Massively parallel sparse matrix function calculations with NTPoly

Science.gov (United States)

Dawson, William; Nakajima, Takahito

2018-04-01

We present NTPoly, a massively parallel library for computing the functions of sparse, symmetric matrices. The theory of matrix functions is a well developed framework with a wide range of applications including differential equations, graph theory, and electronic structure calculations. One particularly important application area is diagonalization free methods in quantum chemistry. When the input and output of the matrix function are sparse, methods based on polynomial expansions can be used to compute matrix functions in linear time. We present a library based on these methods that can compute a variety of matrix functions. Distributed memory parallelization is based on a communication avoiding sparse matrix multiplication algorithm. OpenMP task parallellization is utilized to implement hybrid parallelization. We describe NTPoly's interface and show how it can be integrated with programs written in many different programming languages. We demonstrate the merits of NTPoly by performing large scale calculations on the K computer.

PARALLEL SPATIOTEMPORAL SPECTRAL CLUSTERING WITH MASSIVE TRAJECTORY DATA

Directory of Open Access Journals (Sweden)

Y. Z. Gu

2017-09-01

Full Text Available Massive trajectory data contains wealth useful information and knowledge. Spectral clustering, which has been shown to be effective in finding clusters, becomes an important clustering approaches in the trajectory data mining. However, the traditional spectral clustering lacks the temporal expansion on the algorithm and limited in its applicability to large-scale problems due to its high computational complexity. This paper presents a parallel spatiotemporal spectral clustering based on multiple acceleration solutions to make the algorithm more effective and efficient, the performance is proved due to the experiment carried out on the massive taxi trajectory dataset in Wuhan city, China.

Massively Parallel Sort-Merge Joins in Main Memory Multi-Core Database Systems

OpenAIRE

Albutiu, Martina-Cezara; Kemper, Alfons; Neumann, Thomas

2012-01-01

Two emerging hardware trends will dominate the database system technology in the near future: increasing main memory capacities of several TB per server and massively parallel multi-core processing. Many algorithmic and control techniques in current database technology were devised for disk-based systems where I/O dominated the performance. In this work we take a new look at the well-known sort-merge join which, so far, has not been in the focus of research in scalable massively parallel mult...

Massively parallel quantum computer simulator

NARCIS (Netherlands)

De Raedt, K.; Michielsen, K.; De Raedt, H.; Trieu, B.; Arnold, G.; Richter, M.; Lippert, Th.; Watanabe, H.; Ito, N.

2007-01-01

We describe portable software to simulate universal quantum computers on massive parallel Computers. We illustrate the use of the simulation software by running various quantum algorithms on different computer architectures, such as a IBM BlueGene/L, a IBM Regatta p690+, a Hitachi SR11000/J1, a Cray

Massively parallel Fokker-Planck code ALLAp

International Nuclear Information System (INIS)

Batishcheva, A.A.; Krasheninnikov, S.I.; Craddock, G.G.; Djordjevic, V.

1996-01-01

The recently developed for workstations Fokker-Planck code ALLA simulates the temporal evolution of 1V, 2V and 1D2V collisional edge plasmas. In this work we present the results of code parallelization on the CRI T3D massively parallel platform (ALLAp version). Simultaneously we benchmark the 1D2V parallel vesion against an analytic self-similar solution of the collisional kinetic equation. This test is not trivial as it demands a very strong spatial temperature and density variation within the simulation domain. (orig.)

Solving the Stokes problem on a massively parallel computer

DEFF Research Database (Denmark)

Axelsson, Owe; Barker, Vincent A.; Neytcheva, Maya

2001-01-01

boundary value problem for each velocity component, are solved by the conjugate gradient method with a preconditioning based on the algebraic multi‐level iteration (AMLI) technique. The velocity is found from the computed pressure. The method is optimal in the sense that the computational work...... is proportional to the number of unknowns. Further, it is designed to exploit a massively parallel computer with distributed memory architecture. Numerical experiments on a Cray T3E computer illustrate the parallel performance of the method....

The 2nd Symposium on the Frontiers of Massively Parallel Computations

Science.gov (United States)

Mills, Ronnie (Editor)

1988-01-01

Programming languages, computer graphics, neural networks, massively parallel computers, SIMD architecture, algorithms, digital terrain models, sort computation, simulation of charged particle transport on the massively parallel processor and image processing are among the topics discussed.

Massively parallel multicanonical simulations

Science.gov (United States)

Gross, Jonathan; Zierenberg, Johannes; Weigel, Martin; Janke, Wolfhard

2018-03-01

Generalized-ensemble Monte Carlo simulations such as the multicanonical method and similar techniques are among the most efficient approaches for simulations of systems undergoing discontinuous phase transitions or with rugged free-energy landscapes. As Markov chain methods, they are inherently serial computationally. It was demonstrated recently, however, that a combination of independent simulations that communicate weight updates at variable intervals allows for the efficient utilization of parallel computational resources for multicanonical simulations. Implementing this approach for the many-thread architecture provided by current generations of graphics processing units (GPUs), we show how it can be efficiently employed with of the order of 104 parallel walkers and beyond, thus constituting a versatile tool for Monte Carlo simulations in the era of massively parallel computing. We provide the fully documented source code for the approach applied to the paradigmatic example of the two-dimensional Ising model as starting point and reference for practitioners in the field.

Impact analysis on a massively parallel computer

International Nuclear Information System (INIS)

Zacharia, T.; Aramayo, G.A.

1994-01-01

Advanced mathematical techniques and computer simulation play a major role in evaluating and enhancing the design of beverage cans, industrial, and transportation containers for improved performance. Numerical models are used to evaluate the impact requirements of containers used by the Department of Energy (DOE) for transporting radioactive materials. Many of these models are highly compute-intensive. An analysis may require several hours of computational time on current supercomputers despite the simplicity of the models being studied. As computer simulations and materials databases grow in complexity, massively parallel computers have become important tools. Massively parallel computational research at the Oak Ridge National Laboratory (ORNL) and its application to the impact analysis of shipping containers is briefly described in this paper

Massively parallel evolutionary computation on GPGPUs

CERN Document Server

Tsutsui, Shigeyoshi

2013-01-01

Evolutionary algorithms (EAs) are metaheuristics that learn from natural collective behavior and are applied to solve optimization problems in domains such as scheduling, engineering, bioinformatics, and finance. Such applications demand acceptable solutions with high-speed execution using finite computational resources. Therefore, there have been many attempts to develop platforms for running parallel EAs using multicore machines, massively parallel cluster machines, or grid computing environments. Recent advances in general-purpose computing on graphics processing units (GPGPU) have opened u

Massively parallel sequencing of forensic STRs

DEFF Research Database (Denmark)

Parson, Walther; Ballard, David; Budowle, Bruce

2016-01-01

The DNA Commission of the International Society for Forensic Genetics (ISFG) is reviewing factors that need to be considered ahead of the adoption by the forensic community of short tandem repeat (STR) genotyping by massively parallel sequencing (MPS) technologies. MPS produces sequence data that...

A discrete ordinate response matrix method for massively parallel computers

International Nuclear Information System (INIS)

Hanebutte, U.R.; Lewis, E.E.

1991-01-01

A discrete ordinate response matrix method is formulated for the solution of neutron transport problems on massively parallel computers. The response matrix formulation eliminates iteration on the scattering source. The nodal matrices which result from the diamond-differenced equations are utilized in a factored form which minimizes memory requirements and significantly reduces the required number of algorithm utilizes massive parallelism by assigning each spatial node to a processor. The algorithm is accelerated effectively by a synthetic method in which the low-order diffusion equations are also solved by massively parallel red/black iterations. The method has been implemented on a 16k Connection Machine-2, and S 8 and S 16 solutions have been obtained for fixed-source benchmark problems in X--Y geometry

Computational fluid dynamics on a massively parallel computer

Science.gov (United States)

Jespersen, Dennis C.; Levit, Creon

1989-01-01

A finite difference code was implemented for the compressible Navier-Stokes equations on the Connection Machine, a massively parallel computer. The code is based on the ARC2D/ARC3D program and uses the implicit factored algorithm of Beam and Warming. The codes uses odd-even elimination to solve linear systems. Timings and computation rates are given for the code, and a comparison is made with a Cray XMP.

Identification and analysis of common bean (Phaseolus vulgaris L. transcriptomes by massively parallel pyrosequencing

Directory of Open Access Journals (Sweden)

Thimmapuram Jyothi

2011-10-01

Full Text Available Abstract Background Common bean (Phaseolus vulgaris is the most important food legume in the world. Although this crop is very important to both the developed and developing world as a means of dietary protein supply, resources available in common bean are limited. Global transcriptome analysis is important to better understand gene expression, genetic variation, and gene structure annotation in addition to other important features. However, the number and description of common bean sequences are very limited, which greatly inhibits genome and transcriptome research. Here we used 454 pyrosequencing to obtain a substantial transcriptome dataset for common bean. Results We obtained 1,692,972 reads with an average read length of 207 nucleotides (nt. These reads were assembled into 59,295 unigenes including 39,572 contigs and 19,723 singletons, in addition to 35,328 singletons less than 100 bp. Comparing the unigenes to common bean ESTs deposited in GenBank, we found that 53.40% or 31,664 of these unigenes had no matches to this dataset and can be considered as new common bean transcripts. Functional annotation of the unigenes carried out by Gene Ontology assignments from hits to Arabidopsis and soybean indicated coverage of a broad range of GO categories. The common bean unigenes were also compared to the bean bacterial artificial chromosome (BAC end sequences, and a total of 21% of the unigenes (12,724 including 9,199 contigs and 3,256 singletons match to the 8,823 BAC-end sequences. In addition, a large number of simple sequence repeats (SSRs and transcription factors were also identified in this study. Conclusions This work provides the first large scale identification of the common bean transcriptome derived by 454 pyrosequencing. This research has resulted in a 150% increase in the number of Phaseolus vulgaris ESTs. The dataset obtained through this analysis will provide a platform for functional genomics in common bean and related legumes and

Massively parallel computation of conservation laws

Energy Technology Data Exchange (ETDEWEB)

Garbey, M [Univ. Claude Bernard, Villeurbanne (France); Levine, D [Argonne National Lab., IL (United States)

1990-01-01

The authors present a new method for computing solutions of conservation laws based on the use of cellular automata with the method of characteristics. The method exploits the high degree of parallelism available with cellular automata and retains important features of the method of characteristics. It yields high numerical accuracy and extends naturally to adaptive meshes and domain decomposition methods for perturbed conservation laws. They describe the method and its implementation for a Dirichlet problem with a single conservation law for the one-dimensional case. Numerical results for the one-dimensional law with the classical Burgers nonlinearity or the Buckley-Leverett equation show good numerical accuracy outside the neighborhood of the shocks. The error in the area of the shocks is of the order of the mesh size. The algorithm is well suited for execution on both massively parallel computers and vector machines. They present timing results for an Alliant FX/8, Connection Machine Model 2, and CRAY X-MP.

The language parallel Pascal and other aspects of the massively parallel processor

Science.gov (United States)

Reeves, A. P.; Bruner, J. D.

1982-01-01

A high level language for the Massively Parallel Processor (MPP) was designed. This language, called Parallel Pascal, is described in detail. A description of the language design, a description of the intermediate language, Parallel P-Code, and details for the MPP implementation are included. Formal descriptions of Parallel Pascal and Parallel P-Code are given. A compiler was developed which converts programs in Parallel Pascal into the intermediate Parallel P-Code language. The code generator to complete the compiler for the MPP is being developed independently. A Parallel Pascal to Pascal translator was also developed. The architecture design for a VLSI version of the MPP was completed with a description of fault tolerant interconnection networks. The memory arrangement aspects of the MPP are discussed and a survey of other high level languages is given.

A Massively Parallel Code for Polarization Calculations

Science.gov (United States)

Akiyama, Shizuka; Höflich, Peter

2001-03-01

We present an implementation of our Monte-Carlo radiation transport method for rapidly expanding, NLTE atmospheres for massively parallel computers which utilizes both the distributed and shared memory models. This allows us to take full advantage of the fast communication and low latency inherent to nodes with multiple CPUs, and to stretch the limits of scalability with the number of nodes compared to a version which is based on the shared memory model. Test calculations on a local 20-node Beowulf cluster with dual CPUs showed an improved scalability by about 40%.

A massively parallel corpus: the Bible in 100 languages.

Science.gov (United States)

Christodouloupoulos, Christos; Steedman, Mark

We describe the creation of a massively parallel corpus based on 100 translations of the Bible. We discuss some of the difficulties in acquiring and processing the raw material as well as the potential of the Bible as a corpus for natural language processing. Finally we present a statistical analysis of the corpora collected and a detailed comparison between the English translation and other English corpora.

Arbuscular mycorrhizal fungi assemblages in Chernozem great groups revealed by massively parallel pyrosequencing.

Science.gov (United States)

Dai, Mulan; Hamel, Chantal; St Arnaud, Marc; He, Yong; Grant, Cynthia; Lupwayi, Newton; Janzen, Henry; Malhi, Sukhdev S; Yang, Xiaohong; Zhou, Zhiqin

2012-01-01

The arbuscular mycorrhizal (AM) fungal resources present in wheat fields of the Canadian Prairie were explored using 454 pyrosequencing. Of the 33 dominant AM fungal operational taxonomic units (OTUs) found in the 76 wheat fields surveyed at anthesis in 2009, 14 clustered as Funneliformis - Rhizophagus, 16 as Claroideoglomus, and 3 as Diversisporales. An OTU of Funneliformis mosseae and one OTU of Diversisporales each accounted for approximately 16% of all AM fungal OTUs. The former was ubiquitous, and the latter was mainly restricted to the Black and Dark Brown Chernozems. AM fungal OTU community composition was better explained by the Chernozem great groups (P = 0.044) than by measured soil properties. Fifty-two percent of the AM fungal OTUs were unrelated to measured soil properties. Black Chernozems hosted the largest AM fungal OTU diversity and almost twice the number of AM fungal sequences seen in Dark Brown Chernozems, the great group ranking second for AM fungal sequence abundance. Brown Chernozems hosted the lowest AM fungal abundance and an AM fungal diversity as low as that seen in Gray soils. We concluded that Black Chernozems are most conducive to AM fungal proliferation. AM fungi are generally distributed according to Chernozem great groups in the Canadian Prairie, although some taxa are evenly distributed in all soil groups.

A Programming Model for Massive Data Parallelism with Data Dependencies

International Nuclear Information System (INIS)

Cui, Xiaohui; Mueller, Frank; Potok, Thomas E.; Zhang, Yongpeng

2009-01-01

Accelerating processors can often be more cost and energy effective for a wide range of data-parallel computing problems than general-purpose processors. For graphics processor units (GPUs), this is particularly the case when program development is aided by environments such as NVIDIA s Compute Unified Device Architecture (CUDA), which dramatically reduces the gap between domain-specific architectures and general purpose programming. Nonetheless, general-purpose GPU (GPGPU) programming remains subject to several restrictions. Most significantly, the separation of host (CPU) and accelerator (GPU) address spaces requires explicit management of GPU memory resources, especially for massive data parallelism that well exceeds the memory capacity of GPUs. One solution to this problem is to transfer data between the GPU and host memories frequently. In this work, we investigate another approach. We run massively data-parallel applications on GPU clusters. We further propose a programming model for massive data parallelism with data dependencies for this scenario. Experience from micro benchmarks and real-world applications shows that our model provides not only ease of programming but also significant performance gains

A comparison of parallel pyrosequencing and sanger clone-based sequencing and its impact on the characterization of the genetic diversity of HIV-1.

Directory of Open Access Journals (Sweden)

Binhua Liang

Full Text Available BACKGROUND: Pyrosequencing technology has the potential to rapidly sequence HIV-1 viral quasispecies without requiring the traditional approach of cloning. In this study, we investigated the utility of ultra-deep pyrosequencing to characterize genetic diversity of the HIV-1 gag quasispecies and assessed the possible contribution of pyrosequencing technology in studying HIV-1 biology and evolution. METHODOLOGY/PRINCIPAL FINDINGS: HIV-1 gag gene was amplified from 96 patients using nested PCR. The PCR products were cloned and sequenced using capillary based Sanger fluorescent dideoxy termination sequencing. The same PCR products were also directly sequenced using the 454 pyrosequencing technology. The two sequencing methods were evaluated for their ability to characterize quasispecies variation, and to reveal sites under host immune pressure for their putative functional significance. A total of 14,034 variations were identified by 454 pyrosequencing versus 3,632 variations by Sanger clone-based (SCB sequencing. 11,050 of these variations were detected only by pyrosequencing. These undetected variations were located in the HIV-1 Gag region which is known to contain putative cytotoxic T lymphocyte (CTL and neutralizing antibody epitopes, and sites related to virus assembly and packaging. Analysis of the positively selected sites derived by the two sequencing methods identified several differences. All of them were located within the CTL epitope regions. CONCLUSIONS/SIGNIFICANCE: Ultra-deep pyrosequencing has proven to be a powerful tool for characterization of HIV-1 genetic diversity with enhanced sensitivity, efficiency, and accuracy. It also improved reliability of downstream evolutionary and functional analysis of HIV-1 quasispecies.

Scientific programming on massively parallel processor CP-PACS

International Nuclear Information System (INIS)

Boku, Taisuke

1998-01-01

The massively parallel processor CP-PACS takes various problems of calculation physics as the object, and it has been designed so that its architecture has been devised to do various numerical processings. In this report, the outline of the CP-PACS and the example of programming in the Kernel CG benchmark in NAS Parallel Benchmarks, version 1, are shown, and the pseudo vector processing mechanism and the parallel processing tuning of scientific and technical computation utilizing the three-dimensional hyper crossbar net, which are two great features of the architecture of the CP-PACS are described. As for the CP-PACS, the PUs based on RISC processor and added with pseudo vector processor are used. Pseudo vector processing is realized as the loop processing by scalar command. The features of the connection net of PUs are explained. The algorithm of the NPB version 1 Kernel CG is shown. The part that takes the time for processing most in the main loop is the product of matrix and vector (matvec), and the parallel processing of the matvec is explained. The time for the computation by the CPU is determined. As the evaluation of the performance, the evaluation of the time for execution, the short vector processing of pseudo vector processor based on slide window, and the comparison with other parallel computers are reported. (K.I.)

Micro-mechanical Simulations of Soils using Massively Parallel Supercomputers

Directory of Open Access Journals (Sweden)

David W. Washington

2004-06-01

Full Text Available In this research a computer program, Trubal version 1.51, based on the Discrete Element Method was converted to run on a Connection Machine (CM-5,a massively parallel supercomputer with 512 nodes, to expedite the computational times of simulating Geotechnical boundary value problems. The dynamic memory algorithm in Trubal program did not perform efficiently in CM-2 machine with the Single Instruction Multiple Data (SIMD architecture. This was due to the communication overhead involving global array reductions, global array broadcast and random data movement. Therefore, a dynamic memory algorithm in Trubal program was converted to a static memory arrangement and Trubal program was successfully converted to run on CM-5 machines. The converted program was called "TRUBAL for Parallel Machines (TPM." Simulating two physical triaxial experiments and comparing simulation results with Trubal simulations validated the TPM program. With a 512 nodes CM-5 machine TPM produced a nine-fold speedup demonstrating the inherent parallelism within algorithms based on the Discrete Element Method.

Massively parallel red-black algorithms for x-y-z response matrix equations

International Nuclear Information System (INIS)

Hanebutte, U.R.; Laurin-Kovitz, K.; Lewis, E.E.

1992-01-01

Recently, both discrete ordinates and spherical harmonic (S n and P n ) methods have been cast in the form of response matrices. In x-y geometry, massively parallel algorithms have been developed to solve the resulting response matrix equations on the Connection Machine family of parallel computers, the CM-2, CM-200, and CM-5. These algorithms utilize two-cycle iteration on a red-black checkerboard. In this work we examine the use of massively parallel red-black algorithms to solve response matric equations in three dimensions. This longer term objective is to utilize massively parallel algorithms to solve S n and/or P n response matrix problems. In this exploratory examination, however, we consider the simple 6 x 6 response matrices that are derivable from fine-mesh diffusion approximations in three dimensions

A massively parallel discrete ordinates response matrix method for neutron transport

International Nuclear Information System (INIS)

Hanebutte, U.R.; Lewis, E.E.

