Ed

Objectives To use computational fluid dynamics (CFD) for evaluating and understanding the performance of the high-dose disposable Twincer (TM) dry powder inhaler, as well as to learn the effect of design modifications on dose entrainment, powder dispersion and retention behaviour. Methods Comparison

Energy Efficient Graphene Based High Performance Capacitors.

Science.gov (United States)

Bae, Joonwon; Kwon, Oh Seok; Lee, Chang-Soo

2017-07-10

Graphene (GRP) is an interesting class of nano-structured electronic materials for various cutting-edge applications. To date, extensive research activities have been performed on the investigation of diverse properties of GRP. The incorporation of this elegant material can be very lucrative in terms of practical applications in energy storage/conversion systems. Among various those systems, high performance electrochemical capacitors (ECs) have become popular due to the recent need for energy efficient and portable devices. Therefore, in this article, the application of GRP for capacitors is described succinctly. In particular, a concise summary on the previous research activities regarding GRP based capacitors is also covered extensively. It was revealed that a lot of secondary materials such as polymers and metal oxides have been introduced to improve the performance. Also, diverse devices have been combined with capacitors for better use. More importantly, recent patents related to the preparation and application of GRP based capacitors are also introduced briefly. This article can provide essential information for future study. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Computer proficiency questionnaire: assessing low and high computer proficient seniors.