1992-01-01

In this paper a discrete ordinates response matrix method is formulated with anisotropic scattering for the solution of neutron transport problems on massively parallel computers. The response matrix formulation eliminates iteration on the scattering source. The nodal matrices that result from the diamond-differenced equations are utilized in a factored form that minimizes memory requirements and significantly reduces the number of arithmetic operations required per node. The red-black solution algorithm utilizes massive parallelism by assigning each spatial node to one or more processors. The algorithm is accelerated by a synthetic method in which the low-order diffusion equations are also solved by massively parallel red-black iterations. The method is implemented on a 16K Connection Machine-2, and S 8 and S 16 solutions are obtained for fixed-source benchmark problems in x-y geometry

Increasing the reach of forensic genetics with massively parallel sequencing.

Science.gov (United States)

Budowle, Bruce; Schmedes, Sarah E; Wendt, Frank R

2017-09-01

The field of forensic genetics has made great strides in the analysis of biological evidence related to criminal and civil matters. More so, the discipline has set a standard of performance and quality in the forensic sciences. The advent of massively parallel sequencing will allow the field to expand its capabilities substantially. This review describes the salient features of massively parallel sequencing and how it can impact forensic genetics. The features of this technology offer increased number and types of genetic markers that can be analyzed, higher throughput of samples, and the capability of targeting different organisms, all by one unifying methodology. While there are many applications, three are described where massively parallel sequencing will have immediate impact: molecular autopsy, microbial forensics and differentiation of monozygotic twins. The intent of this review is to expose the forensic science community to the potential enhancements that have or are soon to arrive and demonstrate the continued expansion the field of forensic genetics and its service in the investigation of legal matters.

Analysis of multigrid methods on massively parallel computers: Architectural implications

Science.gov (United States)

Matheson, Lesley R.; Tarjan, Robert E.

1993-01-01

We study the potential performance of multigrid algorithms running on massively parallel computers with the intent of discovering whether presently envisioned machines will provide an efficient platform for such algorithms. We consider the domain parallel version of the standard V cycle algorithm on model problems, discretized using finite difference techniques in two and three dimensions on block structured grids of size 10(exp 6) and 10(exp 9), respectively. Our models of parallel computation were developed to reflect the computing characteristics of the current generation of massively parallel multicomputers. These models are based on an interconnection network of 256 to 16,384 message passing, 'workstation size' processors executing in an SPMD mode. The first model accomplishes interprocessor communications through a multistage permutation network. The communication cost is a logarithmic function which is similar to the costs in a variety of different topologies. The second model allows single stage communication costs only. Both models were designed with information provided by machine developers and utilize implementation derived parameters. With the medium grain parallelism of the current generation and the high fixed cost of an interprocessor communication, our analysis suggests an efficient implementation requires the machine to support the efficient transmission of long messages, (up to 1000 words) or the high initiation cost of a communication must be significantly reduced through an alternative optimization technique. Furthermore, with variable length message capability, our analysis suggests the low diameter multistage networks provide little or no advantage over a simple single stage communications network.

Neural nets for massively parallel optimization

Science.gov (United States)

Dixon, Laurence C. W.; Mills, David

1992-07-01

To apply massively parallel processing systems to the solution of large scale optimization problems it is desirable to be able to evaluate any function f(z), z (epsilon) Rn in a parallel manner. The theorem of Cybenko, Hecht Nielsen, Hornik, Stinchcombe and White, and Funahasi shows that this can be achieved by a neural network with one hidden layer. In this paper we address the problem of the number of nodes required in the layer to achieve a given accuracy in the function and gradient values at all points within a given n dimensional interval. The type of activation function needed to obtain nonsingular Hessian matrices is described and a strategy for obtaining accurate minimal networks presented.

An FPGA-Based Massively Parallel Neuromorphic Cortex Simulator.

Science.gov (United States)

Wang, Runchun M; Thakur, Chetan S; van Schaik, André

2018-01-01

This paper presents a massively parallel and scalable neuromorphic cortex simulator designed for simulating large and structurally connected spiking neural networks, such as complex models of various areas of the cortex. The main novelty of this work is the abstraction of a neuromorphic architecture into clusters represented by minicolumns and hypercolumns, analogously to the fundamental structural units observed in neurobiology. Without this approach, simulating large-scale fully connected networks needs prohibitively large memory to store look-up tables for point-to-point connections. Instead, we use a novel architecture, based on the structural connectivity in the neocortex, such that all the required parameters and connections can be stored in on-chip memory. The cortex simulator can be easily reconfigured for simulating different neural networks without any change in hardware structure by programming the memory. A hierarchical communication scheme allows one neuron to have a fan-out of up to 200 k neurons. As a proof-of-concept, an implementation on one Altera Stratix V FPGA was able to simulate 20 million to 2.6 billion leaky-integrate-and-fire (LIF) neurons in real time. We verified the system by emulating a simplified auditory cortex (with 100 million neurons). This cortex simulator achieved a low power dissipation of 1.62 μW per neuron. With the advent of commercially available FPGA boards, our system offers an accessible and scalable tool for the design, real-time simulation, and analysis of large-scale spiking neural networks.

An FPGA-Based Massively Parallel Neuromorphic Cortex Simulator

Directory of Open Access Journals (Sweden)

Runchun M. Wang

2018-04-01

Full Text Available This paper presents a massively parallel and scalable neuromorphic cortex simulator designed for simulating large and structurally connected spiking neural networks, such as complex models of various areas of the cortex. The main novelty of this work is the abstraction of a neuromorphic architecture into clusters represented by minicolumns and hypercolumns, analogously to the fundamental structural units observed in neurobiology. Without this approach, simulating large-scale fully connected networks needs prohibitively large memory to store look-up tables for point-to-point connections. Instead, we use a novel architecture, based on the structural connectivity in the neocortex, such that all the required parameters and connections can be stored in on-chip memory. The cortex simulator can be easily reconfigured for simulating different neural networks without any change in hardware structure by programming the memory. A hierarchical communication scheme allows one neuron to have a fan-out of up to 200 k neurons. As a proof-of-concept, an implementation on one Altera Stratix V FPGA was able to simulate 20 million to 2.6 billion leaky-integrate-and-fire (LIF neurons in real time. We verified the system by emulating a simplified auditory cortex (with 100 million neurons. This cortex simulator achieved a low power dissipation of 1.62 μW per neuron. With the advent of commercially available FPGA boards, our system offers an accessible and scalable tool for the design, real-time simulation, and analysis of large-scale spiking neural networks.

Performance evaluations of advanced massively parallel platforms based on gyrokinetic toroidal five-dimensional Eulerian code GT5D

International Nuclear Information System (INIS)

Idomura, Yasuhiro; Jolliet, Sebastien

2010-01-01

A gyrokinetic toroidal five dimensional Eulerian code GT5D is ported on six advanced massively parallel platforms and comprehensive benchmark tests are performed. A parallelisation technique based on physical properties of the gyrokinetic equation is presented. By extending the parallelisation technique with a hybrid parallel model, the scalability of the code is improved on platforms with multi-core processors. In the benchmark tests, a good salability is confirmed up to several thousands cores on every platforms, and the maximum sustained performance of ∼18.6 Tflops is achieved using 16384 cores of BX900. (author)

First massively parallel algorithm to be implemented in Apollo-II code

International Nuclear Information System (INIS)

Stankovski, Z.

1994-01-01

The collision probability (CP) method in neutron transport, as applied to arbitrary 2D XY geometries, like the TDT module in APOLLO-II, is very time consuming. Consequently RZ or 3D extensions became prohibitive. Fortunately, this method is very suitable for parallelization. Massively parallel computer architectures, especially MIMD machines, bring a new breath to this method. In this paper we present a CM5 implementation of the CP method. Parallelization is applied to the energy groups, using the CMMD message passing library. In our case we use 32 processors for the standard 99-group APOLLIB-II library. The real advantage of this algorithm will appear in the calculation of the future fine multigroup library (about 8000 groups) of the SAPHYR project with a massively parallel computer (to the order of hundreds of processors). (author). 3 tabs., 4 figs., 4 refs

First massively parallel algorithm to be implemented in APOLLO-II code

International Nuclear Information System (INIS)

Stankovski, Z.

1994-01-01

The collision probability method in neutron transport, as applied to arbitrary 2-dimensional geometries, like the two dimensional transport module in APOLLO-II is very time consuming. Consequently 3-dimensional extension became prohibitive. Fortunately, this method is very suitable for parallelization. Massively parallel computer architectures, especially MIMD machines, bring a new breath to this method. In this paper we present a CM5 implementation of the collision probability method. Parallelization is applied to the energy groups, using the CMMD massage passing library. In our case we used 32 processors for the standard 99-group APOLLIB-II library. The real advantage of this algorithm will appear in the calculation of the future multigroup library (about 8000 groups) of the SAPHYR project with a massively parallel computer (to the order of hundreds of processors). (author). 4 refs., 4 figs., 3 tabs

Representing and computing regular languages on massively parallel networks

Energy Technology Data Exchange (ETDEWEB)

Miller, M.I.; O' Sullivan, J.A. (Electronic Systems and Research Lab., of Electrical Engineering, Washington Univ., St. Louis, MO (US)); Boysam, B. (Dept. of Electrical, Computer and Systems Engineering, Rensselaer Polytechnic Inst., Troy, NY (US)); Smith, K.R. (Dept. of Electrical Engineering, Southern Illinois Univ., Edwardsville, IL (US))

1991-01-01

This paper proposes a general method for incorporating rule-based constraints corresponding to regular languages into stochastic inference problems, thereby allowing for a unified representation of stochastic and syntactic pattern constraints. The authors' approach first established the formal connection of rules to Chomsky grammars, and generalizes the original work of Shannon on the encoding of rule-based channel sequences to Markov chains of maximum entropy. This maximum entropy probabilistic view leads to Gibb's representations with potentials which have their number of minima growing at precisely the exponential rate that the language of deterministically constrained sequences grow. These representations are coupled to stochastic diffusion algorithms, which sample the language-constrained sequences by visiting the energy minima according to the underlying Gibbs' probability law. The coupling to stochastic search methods yields the all-important practical result that fully parallel stochastic cellular automata may be derived to generate samples from the rule-based constraint sets. The production rules and neighborhood state structure of the language of sequences directly determines the necessary connection structures of the required parallel computing surface. Representations of this type have been mapped to the DAP-510 massively-parallel processor consisting of 1024 mesh-connected bit-serial processing elements for performing automated segmentation of electron-micrograph images.

Development of massively parallel quantum chemistry program SMASH

International Nuclear Information System (INIS)

Ishimura, Kazuya

2015-01-01

A massively parallel program for quantum chemistry calculations SMASH was released under the Apache License 2.0 in September 2014. The SMASH program is written in the Fortran90/95 language with MPI and OpenMP standards for parallelization. Frequently used routines, such as one- and two-electron integral calculations, are modularized to make program developments simple. The speed-up of the B3LYP energy calculation for (C 150 H 30 ) 2 with the cc-pVDZ basis set (4500 basis functions) was 50,499 on 98,304 cores of the K computer

GPAW - massively parallel electronic structure calculations with Python-based software

DEFF Research Database (Denmark)

Enkovaara, Jussi; Romero, Nichols A.; Shende, Sameer

2011-01-01

of the productivity enhancing features together with a good numerical performance. We have used this approach in implementing an electronic structure simulation software GPAW using the combination of Python and C programming languages. While the chosen approach works well in standard workstations and Unix...... popular choice. While dynamic, interpreted languages, such as Python, can increase the effciency of programmer, they cannot compete directly with the raw performance of compiled languages. However, by using an interpreted language together with a compiled language, it is possible to have most...... environments, massively parallel supercomputing systems can present some challenges in porting, debugging and profiling the software. In this paper we describe some details of the implementation and discuss the advantages and challenges of the combined Python/C approach. We show that despite the challenges...

MADmap: A Massively Parallel Maximum-Likelihood Cosmic Microwave Background Map-Maker

Energy Technology Data Exchange (ETDEWEB)

Cantalupo, Christopher; Borrill, Julian; Jaffe, Andrew; Kisner, Theodore; Stompor, Radoslaw

2009-06-09

MADmap is a software application used to produce maximum-likelihood images of the sky from time-ordered data which include correlated noise, such as those gathered by Cosmic Microwave Background (CMB) experiments. It works efficiently on platforms ranging from small workstations to the most massively parallel supercomputers. Map-making is a critical step in the analysis of all CMB data sets, and the maximum-likelihood approach is the most accurate and widely applicable algorithm; however, it is a computationally challenging task. This challenge will only increase with the next generation of ground-based, balloon-borne and satellite CMB polarization experiments. The faintness of the B-mode signal that these experiments seek to measure requires them to gather enormous data sets. MADmap is already being run on up to O(1011) time samples, O(108) pixels and O(104) cores, with ongoing work to scale to the next generation of data sets and supercomputers. We describe MADmap's algorithm based around a preconditioned conjugate gradient solver, fast Fourier transforms and sparse matrix operations. We highlight MADmap's ability to address problems typically encountered in the analysis of realistic CMB data sets and describe its application to simulations of the Planck and EBEX experiments. The massively parallel and distributed implementation is detailed and scaling complexities are given for the resources required. MADmap is capable of analysing the largest data sets now being collected on computing resources currently available, and we argue that, given Moore's Law, MADmap will be capable of reducing the most massive projected data sets.

Increasing phylogenetic resolution at low taxonomic levels using massively parallel sequencing of chloroplast genomes

Directory of Open Access Journals (Sweden)

Cronn Richard

2009-12-01

Full Text Available Abstract Background Molecular evolutionary studies share the common goal of elucidating historical relationships, and the common challenge of adequately sampling taxa and characters. Particularly at low taxonomic levels, recent divergence, rapid radiations, and conservative genome evolution yield limited sequence variation, and dense taxon sampling is often desirable. Recent advances in massively parallel sequencing make it possible to rapidly obtain large amounts of sequence data, and multiplexing makes extensive sampling of megabase sequences feasible. Is it possible to efficiently apply massively parallel sequencing to increase phylogenetic resolution at low taxonomic levels? Results We reconstruct the infrageneric phylogeny of Pinus from 37 nearly-complete chloroplast genomes (average 109 kilobases each of an approximately 120 kilobase genome generated using multiplexed massively parallel sequencing. 30/33 ingroup nodes resolved with ≥ 95% bootstrap support; this is a substantial improvement relative to prior studies, and shows massively parallel sequencing-based strategies can produce sufficient high quality sequence to reach support levels originally proposed for the phylogenetic bootstrap. Resampling simulations show that at least the entire plastome is necessary to fully resolve Pinus, particularly in rapidly radiating clades. Meta-analysis of 99 published infrageneric phylogenies shows that whole plastome analysis should provide similar gains across a range of plant genera. A disproportionate amount of phylogenetic information resides in two loci (ycf1, ycf2, highlighting their unusual evolutionary properties. Conclusion Plastome sequencing is now an efficient option for increasing phylogenetic resolution at lower taxonomic levels in plant phylogenetic and population genetic analyses. With continuing improvements in sequencing capacity, the strategies herein should revolutionize efforts requiring dense taxon and character sampling

Proxy-equation paradigm: A strategy for massively parallel asynchronous computations

Science.gov (United States)

Mittal, Ankita; Girimaji, Sharath

2017-09-01

Massively parallel simulations of transport equation systems call for a paradigm change in algorithm development to achieve efficient scalability. Traditional approaches require time synchronization of processing elements (PEs), which severely restricts scalability. Relaxing synchronization requirement introduces error and slows down convergence. In this paper, we propose and develop a novel "proxy equation" concept for a general transport equation that (i) tolerates asynchrony with minimal added error, (ii) preserves convergence order and thus, (iii) expected to scale efficiently on massively parallel machines. The central idea is to modify a priori the transport equation at the PE boundaries to offset asynchrony errors. Proof-of-concept computations are performed using a one-dimensional advection (convection) diffusion equation. The results demonstrate the promise and advantages of the present strategy.

Comparison of Pre-Analytical FFPE Sample Preparation Methods and Their Impact on Massively Parallel Sequencing in Routine Diagnostics

Science.gov (United States)

Heydt, Carina; Fassunke, Jana; Künstlinger, Helen; Ihle, Michaela Angelika; König, Katharina; Heukamp, Lukas Carl; Schildhaus, Hans-Ulrich; Odenthal, Margarete; Büttner, Reinhard; Merkelbach-Bruse, Sabine

2014-01-01

Over the last years, massively parallel sequencing has rapidly evolved and has now transitioned into molecular pathology routine laboratories. It is an attractive platform for analysing multiple genes at the same time with very little input material. Therefore, the need for high quality DNA obtained from automated DNA extraction systems has increased, especially to those laboratories which are dealing with formalin-fixed paraffin-embedded (FFPE) material and high sample throughput. This study evaluated five automated FFPE DNA extraction systems as well as five DNA quantification systems using the three most common techniques, UV spectrophotometry, fluorescent dye-based quantification and quantitative PCR, on 26 FFPE tissue samples. Additionally, the effects on downstream applications were analysed to find the most suitable pre-analytical methods for massively parallel sequencing in routine diagnostics. The results revealed that the Maxwell 16 from Promega (Mannheim, Germany) seems to be the superior system for DNA extraction from FFPE material. The extracts had a 1.3–24.6-fold higher DNA concentration in comparison to the other extraction systems, a higher quality and were most suitable for downstream applications. The comparison of the five quantification methods showed intermethod variations but all methods could be used to estimate the right amount for PCR amplification and for massively parallel sequencing. Interestingly, the best results in massively parallel sequencing were obtained with a DNA input of 15 ng determined by the NanoDrop 2000c spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). No difference could be detected in mutation analysis based on the results of the quantification methods. These findings emphasise, that it is particularly important to choose the most reliable and constant DNA extraction system, especially when using small biopsies and low elution volumes, and that all common DNA quantification techniques can be used for

Comparison of pre-analytical FFPE sample preparation methods and their impact on massively parallel sequencing in routine diagnostics.

Directory of Open Access Journals (Sweden)

Carina Heydt

Full Text Available Over the last years, massively parallel sequencing has rapidly evolved and has now transitioned into molecular pathology routine laboratories. It is an attractive platform for analysing multiple genes at the same time with very little input material. Therefore, the need for high quality DNA obtained from automated DNA extraction systems has increased, especially to those laboratories which are dealing with formalin-fixed paraffin-embedded (FFPE material and high sample throughput. This study evaluated five automated FFPE DNA extraction systems as well as five DNA quantification systems using the three most common techniques, UV spectrophotometry, fluorescent dye-based quantification and quantitative PCR, on 26 FFPE tissue samples. Additionally, the effects on downstream applications were analysed to find the most suitable pre-analytical methods for massively parallel sequencing in routine diagnostics. The results revealed that the Maxwell 16 from Promega (Mannheim, Germany seems to be the superior system for DNA extraction from FFPE material. The extracts had a 1.3-24.6-fold higher DNA concentration in comparison to the other extraction systems, a higher quality and were most suitable for downstream applications. The comparison of the five quantification methods showed intermethod variations but all methods could be used to estimate the right amount for PCR amplification and for massively parallel sequencing. Interestingly, the best results in massively parallel sequencing were obtained with a DNA input of 15 ng determined by the NanoDrop 2000c spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA. No difference could be detected in mutation analysis based on the results of the quantification methods. These findings emphasise, that it is particularly important to choose the most reliable and constant DNA extraction system, especially when using small biopsies and low elution volumes, and that all common DNA quantification techniques can

Development of massively parallel quantum chemistry program SMASH

Energy Technology Data Exchange (ETDEWEB)

Ishimura, Kazuya [Department of Theoretical and Computational Molecular Science, Institute for Molecular Science 38 Nishigo-Naka, Myodaiji, Okazaki, Aichi 444-8585 (Japan)

2015-12-31

A massively parallel program for quantum chemistry calculations SMASH was released under the Apache License 2.0 in September 2014. The SMASH program is written in the Fortran90/95 language with MPI and OpenMP standards for parallelization. Frequently used routines, such as one- and two-electron integral calculations, are modularized to make program developments simple. The speed-up of the B3LYP energy calculation for (C{sub 150}H{sub 30}){sub 2} with the cc-pVDZ basis set (4500 basis functions) was 50,499 on 98,304 cores of the K computer.

Intelligent trigger by massively parallel processors for high energy physics experiments

International Nuclear Information System (INIS)

Rohrbach, F.; Vesztergombi, G.

1992-01-01

The CERN-MPPC collaboration concentrates its effort on the development of machines based on massive parallelism with thousands of integrated processing elements, arranged in a string. Seven applications are under detailed studies within the collaboration: three for LHC, one for SSC, two for fixed target high energy physics at CERN and one for HDTV. Preliminary results are presented. They show that the objectives should be reached with the use of the ASP architecture. (author)

Routing performance analysis and optimization within a massively parallel computer

Science.gov (United States)

Archer, Charles Jens; Peters, Amanda; Pinnow, Kurt Walter; Swartz, Brent Allen

2013-04-16

An apparatus, program product and method optimize the operation of a massively parallel computer system by, in part, receiving actual performance data concerning an application executed by the plurality of interconnected nodes, and analyzing the actual performance data to identify an actual performance pattern. A desired performance pattern may be determined for the application, and an algorithm may be selected from among a plurality of algorithms stored within a memory, the algorithm being configured to achieve the desired performance pattern based on the actual performance data.

Massively parallel Fokker-Planck calculations

International Nuclear Information System (INIS)

Mirin, A.A.

1990-01-01

This paper reports that the Fokker-Planck package FPPAC, which solves the complete nonlinear multispecies Fokker-Planck collision operator for a plasma in two-dimensional velocity space, has been rewritten for the Connection Machine 2. This has involved allocation of variables either to the front end or the CM2, minimization of data flow, and replacement of Cray-optimized algorithms with ones suitable for a massively parallel architecture. Calculations have been carried out on various Connection Machines throughout the country. Results and timings on these machines have been compared to each other and to those on the static memory Cray-2. For large problem size, the Connection Machine 2 is found to be cost-efficient

Optimization of multi-phase compressible lattice Boltzmann codes on massively parallel multi-core systems

NARCIS (Netherlands)

Biferale, L.; Mantovani, F.; Pivanti, M.; Pozzati, F.; Sbragaglia, M.; Schifano, S.F.; Toschi, F.; Tripiccione, R.

2011-01-01

We develop a Lattice Boltzmann code for computational fluid-dynamics and optimize it for massively parallel systems based on multi-core processors. Our code describes 2D multi-phase compressible flows. We analyze the performance bottlenecks that we find as we gradually expose a larger fraction of

Performance of Air Pollution Models on Massively Parallel Computers

DEFF Research Database (Denmark)

Brown, John; Hansen, Per Christian; Wasniewski, Jerzy

1996-01-01

To compare the performance and use of three massively parallel SIMD computers, we implemented a large air pollution model on the computers. Using a realistic large-scale model, we gain detailed insight about the performance of the three computers when used to solve large-scale scientific problems...

Massive Parallelism of Monte-Carlo Simulation on Low-End Hardware using Graphic Processing Units

International Nuclear Information System (INIS)

Mburu, Joe Mwangi; Hah, Chang Joo Hah

2014-01-01

Within the past decade, research has been done on utilizing GPU massive parallelization in core simulation with impressive results but unfortunately, not much commercial application has been done in the nuclear field especially in reactor core simulation. The purpose of this paper is to give an introductory concept on the topic and illustrate the potential of exploiting the massive parallel nature of GPU computing on a simple monte-carlo simulation with very minimal hardware specifications. To do a comparative analysis, a simple two dimension monte-carlo simulation is implemented for both the CPU and GPU in order to evaluate performance gain based on the computing devices. The heterogeneous platform utilized in this analysis is done on a slow notebook with only 1GHz processor. The end results are quite surprising whereby high speedups obtained are almost a factor of 10. In this work, we have utilized heterogeneous computing in a GPU-based approach in applying potential high arithmetic intensive calculation. By applying a complex monte-carlo simulation on GPU platform, we have speed up the computational process by almost a factor of 10 based on one million neutrons. This shows how easy, cheap and efficient it is in using GPU in accelerating scientific computing and the results should encourage in exploring further this avenue especially in nuclear reactor physics simulation where deterministic and stochastic calculations are quite favourable in parallelization

Massive Parallelism of Monte-Carlo Simulation on Low-End Hardware using Graphic Processing Units

Energy Technology Data Exchange (ETDEWEB)

Mburu, Joe Mwangi; Hah, Chang Joo Hah [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)

2014-05-15

Within the past decade, research has been done on utilizing GPU massive parallelization in core simulation with impressive results but unfortunately, not much commercial application has been done in the nuclear field especially in reactor core simulation. The purpose of this paper is to give an introductory concept on the topic and illustrate the potential of exploiting the massive parallel nature of GPU computing on a simple monte-carlo simulation with very minimal hardware specifications. To do a comparative analysis, a simple two dimension monte-carlo simulation is implemented for both the CPU and GPU in order to evaluate performance gain based on the computing devices. The heterogeneous platform utilized in this analysis is done on a slow notebook with only 1GHz processor. The end results are quite surprising whereby high speedups obtained are almost a factor of 10. In this work, we have utilized heterogeneous computing in a GPU-based approach in applying potential high arithmetic intensive calculation. By applying a complex monte-carlo simulation on GPU platform, we have speed up the computational process by almost a factor of 10 based on one million neutrons. This shows how easy, cheap and efficient it is in using GPU in accelerating scientific computing and the results should encourage in exploring further this avenue especially in nuclear reactor physics simulation where deterministic and stochastic calculations are quite favourable in parallelization.

Massively Parallel Computing at Sandia and Its Application to National Defense

National Research Council Canada - National Science Library

Dosanjh, Sudip

1991-01-01

Two years ago, researchers at Sandia National Laboratories showed that a massively parallel computer with 1024 processors could solve scientific problems more than 1000 times faster than a single processor...

Massively-parallel best subset selection for ordinary least-squares regression

DEFF Research Database (Denmark)

Gieseke, Fabian; Polsterer, Kai Lars; Mahabal, Ashish

2017-01-01

Selecting an optimal subset of k out of d features for linear regression models given n training instances is often considered intractable for feature spaces with hundreds or thousands of dimensions. We propose an efficient massively-parallel implementation for selecting such optimal feature...

Massive Asynchronous Parallelization of Sparse Matrix Factorizations

Energy Technology Data Exchange (ETDEWEB)

Chow, Edmond [Georgia Inst. of Technology, Atlanta, GA (United States)

2018-01-08

Solving sparse problems is at the core of many DOE computational science applications. We focus on the challenge of developing sparse algorithms that can fully exploit the parallelism in extreme-scale computing systems, in particular systems with massive numbers of cores per node. Our approach is to express a sparse matrix factorization as a large number of bilinear constraint equations, and then solving these equations via an asynchronous iterative method. The unknowns in these equations are the matrix entries of the factorization that is desired.

Implementation of PHENIX trigger algorithms on massively parallel computers

International Nuclear Information System (INIS)

Petridis, A.N.; Wohn, F.K.

1995-01-01

The event selection requirements of contemporary high energy and nuclear physics experiments are met by the introduction of on-line trigger algorithms which identify potentially interesting events and reduce the data acquisition rate to levels that are manageable by the electronics. Such algorithms being parallel in nature can be simulated off-line using massively parallel computers. The PHENIX experiment intends to investigate the possible existence of a new phase of matter called the quark gluon plasma which has been theorized to have existed in very early stages of the evolution of the universe by studying collisions of heavy nuclei at ultra-relativistic energies. Such interactions can also reveal important information regarding the structure of the nucleus and mandate a thorough investigation of the simpler proton-nucleus collisions at the same energies. The complexity of PHENIX events and the need to analyze and also simulate them at rates similar to the data collection ones imposes enormous computation demands. This work is a first effort to implement PHENIX trigger algorithms on parallel computers and to study the feasibility of using such machines to run the complex programs necessary for the simulation of the PHENIX detector response. Fine and coarse grain approaches have been studied and evaluated. Depending on the application the performance of a massively parallel computer can be much better or much worse than that of a serial workstation. A comparison between single instruction and multiple instruction computers is also made and possible applications of the single instruction machines to high energy and nuclear physics experiments are outlined. copyright 1995 American Institute of Physics

PUMA: An Operating System for Massively Parallel Systems

Directory of Open Access Journals (Sweden)

Stephen R. Wheat

1994-01-01

Full Text Available This article presents an overview of PUMA (Performance-oriented, User-managed Messaging Architecture, a message-passing kernel for massively parallel systems. Message passing in PUMA is based on portals – an opening in the address space of an application process. Once an application process has established a portal, other processes can write values into the portal using a simple send operation. Because messages are written directly into the address space of the receiving process, there is no need to buffer messages in the PUMA kernel and later copy them into the applications address space. PUMA consists of two components: the quintessential kernel (Q-Kernel and the process control thread (PCT. Although the PCT provides management decisions, the Q-Kernel controls access and implements the policies specified by the PCT.

Massively Parallel Sort-Merge Joins in Main Memory Multi-Core Database Systems

OpenAIRE

Martina-Cezara Albutiu, Alfons Kemper, Thomas Neumann

2012-01-01

Two emerging hardware trends will dominate the database system technology in the near future: increasing main memory capacities of several TB per server and massively parallel multi-core processing. Many algorithmic and control techniques in current database technology were devised for disk-based systems where I/O dominated the performance. In this work we take a new look at the well-known sort-merge join which, so far, has not been in the focus of research ...

Massive hybrid parallelism for fully implicit multiphysics

International Nuclear Information System (INIS)

Gaston, D. R.; Permann, C. J.; Andrs, D.; Peterson, J. W.

2013-01-01

As hardware advances continue to modify the supercomputing landscape, traditional scientific software development practices will become more outdated, ineffective, and inefficient. The process of rewriting/retooling existing software for new architectures is a Sisyphean task, and results in substantial hours of development time, effort, and money. Software libraries which provide an abstraction of the resources provided by such architectures are therefore essential if the computational engineering and science communities are to continue to flourish in this modern computing environment. The Multiphysics Object Oriented Simulation Environment (MOOSE) framework enables complex multiphysics analysis tools to be built rapidly by scientists, engineers, and domain specialists, while also allowing them to both take advantage of current HPC architectures, and efficiently prepare for future supercomputer designs. MOOSE employs a hybrid shared-memory and distributed-memory parallel model and provides a complete and consistent interface for creating multiphysics analysis tools. In this paper, a brief discussion of the mathematical algorithms underlying the framework and the internal object-oriented hybrid parallel design are given. Representative massively parallel results from several applications areas are presented, and a brief discussion of future areas of research for the framework are provided. (authors)

Massive hybrid parallelism for fully implicit multiphysics

Energy Technology Data Exchange (ETDEWEB)

Gaston, D. R.; Permann, C. J.; Andrs, D.; Peterson, J. W. [Idaho National Laboratory, 2525 N. Fremont Ave., Idaho Falls, ID 83415 (United States)

2013-07-01

As hardware advances continue to modify the supercomputing landscape, traditional scientific software development practices will become more outdated, ineffective, and inefficient. The process of rewriting/retooling existing software for new architectures is a Sisyphean task, and results in substantial hours of development time, effort, and money. Software libraries which provide an abstraction of the resources provided by such architectures are therefore essential if the computational engineering and science communities are to continue to flourish in this modern computing environment. The Multiphysics Object Oriented Simulation Environment (MOOSE) framework enables complex multiphysics analysis tools to be built rapidly by scientists, engineers, and domain specialists, while also allowing them to both take advantage of current HPC architectures, and efficiently prepare for future supercomputer designs. MOOSE employs a hybrid shared-memory and distributed-memory parallel model and provides a complete and consistent interface for creating multiphysics analysis tools. In this paper, a brief discussion of the mathematical algorithms underlying the framework and the internal object-oriented hybrid parallel design are given. Representative massively parallel results from several applications areas are presented, and a brief discussion of future areas of research for the framework are provided. (authors)

MASSIVE HYBRID PARALLELISM FOR FULLY IMPLICIT MULTIPHYSICS

Energy Technology Data Exchange (ETDEWEB)

Cody J. Permann; David Andrs; John W. Peterson; Derek R. Gaston

2013-05-01

As hardware advances continue to modify the supercomputing landscape, traditional scientific software development practices will become more outdated, ineffective, and inefficient. The process of rewriting/retooling existing software for new architectures is a Sisyphean task, and results in substantial hours of development time, effort, and money. Software libraries which provide an abstraction of the resources provided by such architectures are therefore essential if the computational engineering and science communities are to continue to flourish in this modern computing environment. The Multiphysics Object Oriented Simulation Environment (MOOSE) framework enables complex multiphysics analysis tools to be built rapidly by scientists, engineers, and domain specialists, while also allowing them to both take advantage of current HPC architectures, and efficiently prepare for future supercomputer designs. MOOSE employs a hybrid shared-memory and distributed-memory parallel model and provides a complete and consistent interface for creating multiphysics analysis tools. In this paper, a brief discussion of the mathematical algorithms underlying the framework and the internal object-oriented hybrid parallel design are given. Representative massively parallel results from several applications areas are presented, and a brief discussion of future areas of research for the framework are provided.

Massively parallel Monte Carlo for many-particle simulations on GPUs

Energy Technology Data Exchange (ETDEWEB)

Anderson, Joshua A.; Jankowski, Eric [Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109 (United States); Grubb, Thomas L. [Department of Materials Science and Engineering, University of Michigan, Ann Arbor, MI 48109 (United States); Engel, Michael [Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109 (United States); Glotzer, Sharon C., E-mail: sglotzer@umich.edu [Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109 (United States); Department of Materials Science and Engineering, University of Michigan, Ann Arbor, MI 48109 (United States)

2013-12-01

Current trends in parallel processors call for the design of efficient massively parallel algorithms for scientific computing. Parallel algorithms for Monte Carlo simulations of thermodynamic ensembles of particles have received little attention because of the inherent serial nature of the statistical sampling. In this paper, we present a massively parallel method that obeys detailed balance and implement it for a system of hard disks on the GPU. We reproduce results of serial high-precision Monte Carlo runs to verify the method. This is a good test case because the hard disk equation of state over the range where the liquid transforms into the solid is particularly sensitive to small deviations away from the balance conditions. On a Tesla K20, our GPU implementation executes over one billion trial moves per second, which is 148 times faster than on a single Intel Xeon E5540 CPU core, enables 27 times better performance per dollar, and cuts energy usage by a factor of 13. With this improved performance we are able to calculate the equation of state for systems of up to one million hard disks. These large system sizes are required in order to probe the nature of the melting transition, which has been debated for the last forty years. In this paper we present the details of our computational method, and discuss the thermodynamics of hard disks separately in a companion paper.

Massively Parallel, Molecular Analysis Platform Developed Using a CMOS Integrated Circuit With Biological Nanopores

Science.gov (United States)

Roever, Stefan

2012-01-01

A massively parallel, low cost molecular analysis platform will dramatically change the nature of protein, molecular and genomics research, DNA sequencing, and ultimately, molecular diagnostics. An integrated circuit (IC) with 264 sensors was fabricated using standard CMOS semiconductor processing technology. Each of these sensors is individually controlled with precision analog circuitry and is capable of single molecule measurements. Under electronic and software control, the IC was used to demonstrate the feasibility of creating and detecting lipid bilayers and biological nanopores using wild type α-hemolysin. The ability to dynamically create bilayers over each of the sensors will greatly accelerate pore development and pore mutation analysis. In addition, the noise performance of the IC was measured to be 30fA(rms). With this noise performance, single base detection of DNA was demonstrated using α-hemolysin. The data shows that a single molecule, electrical detection platform using biological nanopores can be operationalized and can ultimately scale to millions of sensors. Such a massively parallel platform will revolutionize molecular analysis and will completely change the field of molecular diagnostics in the future.

ARTS - adaptive runtime system for massively parallel systems. Final report; ARTS - optimale Ausfuehrungsunterstuetzung fuer komplexe Anwendungen auf massiv parallelen Systemen. Teilprojekt: Parallele Stroemungsmechanik. Abschlussbericht

Energy Technology Data Exchange (ETDEWEB)

Gentzsch, W.; Ferstl, F.; Paap, H.G.; Riedel, E.

1998-03-20

In the ARTS project, system software has been developed to support smog and fluid dynamic applications on massively parallel systems. The aim is to implement and test specific software structures within an adaptive run-time system to separate the parallel core algorithms of the applications from the platform independent runtime aspects. Only slight modifications is existing Fortran and C code are necessary to integrate the application code into the new object oriented parallel integrated ARTS framework. The OO-design offers easy control, re-use and adaptation of the system services, resulting in a dramatic decrease in development time of the application and in ease of maintainability of the application software in the future. (orig.) [Deutsch] Im Projekt ARTS wird Basissoftware zur Unterstuetzung von Anwendungen aus den Bereichen Smoganalyse und Stroemungsmechanik auf massiv parallelen Systemen entwickelt und optimiert. Im Vordergrund steht die Erprobung geeigneter Strukturen, um systemnahe Funktionalitaeten in einer Laufzeitumgebung anzusiedeln und dadurch die parallelen Kernalgorithmen der Anwendungsprogramme von den plattformunabhaengigen Laufzeitaspekten zu trennen. Es handelt sich dabei um herkoemmlich strukturierten Fortran-Code, der unter minimalen Aenderungen auch weiterhin nutzbar sein muss, sowie um objektbasiert entworfenen C-Code, der die volle Funktionalitaet der ARTS-Plattform ausnutzen kann. Ein objektorientiertes Design erlaubt eine einfache Kontrolle, Wiederverwendung und Adaption der vom System vorgegebenen Basisdienste. Daraus resultiert ein deutlich reduzierter Entwicklungs- und Laufzeitaufwand fuer die Anwendung. ARTS schafft eine integrierende Plattform, die moderne Technologien aus dem Bereich objektorientierter Laufzeitsysteme mit praxisrelevanten Anforderungen aus dem Bereich des wissenschaftlichen Hoechstleistungsrechnens kombiniert. (orig.)

Quantification of massively parallel sequencing libraries - a comparative study of eight methods

DEFF Research Database (Denmark)

Hussing, Christian; Kampmann, Marie-Louise; Mogensen, Helle Smidt

2018-01-01

Quantification of massively parallel sequencing libraries is important for acquisition of monoclonal beads or clusters prior to clonal amplification and to avoid large variations in library coverage when multiple samples are included in one sequencing analysis. No gold standard for quantification...... estimates followed by Qubit and electrophoresis-based instruments (Bioanalyzer, TapeStation, GX Touch, and Fragment Analyzer), while SYBR Green and TaqMan based qPCR assays gave the lowest estimates. qPCR gave more accurate predictions of sequencing coverage than Qubit and TapeStation did. Costs, time......-consumption, workflow simplicity, and ability to quantify multiple samples are discussed. Technical specifications, advantages, and disadvantages of the various methods are pointed out....

Scalable Parallel Distributed Coprocessor System for Graph Searching Problems with Massive Data

Directory of Open Access Journals (Sweden)

Wanrong Huang

2017-01-01

Full Text Available The Internet applications, such as network searching, electronic commerce, and modern medical applications, produce and process massive data. Considerable data parallelism exists in computation processes of data-intensive applications. A traversal algorithm, breadth-first search (BFS, is fundamental in many graph processing applications and metrics when a graph grows in scale. A variety of scientific programming methods have been proposed for accelerating and parallelizing BFS because of the poor temporal and spatial locality caused by inherent irregular memory access patterns. However, new parallel hardware could provide better improvement for scientific methods. To address small-world graph problems, we propose a scalable and novel field-programmable gate array-based heterogeneous multicore system for scientific programming. The core is multithread for streaming processing. And the communication network InfiniBand is adopted for scalability. We design a binary search algorithm to address mapping to unify all processor addresses. Within the limits permitted by the Graph500 test bench after 1D parallel hybrid BFS algorithm testing, our 8-core and 8-thread-per-core system achieved superior performance and efficiency compared with the prior work under the same degree of parallelism. Our system is efficient not as a special acceleration unit but as a processor platform that deals with graph searching applications.

Climate models on massively parallel computers

International Nuclear Information System (INIS)

Vitart, F.; Rouvillois, P.

1993-01-01

First results got on massively parallel computers (Multiple Instruction Multiple Data and Simple Instruction Multiple Data) allow to consider building of coupled models with high resolutions. This would make possible simulation of thermoaline circulation and other interaction phenomena between atmosphere and ocean. The increasing of computers powers, and then the improvement of resolution will go us to revise our approximations. Then hydrostatic approximation (in ocean circulation) will not be valid when the grid mesh will be of a dimension lower than a few kilometers: We shall have to find other models. The expert appraisement got in numerical analysis at the Center of Limeil-Valenton (CEL-V) will be used again to imagine global models taking in account atmosphere, ocean, ice floe and biosphere, allowing climate simulation until a regional scale

Massively parallel data processing for quantitative total flow imaging with optical coherence microscopy and tomography

Science.gov (United States)

Sylwestrzak, Marcin; Szlag, Daniel; Marchand, Paul J.; Kumar, Ashwin S.; Lasser, Theo

2017-08-01

We present an application of massively parallel processing of quantitative flow measurements data acquired using spectral optical coherence microscopy (SOCM). The need for massive signal processing of these particular datasets has been a major hurdle for many applications based on SOCM. In view of this difficulty, we implemented and adapted quantitative total flow estimation algorithms on graphics processing units (GPU) and achieved a 150 fold reduction in processing time when compared to a former CPU implementation. As SOCM constitutes the microscopy counterpart to spectral optical coherence tomography (SOCT), the developed processing procedure can be applied to both imaging modalities. We present the developed DLL library integrated in MATLAB (with an example) and have included the source code for adaptations and future improvements. Catalogue identifier: AFBT_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AFBT_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU GPLv3 No. of lines in distributed program, including test data, etc.: 913552 No. of bytes in distributed program, including test data, etc.: 270876249 Distribution format: tar.gz Programming language: CUDA/C, MATLAB. Computer: Intel x64 CPU, GPU supporting CUDA technology. Operating system: 64-bit Windows 7 Professional. Has the code been vectorized or parallelized?: Yes, CPU code has been vectorized in MATLAB, CUDA code has been parallelized. RAM: Dependent on users parameters, typically between several gigabytes and several tens of gigabytes Classification: 6.5, 18. Nature of problem: Speed up of data processing in optical coherence microscopy Solution method: Utilization of GPU for massively parallel data processing Additional comments: Compiled DLL library with source code and documentation, example of utilization (MATLAB script with raw data) Running time: 1,8 s for one B-scan (150 × faster in comparison to the CPU

Visualizing Network Traffic to Understand the Performance of Massively Parallel Simulations

KAUST Repository

Landge, A. G.

2012-12-01

The performance of massively parallel applications is often heavily impacted by the cost of communication among compute nodes. However, determining how to best use the network is a formidable task, made challenging by the ever increasing size and complexity of modern supercomputers. This paper applies visualization techniques to aid parallel application developers in understanding the network activity by enabling a detailed exploration of the flow of packets through the hardware interconnect. In order to visualize this large and complex data, we employ two linked views of the hardware network. The first is a 2D view, that represents the network structure as one of several simplified planar projections. This view is designed to allow a user to easily identify trends and patterns in the network traffic. The second is a 3D view that augments the 2D view by preserving the physical network topology and providing a context that is familiar to the application developers. Using the massively parallel multi-physics code pF3D as a case study, we demonstrate that our tool provides valuable insight that we use to explain and optimize pF3D-s performance on an IBM Blue Gene/P system. © 1995-2012 IEEE.

Massively Parallel Dimension Independent Adaptive Metropolis

KAUST Repository

Chen, Yuxin

2015-05-14

This work considers black-box Bayesian inference over high-dimensional parameter spaces. The well-known and widely respected adaptive Metropolis (AM) algorithm is extended herein to asymptotically scale uniformly with respect to the underlying parameter dimension, by respecting the variance, for Gaussian targets. The result- ing algorithm, referred to as the dimension-independent adaptive Metropolis (DIAM) algorithm, also shows improved performance with respect to adaptive Metropolis on non-Gaussian targets. This algorithm is further improved, and the possibility of probing high-dimensional targets is enabled, via GPU-accelerated numerical libraries and periodically synchronized concurrent chains (justified a posteriori). Asymptoti- cally in dimension, this massively parallel dimension-independent adaptive Metropolis (MPDIAM) GPU implementation exhibits a factor of four improvement versus the CPU-based Intel MKL version alone, which is itself already a factor of three improve- ment versus the serial version. The scaling to multiple CPUs and GPUs exhibits a form of strong scaling in terms of the time necessary to reach a certain convergence criterion, through a combination of longer time per sample batch (weak scaling) and yet fewer necessary samples to convergence. This is illustrated by e ciently sampling from several Gaussian and non-Gaussian targets for dimension d 1000.

Reduced complexity and latency for a massive MIMO system using a parallel detection algorithm

Directory of Open Access Journals (Sweden)

Shoichi Higuchi

2017-09-01

Full Text Available In recent years, massive MIMO systems have been widely researched to realize high-speed data transmission. Since massive MIMO systems use a large number of antennas, these systems require huge complexity to detect the signal. In this paper, we propose a novel detection method for massive MIMO using parallel detection with maximum likelihood detection with QR decomposition and M-algorithm (QRM-MLD to reduce the complexity and latency. The proposed scheme obtains an R matrix after permutation of an H matrix and QR decomposition. The R matrix is also eliminated using a Gauss–Jordan elimination method. By using a modified R matrix, the proposed method can detect the transmitted signal using parallel detection. From the simulation results, the proposed scheme can achieve a reduced complexity and latency with a little degradation of the bit error rate (BER performance compared with the conventional method.

GRay: A MASSIVELY PARALLEL GPU-BASED CODE FOR RAY TRACING IN RELATIVISTIC SPACETIMES

Energy Technology Data Exchange (ETDEWEB)

Chan, Chi-kwan; Psaltis, Dimitrios; Özel, Feryal [Department of Astronomy, University of Arizona, 933 N. Cherry Ave., Tucson, AZ 85721 (United States)

2013-11-01

We introduce GRay, a massively parallel integrator designed to trace the trajectories of billions of photons in a curved spacetime. This graphics-processing-unit (GPU)-based integrator employs the stream processing paradigm, is implemented in CUDA C/C++, and runs on nVidia graphics cards. The peak performance of GRay using single-precision floating-point arithmetic on a single GPU exceeds 300 GFLOP (or 1 ns per photon per time step). For a realistic problem, where the peak performance cannot be reached, GRay is two orders of magnitude faster than existing central-processing-unit-based ray-tracing codes. This performance enhancement allows more effective searches of large parameter spaces when comparing theoretical predictions of images, spectra, and light curves from the vicinities of compact objects to observations. GRay can also perform on-the-fly ray tracing within general relativistic magnetohydrodynamic algorithms that simulate accretion flows around compact objects. Making use of this algorithm, we calculate the properties of the shadows of Kerr black holes and the photon rings that surround them. We also provide accurate fitting formulae of their dependencies on black hole spin and observer inclination, which can be used to interpret upcoming observations of the black holes at the center of the Milky Way, as well as M87, with the Event Horizon Telescope.

Design and performance characterization of electronic structure calculations on massively parallel supercomputers

DEFF Research Database (Denmark)

Romero, N. A.; Glinsvad, Christian; Larsen, Ask Hjorth

2013-01-01

Density function theory (DFT) is the most widely employed electronic structure method because of its favorable scaling with system size and accuracy for a broad range of molecular and condensed-phase systems. The advent of massively parallel supercomputers has enhanced the scientific community...

Image processing with massively parallel computer Quadrics Q1

International Nuclear Information System (INIS)

Della Rocca, A.B.; La Porta, L.; Ferriani, S.

1995-05-01

Aimed to evaluate the image processing capabilities of the massively parallel computer Quadrics Q1, a convolution algorithm that has been implemented is described in this report. At first the discrete convolution mathematical definition is recalled together with the main Q1 h/w and s/w features. Then the different codification forms of the algorythm are described and the Q1 performances are compared with those obtained by different computers. Finally, the conclusions report on main results and suggestions

Application of Massively Parallel Sequencing in the Clinical Diagnostic Testing of Inherited Cardiac Conditions

Directory of Open Access Journals (Sweden)

Ivone U. S. Leong

2014-06-01

Full Text Available Sudden cardiac death in people between the ages of 1–40 years is a devastating event and is frequently caused by several heritable cardiac disorders. These disorders include cardiac ion channelopathies, such as long QT syndrome, catecholaminergic polymorphic ventricular tachycardia and Brugada syndrome and cardiomyopathies, such as hypertrophic cardiomyopathy and arrhythmogenic right ventricular cardiomyopathy. Through careful molecular genetic evaluation of DNA from sudden death victims, the causative gene mutation can be uncovered, and the rest of the family can be screened and preventative measures implemented in at-risk individuals. The current screening approach in most diagnostic laboratories uses Sanger-based sequencing; however, this method is time consuming and labour intensive. The development of massively parallel sequencing has made it possible to produce millions of sequence reads simultaneously and is potentially an ideal approach to screen for mutations in genes that are associated with sudden cardiac death. This approach offers mutation screening at reduced cost and turnaround time. Here, we will review the current commercially available enrichment kits, massively parallel sequencing (MPS platforms, downstream data analysis and its application to sudden cardiac death in a diagnostic environment.

Convergence analysis of a class of massively parallel direction splitting algorithms for the Navier-Stokes equations in simple domains

KAUST Repository

Guermond, Jean-Luc; Minev, Peter D.; Salgado, Abner J.

2012-01-01

We provide a convergence analysis for a new fractional timestepping technique for the incompressible Navier-Stokes equations based on direction splitting. This new technique is of linear complexity, unconditionally stable and convergent, and suitable for massive parallelization. © 2012 American Mathematical Society.

cellGPU: Massively parallel simulations of dynamic vertex models

Science.gov (United States)

Sussman, Daniel M.

2017-10-01

Vertex models represent confluent tissue by polygonal or polyhedral tilings of space, with the individual cells interacting via force laws that depend on both the geometry of the cells and the topology of the tessellation. This dependence on the connectivity of the cellular network introduces several complications to performing molecular-dynamics-like simulations of vertex models, and in particular makes parallelizing the simulations difficult. cellGPU addresses this difficulty and lays the foundation for massively parallelized, GPU-based simulations of these models. This article discusses its implementation for a pair of two-dimensional models, and compares the typical performance that can be expected between running cellGPU entirely on the CPU versus its performance when running on a range of commercial and server-grade graphics cards. By implementing the calculation of topological changes and forces on cells in a highly parallelizable fashion, cellGPU enables researchers to simulate time- and length-scales previously inaccessible via existing single-threaded CPU implementations. Program Files doi:http://dx.doi.org/10.17632/6j2cj29t3r.1 Licensing provisions: MIT Programming language: CUDA/C++ Nature of problem: Simulations of off-lattice "vertex models" of cells, in which the interaction forces depend on both the geometry and the topology of the cellular aggregate. Solution method: Highly parallelized GPU-accelerated dynamical simulations in which the force calculations and the topological features can be handled on either the CPU or GPU. Additional comments: The code is hosted at https://gitlab.com/dmsussman/cellGPU, with documentation additionally maintained at http://dmsussman.gitlab.io/cellGPUdocumentation

Implementation of a Monte Carlo algorithm for neutron transport on a massively parallel SIMD machine

International Nuclear Information System (INIS)

Baker, R.S.

1992-01-01

We present some results from the recent adaptation of a vectorized Monte Carlo algorithm to a massively parallel architecture. The performance of the algorithm on a single processor Cray Y-MP and a Thinking Machine Corporations CM-2 and CM-200 is compared for several test problems. The results show that significant speedups are obtainable for vectorized Monte Carlo algorithms on massively parallel machines, even when the algorithms are applied to realistic problems which require extensive variance reduction. However, the architecture of the Connection Machine does place some limitations on the regime in which the Monte Carlo algorithm may be expected to perform well

Implementation of a Monte Carlo algorithm for neutron transport on a massively parallel SIMD machine

International Nuclear Information System (INIS)

Baker, R.S.

1993-01-01

We present some results from the recent adaptation of a vectorized Monte Carlo algorithm to a massively parallel architecture. The performance of the algorithm on a single processor Cray Y-MP and a Thinking Machine Corporations CM-2 and CM-200 is compared for several test problems. The results show that significant speedups are obtainable for vectorized Monte Carlo algorithms on massively parallel machines, even when the algorithms are applied to realistic problems which require extensive variance reduction. However, the architecture of the Connection Machine does place some limitations on the regime in which the Monte Carlo algorithm may be expected to perform well. (orig.)

ASSET: Analysis of Sequences of Synchronous Events in Massively Parallel Spike Trains

Science.gov (United States)

Canova, Carlos; Denker, Michael; Gerstein, George; Helias, Moritz

2016-01-01

With the ability to observe the activity from large numbers of neurons simultaneously using modern recording technologies, the chance to identify sub-networks involved in coordinated processing increases. Sequences of synchronous spike events (SSEs) constitute one type of such coordinated spiking that propagates activity in a temporally precise manner. The synfire chain was proposed as one potential model for such network processing. Previous work introduced a method for visualization of SSEs in massively parallel spike trains, based on an intersection matrix that contains in each entry the degree of overlap of active neurons in two corresponding time bins. Repeated SSEs are reflected in the matrix as diagonal structures of high overlap values. The method as such, however, leaves the task of identifying these diagonal structures to visual inspection rather than to a quantitative analysis. Here we present ASSET (Analysis of Sequences of Synchronous EvenTs), an improved, fully automated method which determines diagonal structures in the intersection matrix by a robust mathematical procedure. The method consists of a sequence of steps that i) assess which entries in the matrix potentially belong to a diagonal structure, ii) cluster these entries into individual diagonal structures and iii) determine the neurons composing the associated SSEs. We employ parallel point processes generated by stochastic simulations as test data to demonstrate the performance of the method under a wide range of realistic scenarios, including different types of non-stationarity of the spiking activity and different correlation structures. Finally, the ability of the method to discover SSEs is demonstrated on complex data from large network simulations with embedded synfire chains. Thus, ASSET represents an effective and efficient tool to analyze massively parallel spike data for temporal sequences of synchronous activity. PMID:27420734

Simultaneous digital quantification and fluorescence-based size characterization of massively parallel sequencing libraries.

Science.gov (United States)

Laurie, Matthew T; Bertout, Jessica A; Taylor, Sean D; Burton, Joshua N; Shendure, Jay A; Bielas, Jason H

2013-08-01

Due to the high cost of failed runs and suboptimal data yields, quantification and determination of fragment size range are crucial steps in the library preparation process for massively parallel sequencing (or next-generation sequencing). Current library quality control methods commonly involve quantification using real-time quantitative PCR and size determination using gel or capillary electrophoresis. These methods are laborious and subject to a number of significant limitations that can make library calibration unreliable. Herein, we propose and test an alternative method for quality control of sequencing libraries using droplet digital PCR (ddPCR). By exploiting a correlation we have discovered between droplet fluorescence and amplicon size, we achieve the joint quantification and size determination of target DNA with a single ddPCR assay. We demonstrate the accuracy and precision of applying this method to the preparation of sequencing libraries.

Implementation of QR up- and downdating on a massively parallel |computer

DEFF Research Database (Denmark)

Bendtsen, Claus; Hansen, Per Christian; Madsen, Kaj

1995-01-01

We describe an implementation of QR up- and downdating on a massively parallel computer (the Connection Machine CM-200) and show that the algorithm maps well onto the computer. In particular, we show how the use of corrected semi-normal equations for downdating can be efficiently implemented. We...... also illustrate the use of our algorithms in a new LP algorithm....

Massively parallel simulator of optical coherence tomography of inhomogeneous turbid media.

Science.gov (United States)

Malektaji, Siavash; Lima, Ivan T; Escobar I, Mauricio R; Sherif, Sherif S

2017-10-01

An accurate and practical simulator for Optical Coherence Tomography (OCT) could be an important tool to study the underlying physical phenomena in OCT such as multiple light scattering. Recently, many researchers have investigated simulation of OCT of turbid media, e.g., tissue, using Monte Carlo methods. The main drawback of these earlier simulators is the long computational time required to produce accurate results. We developed a massively parallel simulator of OCT of inhomogeneous turbid media that obtains both Class I diffusive reflectivity, due to ballistic and quasi-ballistic scattered photons, and Class II diffusive reflectivity due to multiply scattered photons. This Monte Carlo-based simulator is implemented on graphic processing units (GPUs), using the Compute Unified Device Architecture (CUDA) platform and programming model, to exploit the parallel nature of propagation of photons in tissue. It models an arbitrary shaped sample medium as a tetrahedron-based mesh and uses an advanced importance sampling scheme. This new simulator speeds up simulations of OCT of inhomogeneous turbid media by about two orders of magnitude. To demonstrate this result, we have compared the computation times of our new parallel simulator and its serial counterpart using two samples of inhomogeneous turbid media. We have shown that our parallel implementation reduced simulation time of OCT of the first sample medium from 407 min to 92 min by using a single GPU card, to 12 min by using 8 GPU cards and to 7 min by using 16 GPU cards. For the second sample medium, the OCT simulation time was reduced from 209 h to 35.6 h by using a single GPU card, and to 4.65 h by using 8 GPU cards, and to only 2 h by using 16 GPU cards. Therefore our new parallel simulator is considerably more practical to use than its central processing unit (CPU)-based counterpart. Our new parallel OCT simulator could be a practical tool to study the different physical phenomena underlying OCT

Massively Parallel Single-Molecule Manipulation Using Centrifugal Force

Science.gov (United States)

Wong, Wesley; Halvorsen, Ken

2011-03-01

Precise manipulation of single molecules has led to remarkable insights in physics, chemistry, biology, and medicine. However, two issues that have impeded the widespread adoption of these techniques are equipment cost and the laborious nature of making measurements one molecule at a time. To meet these challenges, we have developed an approach that enables massively parallel single- molecule force measurements using centrifugal force. This approach is realized in the centrifuge force microscope, an instrument in which objects in an orbiting sample are subjected to a calibration-free, macroscopically uniform force- field while their micro-to-nanoscopic motions are observed. We demonstrate high- throughput single-molecule force spectroscopy with this technique by performing thousands of rupture experiments in parallel, characterizing force-dependent unbinding kinetics of an antibody-antigen pair in minutes rather than days. Currently, we are taking steps to integrate high-resolution detection, fluorescence, temperature control and a greater dynamic range in force. With significant benefits in efficiency, cost, simplicity, and versatility, single-molecule centrifugation has the potential to expand single-molecule experimentation to a wider range of researchers and experimental systems.

DGDFT: A massively parallel method for large scale density functional theory calculations.

Science.gov (United States)

Hu, Wei; Lin, Lin; Yang, Chao

2015-09-28

We describe a massively parallel implementation of the recently developed discontinuous Galerkin density functional theory (DGDFT) method, for efficient large-scale Kohn-Sham DFT based electronic structure calculations. The DGDFT method uses adaptive local basis (ALB) functions generated on-the-fly during the self-consistent field iteration to represent the solution to the Kohn-Sham equations. The use of the ALB set provides a systematic way to improve the accuracy of the approximation. By using the pole expansion and selected inversion technique to compute electron density, energy, and atomic forces, we can make the computational complexity of DGDFT scale at most quadratically with respect to the number of electrons for both insulating and metallic systems. We show that for the two-dimensional (2D) phosphorene systems studied here, using 37 basis functions per atom allows us to reach an accuracy level of 1.3 × 10(-4) Hartree/atom in terms of the error of energy and 6.2 × 10(-4) Hartree/bohr in terms of the error of atomic force, respectively. DGDFT can achieve 80% parallel efficiency on 128,000 high performance computing cores when it is used to study the electronic structure of 2D phosphorene systems with 3500-14 000 atoms. This high parallel efficiency results from a two-level parallelization scheme that we will describe in detail.

DGDFT: A massively parallel method for large scale density functional theory calculations

International Nuclear Information System (INIS)

Hu, Wei; Yang, Chao; Lin, Lin

2015-01-01

We describe a massively parallel implementation of the recently developed discontinuous Galerkin density functional theory (DGDFT) method, for efficient large-scale Kohn-Sham DFT based electronic structure calculations. The DGDFT method uses adaptive local basis (ALB) functions generated on-the-fly during the self-consistent field iteration to represent the solution to the Kohn-Sham equations. The use of the ALB set provides a systematic way to improve the accuracy of the approximation. By using the pole expansion and selected inversion technique to compute electron density, energy, and atomic forces, we can make the computational complexity of DGDFT scale at most quadratically with respect to the number of electrons for both insulating and metallic systems. We show that for the two-dimensional (2D) phosphorene systems studied here, using 37 basis functions per atom allows us to reach an accuracy level of 1.3 × 10 −4 Hartree/atom in terms of the error of energy and 6.2 × 10 −4 Hartree/bohr in terms of the error of atomic force, respectively. DGDFT can achieve 80% parallel efficiency on 128,000 high performance computing cores when it is used to study the electronic structure of 2D phosphorene systems with 3500-14 000 atoms. This high parallel efficiency results from a two-level parallelization scheme that we will describe in detail

DGDFT: A massively parallel method for large scale density functional theory calculations

Energy Technology Data Exchange (ETDEWEB)

Hu, Wei, E-mail: whu@lbl.gov; Yang, Chao, E-mail: cyang@lbl.gov [Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720 (United States); Lin, Lin, E-mail: linlin@math.berkeley.edu [Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720 (United States); Department of Mathematics, University of California, Berkeley, California 94720 (United States)

2015-09-28

We describe a massively parallel implementation of the recently developed discontinuous Galerkin density functional theory (DGDFT) method, for efficient large-scale Kohn-Sham DFT based electronic structure calculations. The DGDFT method uses adaptive local basis (ALB) functions generated on-the-fly during the self-consistent field iteration to represent the solution to the Kohn-Sham equations. The use of the ALB set provides a systematic way to improve the accuracy of the approximation. By using the pole expansion and selected inversion technique to compute electron density, energy, and atomic forces, we can make the computational complexity of DGDFT scale at most quadratically with respect to the number of electrons for both insulating and metallic systems. We show that for the two-dimensional (2D) phosphorene systems studied here, using 37 basis functions per atom allows us to reach an accuracy level of 1.3 × 10{sup −4} Hartree/atom in terms of the error of energy and 6.2 × 10{sup −4} Hartree/bohr in terms of the error of atomic force, respectively. DGDFT can achieve 80% parallel efficiency on 128,000 high performance computing cores when it is used to study the electronic structure of 2D phosphorene systems with 3500-14 000 atoms. This high parallel efficiency results from a two-level parallelization scheme that we will describe in detail.

Multiplexed microsatellite recovery using massively parallel sequencing

Science.gov (United States)

Jennings, T.N.; Knaus, B.J.; Mullins, T.D.; Haig, S.M.; Cronn, R.C.

2011-01-01

Conservation and management of natural populations requires accurate and inexpensive genotyping methods. Traditional microsatellite, or simple sequence repeat (SSR), marker analysis remains a popular genotyping method because of the comparatively low cost of marker development, ease of analysis and high power of genotype discrimination. With the availability of massively parallel sequencing (MPS), it is now possible to sequence microsatellite-enriched genomic libraries in multiplex pools. To test this approach, we prepared seven microsatellite-enriched, barcoded genomic libraries from diverse taxa (two conifer trees, five birds) and sequenced these on one lane of the Illumina Genome Analyzer using paired-end 80-bp reads. In this experiment, we screened 6.1 million sequences and identified 356958 unique microreads that contained di- or trinucleotide microsatellites. Examination of four species shows that our conversion rate from raw sequences to polymorphic markers compares favourably to Sanger- and 454-based methods. The advantage of multiplexed MPS is that the staggering capacity of modern microread sequencing is spread across many libraries; this reduces sample preparation and sequencing costs to less than $400 (USD) per species. This price is sufficiently low that microsatellite libraries could be prepared and sequenced for all 1373 organisms listed as 'threatened' and 'endangered' in the United States for under $0.5M (USD).

Detection of reverse transcriptase termination sites using cDNA ligation and massive parallel sequencing

DEFF Research Database (Denmark)

Kielpinski, Lukasz J; Boyd, Mette; Sandelin, Albin

2013-01-01

Detection of reverse transcriptase termination sites is important in many different applications, such as structural probing of RNAs, rapid amplification of cDNA 5' ends (5' RACE), cap analysis of gene expression, and detection of RNA modifications and protein-RNA cross-links. The throughput...... of these methods can be increased by applying massive parallel sequencing technologies.Here, we describe a versatile method for detection of reverse transcriptase termination sites based on ligation of an adapter to the 3' end of cDNA with bacteriophage TS2126 RNA ligase (CircLigase™). In the following PCR...

Computational chaos in massively parallel neural networks

Science.gov (United States)

Barhen, Jacob; Gulati, Sandeep

1989-01-01

A fundamental issue which directly impacts the scalability of current theoretical neural network models to massively parallel embodiments, in both software as well as hardware, is the inherent and unavoidable concurrent asynchronicity of emerging fine-grained computational ensembles and the possible emergence of chaotic manifestations. Previous analyses attributed dynamical instability to the topology of the interconnection matrix, to parasitic components or to propagation delays. However, researchers have observed the existence of emergent computational chaos in a concurrently asynchronous framework, independent of the network topology. Researcher present a methodology enabling the effective asynchronous operation of large-scale neural networks. Necessary and sufficient conditions guaranteeing concurrent asynchronous convergence are established in terms of contracting operators. Lyapunov exponents are computed formally to characterize the underlying nonlinear dynamics. Simulation results are presented to illustrate network convergence to the correct results, even in the presence of large delays.

Massively Parallel and Scalable Implicit Time Integration Algorithms for Structural Dynamics

Science.gov (United States)

Farhat, Charbel

1997-01-01

Explicit codes are often used to simulate the nonlinear dynamics of large-scale structural systems, even for low frequency response, because the storage and CPU requirements entailed by the repeated factorizations traditionally found in implicit codes rapidly overwhelm the available computing resources. With the advent of parallel processing, this trend is accelerating because of the following additional facts: (a) explicit schemes are easier to parallelize than implicit ones, and (b) explicit schemes induce short range interprocessor communications that are relatively inexpensive, while the factorization methods used in most implicit schemes induce long range interprocessor communications that often ruin the sought-after speed-up. However, the time step restriction imposed by the Courant stability condition on all explicit schemes cannot yet be offset by the speed of the currently available parallel hardware. Therefore, it is essential to develop efficient alternatives to direct methods that are also amenable to massively parallel processing because implicit codes using unconditionally stable time-integration algorithms are computationally more efficient when simulating the low-frequency dynamics of aerospace structures.

Engineering-Based Thermal CFD Simulations on Massive Parallel Systems

KAUST Repository

Frisch, Jé rô me; Mundani, Ralf-Peter; Rank, Ernst; van Treeck, Christoph

2015-01-01

The development of parallel Computational Fluid Dynamics (CFD) codes is a challenging task that entails efficient parallelization concepts and strategies in order to achieve good scalability values when running those codes on modern supercomputers

Massively parallel electrical conductivity imaging of the subsurface: Applications to hydrocarbon exploration

Science.gov (United States)

Newman, Gregory A.; Commer, Michael

2009-07-01

Three-dimensional (3D) geophysical imaging is now receiving considerable attention for electrical conductivity mapping of potential offshore oil and gas reservoirs. The imaging technology employs controlled source electromagnetic (CSEM) and magnetotelluric (MT) fields and treats geological media exhibiting transverse anisotropy. Moreover when combined with established seismic methods, direct imaging of reservoir fluids is possible. Because of the size of the 3D conductivity imaging problem, strategies are required exploiting computational parallelism and optimal meshing. The algorithm thus developed has been shown to scale to tens of thousands of processors. In one imaging experiment, 32,768 tasks/processors on the IBM Watson Research Blue Gene/L supercomputer were successfully utilized. Over a 24 hour period we were able to image a large scale field data set that previously required over four months of processing time on distributed clusters based on Intel or AMD processors utilizing 1024 tasks on an InfiniBand fabric. Electrical conductivity imaging using massively parallel computational resources produces results that cannot be obtained otherwise and are consistent with timeframes required for practical exploration problems.

Massively parallel electrical conductivity imaging of the subsurface: Applications to hydrocarbon exploration

International Nuclear Information System (INIS)

Newman, Gregory A; Commer, Michael

2009-01-01

Three-dimensional (3D) geophysical imaging is now receiving considerable attention for electrical conductivity mapping of potential offshore oil and gas reservoirs. The imaging technology employs controlled source electromagnetic (CSEM) and magnetotelluric (MT) fields and treats geological media exhibiting transverse anisotropy. Moreover when combined with established seismic methods, direct imaging of reservoir fluids is possible. Because of the size of the 3D conductivity imaging problem, strategies are required exploiting computational parallelism and optimal meshing. The algorithm thus developed has been shown to scale to tens of thousands of processors. In one imaging experiment, 32,768 tasks/processors on the IBM Watson Research Blue Gene/L supercomputer were successfully utilized. Over a 24 hour period we were able to image a large scale field data set that previously required over four months of processing time on distributed clusters based on Intel or AMD processors utilizing 1024 tasks on an InfiniBand fabric. Electrical conductivity imaging using massively parallel computational resources produces results that cannot be obtained otherwise and are consistent with timeframes required for practical exploration problems.

Developing a Massively Parallel Forward Projection Radiography Model for Large-Scale Industrial Applications

Energy Technology Data Exchange (ETDEWEB)

Bauerle, Matthew [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2014-08-01

This project utilizes Graphics Processing Units (GPUs) to compute radiograph simulations for arbitrary objects. The generation of radiographs, also known as the forward projection imaging model, is computationally intensive and not widely utilized. The goal of this research is to develop a massively parallel algorithm that can compute forward projections for objects with a trillion voxels (3D pixels). To achieve this end, the data are divided into blocks that can each t into GPU memory. The forward projected image is also divided into segments to allow for future parallelization and to avoid needless computations.

Massively parallel fabrication of repetitive nanostructures: nanolithography for nanoarrays

International Nuclear Information System (INIS)

Luttge, Regina

2009-01-01

This topical review provides an overview of nanolithographic techniques for nanoarrays. Using patterning techniques such as lithography, normally we aim for a higher order architecture similarly to functional systems in nature. Inspired by the wealth of complexity in nature, these architectures are translated into technical devices, for example, found in integrated circuitry or other systems in which structural elements work as discrete building blocks in microdevices. Ordered artificial nanostructures (arrays of pillars, holes and wires) have shown particular properties and bring about the opportunity to modify and tune the device operation. Moreover, these nanostructures deliver new applications, for example, the nanoscale control of spin direction within a nanomagnet. Subsequently, we can look for applications where this unique property of the smallest manufactured element is repetitively used such as, for example with respect to spin, in nanopatterned magnetic media for data storage. These nanostructures are generally called nanoarrays. Most of these applications require massively parallel produced nanopatterns which can be directly realized by laser interference (areas up to 4 cm 2 are easily achieved with a Lloyd's mirror set-up). In this topical review we will further highlight the application of laser interference as a tool for nanofabrication, its limitations and ultimate advantages towards a variety of devices including nanostructuring for photonic crystal devices, high resolution patterned media and surface modifications of medical implants. The unique properties of nanostructured surfaces have also found applications in biomedical nanoarrays used either for diagnostic or functional assays including catalytic reactions on chip. Bio-inspired templated nanoarrays will be presented in perspective to other massively parallel nanolithography techniques currently discussed in the scientific literature. (topical review)

Massively parallel DNA sequencing facilitates diagnosis of patients with Usher syndrome type 1.

Directory of Open Access Journals (Sweden)

Hidekane Yoshimura

Full Text Available Usher syndrome is an autosomal recessive disorder manifesting hearing loss, retinitis pigmentosa and vestibular dysfunction, and having three clinical subtypes. Usher syndrome type 1 is the most severe subtype due to its profound hearing loss, lack of vestibular responses, and retinitis pigmentosa that appears in prepuberty. Six of the corresponding genes have been identified, making early diagnosis through DNA testing possible, with many immediate and several long-term advantages for patients and their families. However, the conventional genetic techniques, such as direct sequence analysis, are both time-consuming and expensive. Targeted exon sequencing of selected genes using the massively parallel DNA sequencing technology will potentially enable us to systematically tackle previously intractable monogenic disorders and improve molecular diagnosis. Using this technique combined with direct sequence analysis, we screened 17 unrelated Usher syndrome type 1 patients and detected probable pathogenic variants in the 16 of them (94.1% who carried at least one mutation. Seven patients had the MYO7A mutation (41.2%, which is the most common type in Japanese. Most of the mutations were detected by only the massively parallel DNA sequencing. We report here four patients, who had probable pathogenic mutations in two different Usher syndrome type 1 genes, and one case of MYO7A/PCDH15 digenic inheritance. This is the first report of Usher syndrome mutation analysis using massively parallel DNA sequencing and the frequency of Usher syndrome type 1 genes in Japanese. Mutation screening using this technique has the power to quickly identify mutations of many causative genes while maintaining cost-benefit performance. In addition, the simultaneous mutation analysis of large numbers of genes is useful for detecting mutations in different genes that are possibly disease modifiers or of digenic inheritance.

Massively parallel DNA sequencing facilitates diagnosis of patients with Usher syndrome type 1.

Science.gov (United States)

Yoshimura, Hidekane; Iwasaki, Satoshi; Nishio, Shin-Ya; Kumakawa, Kozo; Tono, Tetsuya; Kobayashi, Yumiko; Sato, Hiroaki; Nagai, Kyoko; Ishikawa, Kotaro; Ikezono, Tetsuo; Naito, Yasushi; Fukushima, Kunihiro; Oshikawa, Chie; Kimitsuki, Takashi; Nakanishi, Hiroshi; Usami, Shin-Ichi

2014-01-01

Usher syndrome is an autosomal recessive disorder manifesting hearing loss, retinitis pigmentosa and vestibular dysfunction, and having three clinical subtypes. Usher syndrome type 1 is the most severe subtype due to its profound hearing loss, lack of vestibular responses, and retinitis pigmentosa that appears in prepuberty. Six of the corresponding genes have been identified, making early diagnosis through DNA testing possible, with many immediate and several long-term advantages for patients and their families. However, the conventional genetic techniques, such as direct sequence analysis, are both time-consuming and expensive. Targeted exon sequencing of selected genes using the massively parallel DNA sequencing technology will potentially enable us to systematically tackle previously intractable monogenic disorders and improve molecular diagnosis. Using this technique combined with direct sequence analysis, we screened 17 unrelated Usher syndrome type 1 patients and detected probable pathogenic variants in the 16 of them (94.1%) who carried at least one mutation. Seven patients had the MYO7A mutation (41.2%), which is the most common type in Japanese. Most of the mutations were detected by only the massively parallel DNA sequencing. We report here four patients, who had probable pathogenic mutations in two different Usher syndrome type 1 genes, and one case of MYO7A/PCDH15 digenic inheritance. This is the first report of Usher syndrome mutation analysis using massively parallel DNA sequencing and the frequency of Usher syndrome type 1 genes in Japanese. Mutation screening using this technique has the power to quickly identify mutations of many causative genes while maintaining cost-benefit performance. In addition, the simultaneous mutation analysis of large numbers of genes is useful for detecting mutations in different genes that are possibly disease modifiers or of digenic inheritance.

Enhanced memory architecture for massively parallel vision chip

Science.gov (United States)

Chen, Zhe; Yang, Jie; Liu, Liyuan; Wu, Nanjian

2015-04-01

Local memory architecture plays an important role in high performance massively parallel vision chip. In this paper, we propose an enhanced memory architecture with compact circuit area designed in a full-custom flow. The memory consists of separate master-stage static latches and shared slave-stage dynamic latches. We use split transmission transistors on the input data path to enhance tolerance for charge sharing and to achieve random read/write capabilities. The memory is designed in a 0.18 μm CMOS process. The area overhead of the memory achieves 16.6 μm2/bit. Simulation results show that the maximum operating frequency reaches 410 MHz and the corresponding peak dynamic power consumption for a 64-bit memory unit is 190 μW under 1.8 V supply voltage.

Increasing phylogenetic resolution at low taxonomic levels using massively parallel sequencing of chloroplast genomes

Science.gov (United States)

Matthew Parks; Richard Cronn; Aaron Liston

2009-01-01

We reconstruct the infrageneric phylogeny of Pinus from 37 nearly-complete chloroplast genomes (average 109 kilobases each of an approximately 120 kilobase genome) generated using multiplexed massively parallel sequencing. We found that 30/33 ingroup nodes resolved wlth > 95-percent bootstrap support; this is a substantial improvement relative...

MCBooster: a tool for MC generation for massively parallel platforms

CERN Multimedia

Alves Junior, Antonio Augusto

2016-01-01

MCBooster is a header-only, C++11-compliant library for the generation of large samples of phase-space Monte Carlo events on massively parallel platforms. It was released on GitHub in the spring of 2016. The library core algorithms implement the Raubold-Lynch method; they are able to generate the full kinematics of decays with up to nine particles in the final state. The library supports the generation of sequential decays as well as the parallel evaluation of arbitrary functions over the generated events. The output of MCBooster completely accords with popular and well-tested software packages such as GENBOD (W515 from CERNLIB) and TGenPhaseSpace from the ROOT framework. MCBooster is developed on top of the Thrust library and runs on Linux systems. It deploys transparently on NVidia CUDA-enabled GPUs as well as multicore CPUs. This contribution summarizes the main features of MCBooster. A basic description of the user interface and some examples of applications are provided, along with measurements of perfor...

Multi-mode sensor processing on a dynamically reconfigurable massively parallel processor array

Science.gov (United States)

Chen, Paul; Butts, Mike; Budlong, Brad; Wasson, Paul

2008-04-01

This paper introduces a novel computing architecture that can be reconfigured in real time to adapt on demand to multi-mode sensor platforms' dynamic computational and functional requirements. This 1 teraOPS reconfigurable Massively Parallel Processor Array (MPPA) has 336 32-bit processors. The programmable 32-bit communication fabric provides streamlined inter-processor connections with deterministically high performance. Software programmability, scalability, ease of use, and fast reconfiguration time (ranging from microseconds to milliseconds) are the most significant advantages over FPGAs and DSPs. This paper introduces the MPPA architecture, its programming model, and methods of reconfigurability. An MPPA platform for reconfigurable computing is based on a structural object programming model. Objects are software programs running concurrently on hundreds of 32-bit RISC processors and memories. They exchange data and control through a network of self-synchronizing channels. A common application design pattern on this platform, called a work farm, is a parallel set of worker objects, with one input and one output stream. Statically configured work farms with homogeneous and heterogeneous sets of workers have been used in video compression and decompression, network processing, and graphics applications.

A highly scalable massively parallel fast marching method for the Eikonal equation

Science.gov (United States)

Yang, Jianming; Stern, Frederick

2017-03-01

The fast marching method is a widely used numerical method for solving the Eikonal equation arising from a variety of scientific and engineering fields. It is long deemed inherently sequential and an efficient parallel algorithm applicable to large-scale practical applications is not available in the literature. In this study, we present a highly scalable massively parallel implementation of the fast marching method using a domain decomposition approach. Central to this algorithm is a novel restarted narrow band approach that coordinates the frequency of communications and the amount of computations extra to a sequential run for achieving an unprecedented parallel performance. Within each restart, the narrow band fast marching method is executed; simple synchronous local exchanges and global reductions are adopted for communicating updated data in the overlapping regions between neighboring subdomains and getting the latest front status, respectively. The independence of front characteristics is exploited through special data structures and augmented status tags to extract the masked parallelism within the fast marching method. The efficiency, flexibility, and applicability of the parallel algorithm are demonstrated through several examples. These problems are extensively tested on six grids with up to 1 billion points using different numbers of processes ranging from 1 to 65536. Remarkable parallel speedups are achieved using tens of thousands of processes. Detailed pseudo-codes for both the sequential and parallel algorithms are provided to illustrate the simplicity of the parallel implementation and its similarity to the sequential narrow band fast marching algorithm.

Massively parallel whole genome amplification for single-cell sequencing using droplet microfluidics.

Science.gov (United States)

Hosokawa, Masahito; Nishikawa, Yohei; Kogawa, Masato; Takeyama, Haruko

2017-07-12

Massively parallel single-cell genome sequencing is required to further understand genetic diversities in complex biological systems. Whole genome amplification (WGA) is the first step for single-cell sequencing, but its throughput and accuracy are insufficient in conventional reaction platforms. Here, we introduce single droplet multiple displacement amplification (sd-MDA), a method that enables massively parallel amplification of single cell genomes while maintaining sequence accuracy and specificity. Tens of thousands of single cells are compartmentalized in millions of picoliter droplets and then subjected to lysis and WGA by passive droplet fusion in microfluidic channels. Because single cells are isolated in compartments, their genomes are amplified to saturation without contamination. This enables the high-throughput acquisition of contamination-free and cell specific sequence reads from single cells (21,000 single-cells/h), resulting in enhancement of the sequence data quality compared to conventional methods. This method allowed WGA of both single bacterial cells and human cancer cells. The obtained sequencing coverage rivals those of conventional techniques with superior sequence quality. In addition, we also demonstrate de novo assembly of uncultured soil bacteria and obtain draft genomes from single cell sequencing. This sd-MDA is promising for flexible and scalable use in single-cell sequencing.

Block iterative restoration of astronomical images with the massively parallel processor

International Nuclear Information System (INIS)

Heap, S.R.; Lindler, D.J.

1987-01-01

A method is described for algebraic image restoration capable of treating astronomical images. For a typical 500 x 500 image, direct algebraic restoration would require the solution of a 250,000 x 250,000 linear system. The block iterative approach is used to reduce the problem to solving 4900 121 x 121 linear systems. The algorithm was implemented on the Goddard Massively Parallel Processor, which can solve a 121 x 121 system in approximately 0.06 seconds. Examples are shown of the results for various astronomical images

A Computational Fluid Dynamics Algorithm on a Massively Parallel Computer

Science.gov (United States)

Jespersen, Dennis C.; Levit, Creon

1989-01-01

The discipline of computational fluid dynamics is demanding ever-increasing computational power to deal with complex fluid flow problems. We investigate the performance of a finite-difference computational fluid dynamics algorithm on a massively parallel computer, the Connection Machine. Of special interest is an implicit time-stepping algorithm; to obtain maximum performance from the Connection Machine, it is necessary to use a nonstandard algorithm to solve the linear systems that arise in the implicit algorithm. We find that the Connection Machine ran achieve very high computation rates on both explicit and implicit algorithms. The performance of the Connection Machine puts it in the same class as today's most powerful conventional supercomputers.

The Fortran-P Translator: Towards Automatic Translation of Fortran 77 Programs for Massively Parallel Processors

Directory of Open Access Journals (Sweden)

Matthew O'keefe

1995-01-01

Full Text Available Massively parallel processors (MPPs hold the promise of extremely high performance that, if realized, could be used to study problems of unprecedented size and complexity. One of the primary stumbling blocks to this promise has been the lack of tools to translate application codes to MPP form. In this article we show how applications codes written in a subset of Fortran 77, called Fortran-P, can be translated to achieve good performance on several massively parallel machines. This subset can express codes that are self-similar, where the algorithm applied to the global data domain is also applied to each subdomain. We have found many codes that match the Fortran-P programming style and have converted them using our tools. We believe a self-similar coding style will accomplish what a vectorizable style has accomplished for vector machines by allowing the construction of robust, user-friendly, automatic translation systems that increase programmer productivity and generate fast, efficient code for MPPs.

Computations on the massively parallel processor at the Goddard Space Flight Center

Science.gov (United States)

Strong, James P.

1991-01-01

Described are four significant algorithms implemented on the massively parallel processor (MPP) at the Goddard Space Flight Center. Two are in the area of image analysis. Of the other two, one is a mathematical simulation experiment and the other deals with the efficient transfer of data between distantly separated processors in the MPP array. The first algorithm presented is the automatic determination of elevations from stereo pairs. The second algorithm solves mathematical logistic equations capable of producing both ordered and chaotic (or random) solutions. This work can potentially lead to the simulation of artificial life processes. The third algorithm is the automatic segmentation of images into reasonable regions based on some similarity criterion, while the fourth is an implementation of a bitonic sort of data which significantly overcomes the nearest neighbor interconnection constraints on the MPP for transferring data between distant processors.

Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms.

Science.gov (United States)

Yu, Leiming; Nina-Paravecino, Fanny; Kaeli, David; Fang, Qianqian

2018-01-01

We present a highly scalable Monte Carlo (MC) three-dimensional photon transport simulation platform designed for heterogeneous computing systems. Through the development of a massively parallel MC algorithm using the Open Computing Language framework, this research extends our existing graphics processing unit (GPU)-accelerated MC technique to a highly scalable vendor-independent heterogeneous computing environment, achieving significantly improved performance and software portability. A number of parallel computing techniques are investigated to achieve portable performance over a wide range of computing hardware. Furthermore, multiple thread-level and device-level load-balancing strategies are developed to obtain efficient simulations using multiple central processing units and GPUs. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Time-dependent density-functional theory in massively parallel computer architectures: the OCTOPUS project.

Science.gov (United States)

Andrade, Xavier; Alberdi-Rodriguez, Joseba; Strubbe, David A; Oliveira, Micael J T; Nogueira, Fernando; Castro, Alberto; Muguerza, Javier; Arruabarrena, Agustin; Louie, Steven G; Aspuru-Guzik, Alán; Rubio, Angel; Marques, Miguel A L

2012-06-13

Octopus is a general-purpose density-functional theory (DFT) code, with a particular emphasis on the time-dependent version of DFT (TDDFT). In this paper we present the ongoing efforts to achieve the parallelization of octopus. We focus on the real-time variant of TDDFT, where the time-dependent Kohn-Sham equations are directly propagated in time. This approach has great potential for execution in massively parallel systems such as modern supercomputers with thousands of processors and graphics processing units (GPUs). For harvesting the potential of conventional supercomputers, the main strategy is a multi-level parallelization scheme that combines the inherent scalability of real-time TDDFT with a real-space grid domain-partitioning approach. A scalable Poisson solver is critical for the efficiency of this scheme. For GPUs, we show how using blocks of Kohn-Sham states provides the required level of data parallelism and that this strategy is also applicable for code optimization on standard processors. Our results show that real-time TDDFT, as implemented in octopus, can be the method of choice for studying the excited states of large molecular systems in modern parallel architectures.

Time-dependent density-functional theory in massively parallel computer architectures: the octopus project

Science.gov (United States)

Andrade, Xavier; Alberdi-Rodriguez, Joseba; Strubbe, David A.; Oliveira, Micael J. T.; Nogueira, Fernando; Castro, Alberto; Muguerza, Javier; Arruabarrena, Agustin; Louie, Steven G.; Aspuru-Guzik, Alán; Rubio, Angel; Marques, Miguel A. L.

2012-06-01

Octopus is a general-purpose density-functional theory (DFT) code, with a particular emphasis on the time-dependent version of DFT (TDDFT). In this paper we present the ongoing efforts to achieve the parallelization of octopus. We focus on the real-time variant of TDDFT, where the time-dependent Kohn-Sham equations are directly propagated in time. This approach has great potential for execution in massively parallel systems such as modern supercomputers with thousands of processors and graphics processing units (GPUs). For harvesting the potential of conventional supercomputers, the main strategy is a multi-level parallelization scheme that combines the inherent scalability of real-time TDDFT with a real-space grid domain-partitioning approach. A scalable Poisson solver is critical for the efficiency of this scheme. For GPUs, we show how using blocks of Kohn-Sham states provides the required level of data parallelism and that this strategy is also applicable for code optimization on standard processors. Our results show that real-time TDDFT, as implemented in octopus, can be the method of choice for studying the excited states of large molecular systems in modern parallel architectures.

Time-dependent density-functional theory in massively parallel computer architectures: the octopus project

International Nuclear Information System (INIS)

Andrade, Xavier; Aspuru-Guzik, Alán; Alberdi-Rodriguez, Joseba; Rubio, Angel; Strubbe, David A; Louie, Steven G; Oliveira, Micael J T; Nogueira, Fernando; Castro, Alberto; Muguerza, Javier; Arruabarrena, Agustin; Marques, Miguel A L

2012-01-01

Octopus is a general-purpose density-functional theory (DFT) code, with a particular emphasis on the time-dependent version of DFT (TDDFT). In this paper we present the ongoing efforts to achieve the parallelization of octopus. We focus on the real-time variant of TDDFT, where the time-dependent Kohn-Sham equations are directly propagated in time. This approach has great potential for execution in massively parallel systems such as modern supercomputers with thousands of processors and graphics processing units (GPUs). For harvesting the potential of conventional supercomputers, the main strategy is a multi-level parallelization scheme that combines the inherent scalability of real-time TDDFT with a real-space grid domain-partitioning approach. A scalable Poisson solver is critical for the efficiency of this scheme. For GPUs, we show how using blocks of Kohn-Sham states provides the required level of data parallelism and that this strategy is also applicable for code optimization on standard processors. Our results show that real-time TDDFT, as implemented in octopus, can be the method of choice for studying the excited states of large molecular systems in modern parallel architectures. (topical review)

Tolerating correlated failures in Massively Parallel Stream Processing Engines

DEFF Research Database (Denmark)

Su, L.; Zhou, Y.

2016-01-01

Fault-tolerance techniques for stream processing engines can be categorized into passive and active approaches. A typical passive approach periodically checkpoints a processing task's runtime states and can recover a failed task by restoring its runtime state using its latest checkpoint. On the o......Fault-tolerance techniques for stream processing engines can be categorized into passive and active approaches. A typical passive approach periodically checkpoints a processing task's runtime states and can recover a failed task by restoring its runtime state using its latest checkpoint....... On the other hand, an active approach usually employs backup nodes to run replicated tasks. Upon failure, the active replica can take over the processing of the failed task with minimal latency. However, both approaches have their own inadequacies in Massively Parallel Stream Processing Engines (MPSPE...

Distributed Parallel Endmember Extraction of Hyperspectral Data Based on Spark

Directory of Open Access Journals (Sweden)

Zebin Wu

2016-01-01

Full Text Available Due to the increasing dimensionality and volume of remotely sensed hyperspectral data, the development of acceleration techniques for massive hyperspectral image analysis approaches is a very important challenge. Cloud computing offers many possibilities of distributed processing of hyperspectral datasets. This paper proposes a novel distributed parallel endmember extraction method based on iterative error analysis that utilizes cloud computing principles to efficiently process massive hyperspectral data. The proposed method takes advantage of technologies including MapReduce programming model, Hadoop Distributed File System (HDFS, and Apache Spark to realize distributed parallel implementation for hyperspectral endmember extraction, which significantly accelerates the computation of hyperspectral processing and provides high throughput access to large hyperspectral data. The experimental results, which are obtained by extracting endmembers of hyperspectral datasets on a cloud computing platform built on a cluster, demonstrate the effectiveness and computational efficiency of the proposed method.

A Massively Parallel Solver for the Mechanical Harmonic Analysis of Accelerator Cavities

International Nuclear Information System (INIS)

2015-01-01

ACE3P is a 3D massively parallel simulation suite that developed at SLAC National Accelerator Laboratory that can perform coupled electromagnetic, thermal and mechanical study. Effectively utilizing supercomputer resources, ACE3P has become a key simulation tool for particle accelerator R and D. A new frequency domain solver to perform mechanical harmonic response analysis of accelerator components is developed within the existing parallel framework. This solver is designed to determine the frequency response of the mechanical system to external harmonic excitations for time-efficient accurate analysis of the large-scale problems. Coupled with the ACE3P electromagnetic modules, this capability complements a set of multi-physics tools for a comprehensive study of microphonics in superconducting accelerating cavities in order to understand the RF response and feedback requirements for the operational reliability of a particle accelerator. (auth)

Parallel computing works

Energy Technology Data Exchange (ETDEWEB)

1991-10-23

An account of the Caltech Concurrent Computation Program (C{sup 3}P), a five year project that focused on answering the question: Can parallel computers be used to do large-scale scientific computations '' As the title indicates, the question is answered in the affirmative, by implementing numerous scientific applications on real parallel computers and doing computations that produced new scientific results. In the process of doing so, C{sup 3}P helped design and build several new computers, designed and implemented basic system software, developed algorithms for frequently used mathematical computations on massively parallel machines, devised performance models and measured the performance of many computers, and created a high performance computing facility based exclusively on parallel computers. While the initial focus of C{sup 3}P was the hypercube architecture developed by C. Seitz, many of the methods developed and lessons learned have been applied successfully on other massively parallel architectures.

From Massively Parallel Algorithms and Fluctuating Time Horizons to Nonequilibrium Surface Growth

International Nuclear Information System (INIS)

Korniss, G.; Toroczkai, Z.; Novotny, M. A.; Rikvold, P. A.

2000-01-01

We study the asymptotic scaling properties of a massively parallel algorithm for discrete-event simulations where the discrete events are Poisson arrivals. The evolution of the simulated time horizon is analogous to a nonequilibrium surface. Monte Carlo simulations and a coarse-grained approximation indicate that the macroscopic landscape in the steady state is governed by the Edwards-Wilkinson Hamiltonian. Since the efficiency of the algorithm corresponds to the density of local minima in the associated surface, our results imply that the algorithm is asymptotically scalable. (c) 2000 The American Physical Society

Passive and partially active fault tolerance for massively parallel stream processing engines

DEFF Research Database (Denmark)

Su, Li; Zhou, Yongluan

2018-01-01

. On the other hand, an active approach usually employs backup nodes to run replicated tasks. Upon failure, the active replica can take over the processing of the failed task with minimal latency. However, both approaches have their own inadequacies in Massively Parallel Stream Processing Engines (MPSPE...... also propose effective and efficient algorithms to optimize a partially active replication plan to maximize the quality of tentative outputs. We implemented PPA on top of Storm, an open-source MPSPE and conducted extensive experiments using both real and synthetic datasets to verify the effectiveness...

Massively Parallel Interrogation of Aptamer Sequence, Structure and Function

Energy Technology Data Exchange (ETDEWEB)

Fischer, N O; Tok, J B; Tarasow, T M

2008-02-08

Optimization of high affinity reagents is a significant bottleneck in medicine and the life sciences. The ability to synthetically create thousands of permutations of a lead high-affinity reagent and survey the properties of individual permutations in parallel could potentially relieve this bottleneck. Aptamers are single stranded oligonucleotides affinity reagents isolated by in vitro selection processes and as a class have been shown to bind a wide variety of target molecules. Methodology/Principal Findings. High density DNA microarray technology was used to synthesize, in situ, arrays of approximately 3,900 aptamer sequence permutations in triplicate. These sequences were interrogated on-chip for their ability to bind the fluorescently-labeled cognate target, immunoglobulin E, resulting in the parallel execution of thousands of experiments. Fluorescence intensity at each array feature was well resolved and shown to be a function of the sequence present. The data demonstrated high intra- and interchip correlation between the same features as well as among the sequence triplicates within a single array. Consistent with aptamer mediated IgE binding, fluorescence intensity correlated strongly with specific aptamer sequences and the concentration of IgE applied to the array. The massively parallel sequence-function analyses provided by this approach confirmed the importance of a consensus sequence found in all 21 of the original IgE aptamer sequences and support a common stem:loop structure as being the secondary structure underlying IgE binding. The microarray application, data and results presented illustrate an efficient, high information content approach to optimizing aptamer function. It also provides a foundation from which to better understand and manipulate this important class of high affinity biomolecules.

Massively parallel interrogation of aptamer sequence, structure and function.

Directory of Open Access Journals (Sweden)

Nicholas O Fischer

Full Text Available BACKGROUND: Optimization of high affinity reagents is a significant bottleneck in medicine and the life sciences. The ability to synthetically create thousands of permutations of a lead high-affinity reagent and survey the properties of individual permutations in parallel could potentially relieve this bottleneck. Aptamers are single stranded oligonucleotides affinity reagents isolated by in vitro selection processes and as a class have been shown to bind a wide variety of target molecules. METHODOLOGY/PRINCIPAL FINDINGS: High density DNA microarray technology was used to synthesize, in situ, arrays of approximately 3,900 aptamer sequence permutations in triplicate. These sequences were interrogated on-chip for their ability to bind the fluorescently-labeled cognate target, immunoglobulin E, resulting in the parallel execution of thousands of experiments. Fluorescence intensity at each array feature was well resolved and shown to be a function of the sequence present. The data demonstrated high intra- and inter-chip correlation between the same features as well as among the sequence triplicates within a single array. Consistent with aptamer mediated IgE binding, fluorescence intensity correlated strongly with specific aptamer sequences and the concentration of IgE applied to the array. CONCLUSION AND SIGNIFICANCE: The massively parallel sequence-function analyses provided by this approach confirmed the importance of a consensus sequence found in all 21 of the original IgE aptamer sequences and support a common stem:loop structure as being the secondary structure underlying IgE binding. The microarray application, data and results presented illustrate an efficient, high information content approach to optimizing aptamer function. It also provides a foundation from which to better understand and manipulate this important class of high affinity biomolecules.

OpenCL Implementation of a Parallel Universal Kriging Algorithm for Massive Spatial Data Interpolation on Heterogeneous Systems

Directory of Open Access Journals (Sweden)

Fang Huang

2016-06-01

Full Text Available In some digital Earth engineering applications, spatial interpolation algorithms are required to process and analyze large amounts of data. Due to its powerful computing capacity, heterogeneous computing has been used in many applications for data processing in various fields. In this study, we explore the design and implementation of a parallel universal kriging spatial interpolation algorithm using the OpenCL programming model on heterogeneous computing platforms for massive Geo-spatial data processing. This study focuses primarily on transforming the hotspots in serial algorithms, i.e., the universal kriging interpolation function, into the corresponding kernel function in OpenCL. We also employ parallelization and optimization techniques in our implementation to improve the code performance. Finally, based on the results of experiments performed on two different high performance heterogeneous platforms, i.e., an NVIDIA graphics processing unit system and an Intel Xeon Phi system (MIC, we show that the parallel universal kriging algorithm can achieve the highest speedup of up to 40× with a single computing device and the highest speedup of up to 80× with multiple devices.

Application of Raptor-M3G to reactor dosimetry problems on massively parallel architectures - 026

International Nuclear Information System (INIS)

Longoni, G.

2010-01-01

The solution of complex 3-D radiation transport problems requires significant resources both in terms of computation time and memory availability. Therefore, parallel algorithms and multi-processor architectures are required to solve efficiently large 3-D radiation transport problems. This paper presents the application of RAPTOR-M3G (Rapid Parallel Transport Of Radiation - Multiple 3D Geometries) to reactor dosimetry problems. RAPTOR-M3G is a newly developed parallel computer code designed to solve the discrete ordinates (SN) equations on multi-processor computer architectures. This paper presents the results for a reactor dosimetry problem using a 3-D model of a commercial 2-loop pressurized water reactor (PWR). The accuracy and performance of RAPTOR-M3G will be analyzed and the numerical results obtained from the calculation will be compared directly to measurements of the neutron field in the reactor cavity air gap. The parallel performance of RAPTOR-M3G on massively parallel architectures, where the number of computing nodes is in the order of hundreds, will be analyzed up to four hundred processors. The performance results will be presented based on two supercomputing architectures: the POPLE supercomputer operated by the Pittsburgh Supercomputing Center and the Westinghouse computer cluster. The Westinghouse computer cluster is equipped with a standard Ethernet network connection and an InfiniBand R interconnects capable of a bandwidth in excess of 20 GBit/sec. Therefore, the impact of the network architecture on RAPTOR-M3G performance will be analyzed as well. (authors)

Wideband aperture array using RF channelizers and massively parallel digital 2D IIR filterbank

Science.gov (United States)

Sengupta, Arindam; Madanayake, Arjuna; Gómez-García, Roberto; Engeberg, Erik D.

2014-05-01

Wideband receive-mode beamforming applications in wireless location, electronically-scanned antennas for radar, RF sensing, microwave imaging and wireless communications require digital aperture arrays that offer a relatively constant far-field beam over several octaves of bandwidth. Several beamforming schemes including the well-known true time-delay and the phased array beamformers have been realized using either finite impulse response (FIR) or fast Fourier transform (FFT) digital filter-sum based techniques. These beamforming algorithms offer the desired selectivity at the cost of a high computational complexity and frequency-dependant far-field array patterns. A novel approach to receiver beamforming is the use of massively parallel 2-D infinite impulse response (IIR) fan filterbanks for the synthesis of relatively frequency independent RF beams at an order of magnitude lower multiplier complexity compared to FFT or FIR filter based conventional algorithms. The 2-D IIR filterbanks demand fast digital processing that can support several octaves of RF bandwidth, fast analog-to-digital converters (ADCs) for RF-to-bits type direct conversion of wideband antenna element signals. Fast digital implementation platforms that can realize high-precision recursive filter structures necessary for real-time beamforming, at RF radio bandwidths, are also desired. We propose a novel technique that combines a passive RF channelizer, multichannel ADC technology, and single-phase massively parallel 2-D IIR digital fan filterbanks, realized at low complexity using FPGA and/or ASIC technology. There exists native support for a larger bandwidth than the maximum clock frequency of the digital implementation technology. We also strive to achieve More-than-Moore throughput by processing a wideband RF signal having content with N-fold (B = N Fclk/2) bandwidth compared to the maximum clock frequency Fclk Hz of the digital VLSI platform under consideration. Such increase in bandwidth is

Massively parallel amplicon sequencing reveals isotype-specific variability of antimicrobial peptide transcripts in Mytilus galloprovincialis.

Directory of Open Access Journals (Sweden)

Umberto Rosani

Full Text Available BACKGROUND: Effective innate responses against potential pathogens are essential in the living world and possibly contributed to the evolutionary success of invertebrates. Taken together, antimicrobial peptide (AMP precursors of defensin, mytilin, myticin and mytimycin can represent about 40% of the hemocyte transcriptome in mussels injected with viral-like and bacterial preparations, and unique profiles of myticin C variants are expressed in single mussels. Based on amplicon pyrosequencing, we have ascertained and compared the natural and Vibrio-induced diversity of AMP transcripts in mussel hemocytes from three European regions. METHODOLOGY/PRINCIPAL FINDINGS: Hemolymph was collected from mussels farmed in the coastal regions of Palavas (France, Vigo (Spain and Venice (Italy. To represent the AMP families known in M. galloprovincialis, nine transcript sequences have been selected, amplified from hemocyte RNA and subjected to pyrosequencing. Hemolymph from farmed (offshore and wild (lagoon Venice mussels, both injected with 10(7 Vibrio cells, were similarly processed. Amplicon pyrosequencing emphasized the AMP transcript diversity, with Single Nucleotide Changes (SNC minimal for mytilin B/C and maximal for arthropod-like defensin and myticin C. Ratio of non-synonymous vs. synonymous changes also greatly differed between AMP isotypes. Overall, each amplicon revealed similar levels of nucleotidic variation across geographical regions, with two main sequence patterns confirmed for mytimycin and no substantial changes after immunostimulation. CONCLUSIONS/SIGNIFICANCE: Barcoding and bidirectional pyrosequencing allowed us to map and compare the transcript diversity of known mussel AMPs. Though most of the genuine cds variation was common to the analyzed samples we could estimate from 9 to 106 peptide variants in hemolymph pools representing 100 mussels, depending on the AMP isoform and sampling site. In this study, no prevailing SNC patterns related

User's Guide for TOUGH2-MP - A Massively Parallel Version of the TOUGH2 Code

International Nuclear Information System (INIS)

Earth Sciences Division; Zhang, Keni; Zhang, Keni; Wu, Yu-Shu; Pruess, Karsten

2008-01-01

TOUGH2-MP is a massively parallel (MP) version of the TOUGH2 code, designed for computationally efficient parallel simulation of isothermal and nonisothermal flows of multicomponent, multiphase fluids in one, two, and three-dimensional porous and fractured media. In recent years, computational requirements have become increasingly intensive in large or highly nonlinear problems for applications in areas such as radioactive waste disposal, CO2 geological sequestration, environmental assessment and remediation, reservoir engineering, and groundwater hydrology. The primary objective of developing the parallel-simulation capability is to significantly improve the computational performance of the TOUGH2 family of codes. The particular goal for the parallel simulator is to achieve orders-of-magnitude improvement in computational time for models with ever-increasing complexity. TOUGH2-MP is designed to perform parallel simulation on multi-CPU computational platforms. An earlier version of TOUGH2-MP (V1.0) was based on the TOUGH2 Version 1.4 with EOS3, EOS9, and T2R3D modules, a software previously qualified for applications in the Yucca Mountain project, and was designed for execution on CRAY T3E and IBM SP supercomputers. The current version of TOUGH2-MP (V2.0) includes all fluid property modules of the standard version TOUGH2 V2.0. It provides computationally efficient capabilities using supercomputers, Linux clusters, or multi-core PCs, and also offers many user-friendly features. The parallel simulator inherits all process capabilities from V2.0 together with additional capabilities for handling fractured media from V1.4. This report provides a quick starting guide on how to set up and run the TOUGH2-MP program for users with a basic knowledge of running the (standard) version TOUGH2 code. The report also gives a brief technical description of the code, including a discussion of parallel methodology, code structure, as well as mathematical and numerical methods used

Modular and efficient ozone systems based on massively parallel chemical processing in microchannel plasma arrays: performance and commercialization

Science.gov (United States)

Kim, M.-H.; Cho, J. H.; Park, S.-J.; Eden, J. G.

2017-08-01

Plasmachemical systems based on the production of a specific molecule (O3) in literally thousands of microchannel plasmas simultaneously have been demonstrated, developed and engineered over the past seven years, and commercialized. At the heart of this new plasma technology is the plasma chip, a flat aluminum strip fabricated by photolithographic and wet chemical processes and comprising 24-48 channels, micromachined into nanoporous aluminum oxide, with embedded electrodes. By integrating 4-6 chips into a module, the mass output of an ozone microplasma system is scaled linearly with the number of modules operating in parallel. A 115 g/hr (2.7 kg/day) ozone system, for example, is realized by the combined output of 18 modules comprising 72 chips and 1,800 microchannels. The implications of this plasma processing architecture for scaling ozone production capability, and reducing capital and service costs when introducing redundancy into the system, are profound. In contrast to conventional ozone generator technology, microplasma systems operate reliably (albeit with reduced output) in ambient air and humidity levels up to 90%, a characteristic attributable to the water adsorption/desorption properties and electrical breakdown strength of nanoporous alumina. Extensive testing has documented chip and system lifetimes (MTBF) beyond 5,000 hours, and efficiencies >130 g/kWh when oxygen is the feedstock gas. Furthermore, the weight and volume of microplasma systems are a factor of 3-10 lower than those for conventional ozone systems of comparable output. Massively-parallel plasmachemical processing offers functionality, performance, and commercial value beyond that afforded by conventional technology, and is currently in operation in more than 30 countries worldwide.

Massively Parallel Finite Element Programming

KAUST Repository

Heister, Timo; Kronbichler, Martin; Bangerth, Wolfgang

2010-01-01

Today's large finite element simulations require parallel algorithms to scale on clusters with thousands or tens of thousands of processor cores. We present data structures and algorithms to take advantage of the power of high performance computers in generic finite element codes. Existing generic finite element libraries often restrict the parallelization to parallel linear algebra routines. This is a limiting factor when solving on more than a few hundreds of cores. We describe routines for distributed storage of all major components coupled with efficient, scalable algorithms. We give an overview of our effort to enable the modern and generic finite element library deal.II to take advantage of the power of large clusters. In particular, we describe the construction of a distributed mesh and develop algorithms to fully parallelize the finite element calculation. Numerical results demonstrate good scalability. © 2010 Springer-Verlag.

Massively Parallel Finite Element Programming

KAUST Repository

Heister, Timo

2010-01-01

Today\\'s large finite element simulations require parallel algorithms to scale on clusters with thousands or tens of thousands of processor cores. We present data structures and algorithms to take advantage of the power of high performance computers in generic finite element codes. Existing generic finite element libraries often restrict the parallelization to parallel linear algebra routines. This is a limiting factor when solving on more than a few hundreds of cores. We describe routines for distributed storage of all major components coupled with efficient, scalable algorithms. We give an overview of our effort to enable the modern and generic finite element library deal.II to take advantage of the power of large clusters. In particular, we describe the construction of a distributed mesh and develop algorithms to fully parallelize the finite element calculation. Numerical results demonstrate good scalability. © 2010 Springer-Verlag.

Massive parallel 3D PIC simulation of negative ion extraction

Science.gov (United States)

Revel, Adrien; Mochalskyy, Serhiy; Montellano, Ivar Mauricio; Wünderlich, Dirk; Fantz, Ursel; Minea, Tiberiu

2017-09-01

The 3D PIC-MCC code ONIX is dedicated to modeling Negative hydrogen/deuterium Ion (NI) extraction and co-extraction of electrons from radio-frequency driven, low pressure plasma sources. It provides valuable insight on the complex phenomena involved in the extraction process. In previous calculations, a mesh size larger than the Debye length was used, implying numerical electron heating. Important steps have been achieved in terms of computation performance and parallelization efficiency allowing successful massive parallel calculations (4096 cores), imperative to resolve the Debye length. In addition, the numerical algorithms have been improved in terms of grid treatment, i.e., the electric field near the complex geometry boundaries (plasma grid) is calculated more accurately. The revised model preserves the full 3D treatment, but can take advantage of a highly refined mesh. ONIX was used to investigate the role of the mesh size, the re-injection scheme for lost particles (extracted or wall absorbed), and the electron thermalization process on the calculated extracted current and plasma characteristics. It is demonstrated that all numerical schemes give the same NI current distribution for extracted ions. Concerning the electrons, the pair-injection technique is found well-adapted to simulate the sheath in front of the plasma grid.

Cloud identification using genetic algorithms and massively parallel computation

Science.gov (United States)

Buckles, Bill P.; Petry, Frederick E.

1996-01-01

As a Guest Computational Investigator under the NASA administered component of the High Performance Computing and Communication Program, we implemented a massively parallel genetic algorithm on the MasPar SIMD computer. Experiments were conducted using Earth Science data in the domains of meteorology and oceanography. Results obtained in these domains are competitive with, and in most cases better than, similar problems solved using other methods. In the meteorological domain, we chose to identify clouds using AVHRR spectral data. Four cloud speciations were used although most researchers settle for three. Results were remarkedly consistent across all tests (91% accuracy). Refinements of this method may lead to more timely and complete information for Global Circulation Models (GCMS) that are prevalent in weather forecasting and global environment studies. In the oceanographic domain, we chose to identify ocean currents from a spectrometer having similar characteristics to AVHRR. Here the results were mixed (60% to 80% accuracy). Given that one is willing to run the experiment several times (say 10), then it is acceptable to claim the higher accuracy rating. This problem has never been successfully automated. Therefore, these results are encouraging even though less impressive than the cloud experiment. Successful conclusion of an automated ocean current detection system would impact coastal fishing, naval tactics, and the study of micro-climates. Finally we contributed to the basic knowledge of GA (genetic algorithm) behavior in parallel environments. We developed better knowledge of the use of subpopulations in the context of shared breeding pools and the migration of individuals. Rigorous experiments were conducted based on quantifiable performance criteria. While much of the work confirmed current wisdom, for the first time we were able to submit conclusive evidence. The software developed under this grant was placed in the public domain. An extensive user

Massively parallel de novo protein design for targeted therapeutics

KAUST Repository

Chevalier, Aaron

2017-09-26

De novo protein design holds promise for creating small stable proteins with shapes customized to bind therapeutic targets. We describe a massively parallel approach for designing, manufacturing and screening mini-protein binders, integrating large-scale computational design, oligonucleotide synthesis, yeast display screening and next-generation sequencing. We designed and tested 22,660 mini-proteins of 37-43 residues that target influenza haemagglutinin and botulinum neurotoxin B, along with 6,286 control sequences to probe contributions to folding and binding, and identified 2,618 high-affinity binders. Comparison of the binding and non-binding design sets, which are two orders of magnitude larger than any previously investigated, enabled the evaluation and improvement of the computational model. Biophysical characterization of a subset of the binder designs showed that they are extremely stable and, unlike antibodies, do not lose activity after exposure to high temperatures. The designs elicit little or no immune response and provide potent prophylactic and therapeutic protection against influenza, even after extensive repeated dosing.

Massively parallel de novo protein design for targeted therapeutics

KAUST Repository

Chevalier, Aaron; Silva, Daniel-Adriano; Rocklin, Gabriel J.; Hicks, Derrick R.; Vergara, Renan; Murapa, Patience; Bernard, Steffen M.; Zhang, Lu; Lam, Kwok-Ho; Yao, Guorui; Bahl, Christopher D.; Miyashita, Shin-Ichiro; Goreshnik, Inna; Fuller, James T.; Koday, Merika T.; Jenkins, Cody M.; Colvin, Tom; Carter, Lauren; Bohn, Alan; Bryan, Cassie M.; Ferná ndez-Velasco, D. Alejandro; Stewart, Lance; Dong, Min; Huang, Xuhui; Jin, Rongsheng; Wilson, Ian A.; Fuller, Deborah H.; Baker, David

2017-01-01

De novo protein design holds promise for creating small stable proteins with shapes customized to bind therapeutic targets. We describe a massively parallel approach for designing, manufacturing and screening mini-protein binders, integrating large-scale computational design, oligonucleotide synthesis, yeast display screening and next-generation sequencing. We designed and tested 22,660 mini-proteins of 37-43 residues that target influenza haemagglutinin and botulinum neurotoxin B, along with 6,286 control sequences to probe contributions to folding and binding, and identified 2,618 high-affinity binders. Comparison of the binding and non-binding design sets, which are two orders of magnitude larger than any previously investigated, enabled the evaluation and improvement of the computational model. Biophysical characterization of a subset of the binder designs showed that they are extremely stable and, unlike antibodies, do not lose activity after exposure to high temperatures. The designs elicit little or no immune response and provide potent prophylactic and therapeutic protection against influenza, even after extensive repeated dosing.

Massively parallel performance of neutron transport response matrix algorithms

International Nuclear Information System (INIS)

Hanebutte, U.R.; Lewis, E.E.

1993-01-01

Massively parallel red/black response matrix algorithms for the solution of within-group neutron transport problems are implemented on the Connection Machines-2, 200 and 5. The response matrices are dericed from the diamond-differences and linear-linear nodal discrete ordinate and variational nodal P 3 approximations. The unaccelerated performance of the iterative procedure is examined relative to the maximum rated performances of the machines. The effects of processor partitions size, of virtual processor ratio and of problems size are examined in detail. For the red/black algorithm, the ratio of inter-node communication to computing times is found to be quite small, normally of the order of ten percent or less. Performance increases with problems size and with virtual processor ratio, within the memeory per physical processor limitation. Algorithm adaptation to courser grain machines is straight-forward, with total computing time being virtually inversely proportional to the number of physical processors. (orig.)

Massively parallel de novo protein design for targeted therapeutics

Science.gov (United States)

Chevalier, Aaron; Silva, Daniel-Adriano; Rocklin, Gabriel J.; Hicks, Derrick R.; Vergara, Renan; Murapa, Patience; Bernard, Steffen M.; Zhang, Lu; Lam, Kwok-Ho; Yao, Guorui; Bahl, Christopher D.; Miyashita, Shin-Ichiro; Goreshnik, Inna; Fuller, James T.; Koday, Merika T.; Jenkins, Cody M.; Colvin, Tom; Carter, Lauren; Bohn, Alan; Bryan, Cassie M.; Fernández-Velasco, D. Alejandro; Stewart, Lance; Dong, Min; Huang, Xuhui; Jin, Rongsheng; Wilson, Ian A.; Fuller, Deborah H.; Baker, David

2018-01-01

De novo protein design holds promise for creating small stable proteins with shapes customized to bind therapeutic targets. We describe a massively parallel approach for designing, manufacturing and screening mini-protein binders, integrating large-scale computational design, oligonucleotide synthesis, yeast display screening and next-generation sequencing. We designed and tested 22,660 mini-proteins of 37–43 residues that target influenza haemagglutinin and botulinum neurotoxin B, along with 6,286 control sequences to probe contributions to folding and binding, and identified 2,618 high-affinity binders. Comparison of the binding and non-binding design sets, which are two orders of magnitude larger than any previously investigated, enabled the evaluation and improvement of the computational model. Biophysical characterization of a subset of the binder designs showed that they are extremely stable and, unlike antibodies, do not lose activity after exposure to high temperatures. The designs elicit little or no immune response and provide potent prophylactic and therapeutic protection against influenza, even after extensive repeated dosing. PMID:28953867

A massively parallel algorithm for the collision probability calculations in the Apollo-II code using the PVM library

International Nuclear Information System (INIS)

Stankovski, Z.

1995-01-01

The collision probability method in neutron transport, as applied to 2D geometries, consume a great amount of computer time, for a typical 2D assembly calculation evaluations. Consequently RZ or 3D calculations became prohibitive. In this paper we present a simple but efficient parallel algorithm based on the message passing host/node programing model. Parallelization was applied to the energy group treatment. Such approach permits parallelization of the existing code, requiring only limited modifications. Sequential/parallel computer portability is preserved, witch is a necessary condition for a industrial code. Sequential performances are also preserved. The algorithm is implemented on a CRAY 90 coupled to a 128 processor T3D computer, a 16 processor IBM SP1 and a network of workstations, using the Public Domain PVM library. The tests were executed for a 2D geometry with the standard 99-group library. All results were very satisfactory, the best ones with IBM SP1. Because of heterogeneity of the workstation network, we did ask high performances for this architecture. The same source code was used for all computers. A more impressive advantage of this algorithm will appear in the calculations of the SAPHYR project (with the future fine multigroup library of about 8000 groups) with a massively parallel computer, using several hundreds of processors. (author). 5 refs., 6 figs., 2 tabs

A massively parallel algorithm for the collision probability calculations in the Apollo-II code using the PVM library

International Nuclear Information System (INIS)

Stankovski, Z.

1995-01-01

The collision probability method in neutron transport, as applied to 2D geometries, consume a great amount of computer time, for a typical 2D assembly calculation about 90% of the computing time is consumed in the collision probability evaluations. Consequently RZ or 3D calculations became prohibitive. In this paper the author presents a simple but efficient parallel algorithm based on the message passing host/node programmation model. Parallelization was applied to the energy group treatment. Such approach permits parallelization of the existing code, requiring only limited modifications. Sequential/parallel computer portability is preserved, which is a necessary condition for a industrial code. Sequential performances are also preserved. The algorithm is implemented on a CRAY 90 coupled to a 128 processor T3D computer, a 16 processor IBM SPI and a network of workstations, using the Public Domain PVM library. The tests were executed for a 2D geometry with the standard 99-group library. All results were very satisfactory, the best ones with IBM SPI. Because of heterogeneity of the workstation network, the author did not ask high performances for this architecture. The same source code was used for all computers. A more impressive advantage of this algorithm will appear in the calculations of the SAPHYR project (with the future fine multigroup library of about 8000 groups) with a massively parallel computer, using several hundreds of processors

Revealing the Physics of Galactic Winds Through Massively-Parallel Hydrodynamics Simulations

Science.gov (United States)

Schneider, Evan Elizabeth

This thesis documents the hydrodynamics code Cholla and a numerical study of multiphase galactic winds. Cholla is a massively-parallel, GPU-based code designed for astrophysical simulations that is freely available to the astrophysics community. A static-mesh Eulerian code, Cholla is ideally suited to carrying out massive simulations (> 20483 cells) that require very high resolution. The code incorporates state-of-the-art hydrodynamics algorithms including third-order spatial reconstruction, exact and linearized Riemann solvers, and unsplit integration algorithms that account for transverse fluxes on multidimensional grids. Operator-split radiative cooling and a dual-energy formalism for high mach number flows are also included. An extensive test suite demonstrates Cholla's superior ability to model shocks and discontinuities, while the GPU-native design makes the code extremely computationally efficient - speeds of 5-10 million cell updates per GPU-second are typical on current hardware for 3D simulations with all of the aforementioned physics. The latter half of this work comprises a comprehensive study of the mixing between a hot, supernova-driven wind and cooler clouds representative of those observed in multiphase galactic winds. Both adiabatic and radiatively-cooling clouds are investigated. The analytic theory of cloud-crushing is applied to the problem, and adiabatic turbulent clouds are found to be mixed with the hot wind on similar timescales as the classic spherical case (4-5 t cc) with an appropriate rescaling of the cloud-crushing time. Radiatively cooling clouds survive considerably longer, and the differences in evolution between turbulent and spherical clouds cannot be reconciled with a simple rescaling. The rapid incorporation of low-density material into the hot wind implies efficient mass-loading of hot phases of galactic winds. At the same time, the extreme compression of high-density cloud material leads to long-lived but slow-moving clumps

Massive parallel sequencing in sarcoma pathobiology: state of the art and perspectives.

Science.gov (United States)

Brenca, Monica; Maestro, Roberta

2015-01-01

Sarcomas are an aggressive and highly heterogeneous group of mesenchymal malignancies with different morphologies and clinical behavior. Current therapeutic strategies remain unsatisfactory. Cytogenetic and molecular characterization of these tumors is resulting in the breakdown of the classical histopathological categories into molecular subgroups that better define sarcoma pathobiology and pave the way to more precise diagnostic criteria and novel therapeutic opportunities. The purpose of this short review is to summarize the state-of-the-art on the exploitation of massive parallel sequencing technologies, also known as next generation sequencing, in the elucidation of sarcoma pathobiology and to discuss how these applications may impact on diagnosis, prognosis and therapy of these tumors.

Decreasing Data Analytics Time: Hybrid Architecture MapReduce-Massive Parallel Processing for a Smart Grid

Directory of Open Access Journals (Sweden)

Abdeslam Mehenni

2017-03-01

Full Text Available As our populations grow in a world of limited resources enterprise seek ways to lighten our load on the planet. The idea of modifying consumer behavior appears as a foundation for smart grids. Enterprise demonstrates the value available from deep analysis of electricity consummation histories, consumers’ messages, and outage alerts, etc. Enterprise mines massive structured and unstructured data. In a nutshell, smart grids result in a flood of data that needs to be analyzed, for better adjust to demand and give customers more ability to delve into their power consumption. Simply put, smart grids will increasingly have a flexible data warehouse attached to them. The key driver for the adoption of data management strategies is clearly the need to handle and analyze the large amounts of information utilities are now faced with. New approaches to data integration are nauseating moment; Hadoop is in fact now being used by the utility to help manage the huge growth in data whilst maintaining coherence of the Data Warehouse. In this paper we define a new Meter Data Management System Architecture repository that differ with three leaders MDMS, where we use MapReduce programming model for ETL and Parallel DBMS in Query statements(Massive Parallel Processing MPP.

Statistical method to compare massive parallel sequencing pipelines.

Science.gov (United States)

Elsensohn, M H; Leblay, N; Dimassi, S; Campan-Fournier, A; Labalme, A; Roucher-Boulez, F; Sanlaville, D; Lesca, G; Bardel, C; Roy, P

2017-03-01

Today, sequencing is frequently carried out by Massive Parallel Sequencing (MPS) that cuts drastically sequencing time and expenses. Nevertheless, Sanger sequencing remains the main validation method to confirm the presence of variants. The analysis of MPS data involves the development of several bioinformatic tools, academic or commercial. We present here a statistical method to compare MPS pipelines and test it in a comparison between an academic (BWA-GATK) and a commercial pipeline (TMAP-NextGENe®), with and without reference to a gold standard (here, Sanger sequencing), on a panel of 41 genes in 43 epileptic patients. This method used the number of variants to fit log-linear models for pairwise agreements between pipelines. To assess the heterogeneity of the margins and the odds ratios of agreement, four log-linear models were used: a full model, a homogeneous-margin model, a model with single odds ratio for all patients, and a model with single intercept. Then a log-linear mixed model was fitted considering the biological variability as a random effect. Among the 390,339 base-pairs sequenced, TMAP-NextGENe® and BWA-GATK found, on average, 2253.49 and 1857.14 variants (single nucleotide variants and indels), respectively. Against the gold standard, the pipelines had similar sensitivities (63.47% vs. 63.42%) and close but significantly different specificities (99.57% vs. 99.65%; p < 0.001). Same-trend results were obtained when only single nucleotide variants were considered (99.98% specificity and 76.81% sensitivity for both pipelines). The method allows thus pipeline comparison and selection. It is generalizable to all types of MPS data and all pipelines.

Evaluation of culture-based techniques and 454 pyrosequencing for the analysis of fungal diversity in potting media and organic fertilizers.

Science.gov (United States)

Al-Sadi, A M; Al-Mazroui, S S; Phillips, A J L

2015-08-01

Potting media and organic fertilizers (OFs) are commonly used in agricultural systems. However, there is a lack of studies on the efficiency of culture-based techniques in assessing the level of fungal diversity in these products. A study was conducted to investigate the efficiency of seven culture-based techniques and pyrosequencing for characterizing fungal diversity in potting media and OFs. Fungal diversity was evaluated using serial dilution, direct plating and baiting with carrot slices, potato slices, radish seeds, cucumber seeds and cucumber cotyledons. Identity of all the isolates was confirmed on the basis of the internal transcribed spacer region of the ribosomal RNA (ITS rRNA) sequence data. The direct plating technique was found to be superior over other culture-based techniques in the number of fungal species detected. It was also found to be simple and the least time consuming technique. Comparing the efficiency of direct plating with 454 pyrosequencing revealed that pyrosequencing detected 12 and 15 times more fungal species from potting media and OFs respectively. Analysis revealed that there were differences between potting media and OFs in the dominant phyla, classes, orders, families, genera and species detected. Zygomycota (52%) and Chytridiomycota (60%) were the predominant phyla in potting media and OFs respectively. The superiority of pyrosequencing over cultural methods could be related to the ability to detect obligate fungi, slow growing fungi and fungi that exist at low population densities. The evaluated methods in this study, especially direct plating and pyrosequencing, may be used as tools to help detect and reduce movement of unwanted fungi between countries and regions. © 2015 The Society for Applied Microbiology.

Massive Exploration of Perturbed Conditions of the Blood Coagulation Cascade through GPU Parallelization

Directory of Open Access Journals (Sweden)

Paolo Cazzaniga

2014-01-01

high-performance computing solutions is motivated by the need of performing large numbers of in silico analysis to study the behavior of biological systems in different conditions, which necessitate a computing power that usually overtakes the capability of standard desktop computers. In this work we present coagSODA, a CUDA-powered computational tool that was purposely developed for the analysis of a large mechanistic model of the blood coagulation cascade (BCC, defined according to both mass-action kinetics and Hill functions. coagSODA allows the execution of parallel simulations of the dynamics of the BCC by automatically deriving the system of ordinary differential equations and then exploiting the numerical integration algorithm LSODA. We present the biological results achieved with a massive exploration of perturbed conditions of the BCC, carried out with one-dimensional and bi-dimensional parameter sweep analysis, and show that GPU-accelerated parallel simulations of this model can increase the computational performances up to a 181× speedup compared to the corresponding sequential simulations.

Beam dynamics calculations and particle tracking using massively parallel processors

International Nuclear Information System (INIS)

Ryne, R.D.; Habib, S.

1995-01-01

During the past decade massively parallel processors (MPPs) have slowly gained acceptance within the scientific community. At present these machines typically contain a few hundred to one thousand off-the-shelf microprocessors and a total memory of up to 32 GBytes. The potential performance of these machines is illustrated by the fact that a month long job on a high end workstation might require only a few hours on an MPP. The acceptance of MPPs has been slow for a variety of reasons. For example, some algorithms are not easily parallelizable. Also, in the past these machines were difficult to program. But in recent years the development of Fortran-like languages such as CM Fortran and High Performance Fortran have made MPPs much easier to use. In the following we will describe how MPPs can be used for beam dynamics calculations and long term particle tracking

Implementation, capabilities, and benchmarking of Shift, a massively parallel Monte Carlo radiation transport code

International Nuclear Information System (INIS)

Pandya, Tara M.; Johnson, Seth R.; Evans, Thomas M.; Davidson, Gregory G.; Hamilton, Steven P.; Godfrey, Andrew T.

2015-01-01

This paper discusses the implementation, capabilities, and validation of Shift, a massively parallel Monte Carlo radiation transport package developed and maintained at Oak Ridge National Laboratory. It has been developed to scale well from laptop to small computing clusters to advanced supercomputers. Special features of Shift include hybrid capabilities for variance reduction such as CADIS and FW-CADIS, and advanced parallel decomposition and tally methods optimized for scalability on supercomputing architectures. Shift has been validated and verified against various reactor physics benchmarks and compares well to other state-of-the-art Monte Carlo radiation transport codes such as MCNP5, CE KENO-VI, and OpenMC. Some specific benchmarks used for verification and validation include the CASL VERA criticality test suite and several Westinghouse AP1000 ® problems. These benchmark and scaling studies show promising results

Significant association between sulfate-reducing bacteria and uranium-reducing microbial communities as revealed by a combined massively parallel sequencing-indicator species approach.

Science.gov (United States)

Cardenas, Erick; Wu, Wei-Min; Leigh, Mary Beth; Carley, Jack; Carroll, Sue; Gentry, Terry; Luo, Jian; Watson, David; Gu, Baohua; Ginder-Vogel, Matthew; Kitanidis, Peter K; Jardine, Philip M; Zhou, Jizhong; Criddle, Craig S; Marsh, Terence L; Tiedje, James M

2010-10-01

Massively parallel sequencing has provided a more affordable and high-throughput method to study microbial communities, although it has mostly been used in an exploratory fashion. We combined pyrosequencing with a strict indicator species statistical analysis to test if bacteria specifically responded to ethanol injection that successfully promoted dissimilatory uranium(VI) reduction in the subsurface of a uranium contamination plume at the Oak Ridge Field Research Center in Tennessee. Remediation was achieved with a hydraulic flow control consisting of an inner loop, where ethanol was injected, and an outer loop for flow-field protection. This strategy reduced uranium concentrations in groundwater to levels below 0.126 μM and created geochemical gradients in electron donors from the inner-loop injection well toward the outer loop and downgradient flow path. Our analysis with 15 sediment samples from the entire test area found significant indicator species that showed a high degree of adaptation to the three different hydrochemical-created conditions. Castellaniella and Rhodanobacter characterized areas with low pH, heavy metals, and low bioactivity, while sulfate-, Fe(III)-, and U(VI)-reducing bacteria (Desulfovibrio, Anaeromyxobacter, and Desulfosporosinus) were indicators of areas where U(VI) reduction occurred. The abundance of these bacteria, as well as the Fe(III) and U(VI) reducer Geobacter, correlated with the hydraulic connectivity to the substrate injection site, suggesting that the selected populations were a direct response to electron donor addition by the groundwater flow path. A false-discovery-rate approach was implemented to discard false-positive results by chance, given the large amount of data compared.

A scalable approach to modeling groundwater flow on massively parallel computers

International Nuclear Information System (INIS)

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

1995-12-01

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

Inter-laboratory evaluation of the EUROFORGEN Global ancestry-informative SNP panel by massively parallel sequencing using the Ion PGM™

DEFF Research Database (Denmark)

Eduardoff, M; Gross, T E; Santos, C

2016-01-01

Seq™ PCR primers was designed for the Global AIM-SNPs to perform massively parallel sequencing using the Ion PGM™ system. This study assessed individual SNP genotyping precision using the Ion PGM™, the forensic sensitivity of the multiplex using dilution series, degraded DNA plus simple mixtures...

Massively parallel pyrosequencing of the mitochondrial genome with the 454 methodology in forensic genetics

DEFF Research Database (Denmark)

Mikkelsen, Martin; Frank-Hansen, Rune; Hansen, Anders Johannes

2014-01-01

RESULTS: of sequencing of whole mitochondrial genome, HV1 and HV2 DNA with the second generation system (SGS) Roche 454 GS Junior were compared with results of Sanger sequencing and SNP typing with SNaPshot single base extension detected with MALDI-TOF and capillary electrophoresis. We investigated...

A Faster Parallel Algorithm and Efficient Multithreaded Implementations for Evaluating Betweenness Centrality on Massive Datasets

Energy Technology Data Exchange (ETDEWEB)

Madduri, Kamesh; Ediger, David; Jiang, Karl; Bader, David A.; Chavarria-Miranda, Daniel

2009-02-15

We present a new lock-free parallel algorithm for computing betweenness centralityof massive small-world networks. With minor changes to the data structures, ouralgorithm also achieves better spatial cache locality compared to previous approaches. Betweenness centrality is a key algorithm kernel in HPCS SSCA#2, a benchmark extensively used to evaluate the performance of emerging high-performance computing architectures for graph-theoretic computations. We design optimized implementations of betweenness centrality and the SSCA#2 benchmark for two hardware multithreaded systems: a Cray XMT system with the Threadstorm processor, and a single-socket Sun multicore server with the UltraSPARC T2 processor. For a small-world network of 134 million vertices and 1.073 billion edges, the 16-processor XMT system and the 8-core Sun Fire T5120 server achieve TEPS scores (an algorithmic performance count for the SSCA#2 benchmark) of 160 million and 90 million respectively, which corresponds to more than a 2X performance improvement over the previous parallel implementations. To better characterize the performance of these multithreaded systems, we correlate the SSCA#2 performance results with data from the memory-intensive STREAM and RandomAccess benchmarks. Finally, we demonstrate the applicability of our implementation to analyze massive real-world datasets by computing approximate betweenness centrality for a large-scale IMDb movie-actor network.

Mining of unexplored habitats for novel chitinases - chiA as a helper gene proxy in metagenomics

DEFF Research Database (Denmark)

Cretoiu, Mariana Silvia; Kielak, Anna Maria; Abu Al-Soud, Waleed

2012-01-01

encompassed (1) classical overall enzymatic assays, (2) chiA gene abundance measurement by qPCR, (3) chiA gene pyrosequencing, and (4) chiA gene-based PCR-DGGE was used. The chiA gene pyrosequencing is unprecedented, as it is the first massive parallel sequencing of this gene. The data obtained showed...... the existence across habitats of core bacterial communities responsible for chitin assimilation irrespective of ecosystem origin. Conversely, there were habitat-specific differences. In addition, a suite of sequences were obtained that are as yet unregistered in the chitinase database. In terms of chiA gene...

Massively parallel computing and the search for jets and black holes at the LHC

Energy Technology Data Exchange (ETDEWEB)

Halyo, V., E-mail: vhalyo@gmail.com; LeGresley, P.; Lujan, P.

2014-04-21

Massively parallel computing at the LHC could be the next leap necessary to reach an era of new discoveries at the LHC after the Higgs discovery. Scientific computing is a critical component of the LHC experiment, including operation, trigger, LHC computing GRID, simulation, and analysis. One way to improve the physics reach of the LHC is to take advantage of the flexibility of the trigger system by integrating coprocessors based on Graphics Processing Units (GPUs) or the Many Integrated Core (MIC) architecture into its server farm. This cutting edge technology provides not only the means to accelerate existing algorithms, but also the opportunity to develop new algorithms that select events in the trigger that previously would have evaded detection. In this paper we describe new algorithms that would allow us to select in the trigger new topological signatures that include non-prompt jet and black hole-like objects in the silicon tracker.

Massively parallel simulations of strong electronic correlations: Realistic Coulomb vertex and multiplet effects

Science.gov (United States)

Baumgärtel, M.; Ghanem, K.; Kiani, A.; Koch, E.; Pavarini, E.; Sims, H.; Zhang, G.

2017-07-01

We discuss the efficient implementation of general impurity solvers for dynamical mean-field theory. We show that both Lanczos and quantum Monte Carlo in different flavors (Hirsch-Fye, continuous-time hybridization- and interaction-expansion) exhibit excellent scaling on massively parallel supercomputers. We apply these algorithms to simulate realistic model Hamiltonians including the full Coulomb vertex, crystal-field splitting, and spin-orbit interaction. We discuss how to remove the sign problem in the presence of non-diagonal crystal-field and hybridization matrices. We show how to extract the physically observable quantities from imaginary time data, in particular correlation functions and susceptibilities. Finally, we present benchmarks and applications for representative correlated systems.

Significant Association between Sulfate-Reducing Bacteria and Uranium-Reducing Microbial Communities as Revealed by a Combined Massively Parallel Sequencing-Indicator Species Approach▿ †

Science.gov (United States)

Cardenas, Erick; Wu, Wei-Min; Leigh, Mary Beth; Carley, Jack; Carroll, Sue; Gentry, Terry; Luo, Jian; Watson, David; Gu, Baohua; Ginder-Vogel, Matthew; Kitanidis, Peter K.; Jardine, Philip M.; Zhou, Jizhong; Criddle, Craig S.; Marsh, Terence L.; Tiedje, James M.

2010-01-01

Massively parallel sequencing has provided a more affordable and high-throughput method to study microbial communities, although it has mostly been used in an exploratory fashion. We combined pyrosequencing with a strict indicator species statistical analysis to test if bacteria specifically responded to ethanol injection that successfully promoted dissimilatory uranium(VI) reduction in the subsurface of a uranium contamination plume at the Oak Ridge Field Research Center in Tennessee. Remediation was achieved with a hydraulic flow control consisting of an inner loop, where ethanol was injected, and an outer loop for flow-field protection. This strategy reduced uranium concentrations in groundwater to levels below 0.126 μM and created geochemical gradients in electron donors from the inner-loop injection well toward the outer loop and downgradient flow path. Our analysis with 15 sediment samples from the entire test area found significant indicator species that showed a high degree of adaptation to the three different hydrochemical-created conditions. Castellaniella and Rhodanobacter characterized areas with low pH, heavy metals, and low bioactivity, while sulfate-, Fe(III)-, and U(VI)-reducing bacteria (Desulfovibrio, Anaeromyxobacter, and Desulfosporosinus) were indicators of areas where U(VI) reduction occurred. The abundance of these bacteria, as well as the Fe(III) and U(VI) reducer Geobacter, correlated with the hydraulic connectivity to the substrate injection site, suggesting that the selected populations were a direct response to electron donor addition by the groundwater flow path. A false-discovery-rate approach was implemented to discard false-positive results by chance, given the large amount of data compared. PMID:20729318

Hierarchical Image Segmentation of Remotely Sensed Data using Massively Parallel GNU-LINUX Software

Science.gov (United States)

Tilton, James C.

2003-01-01

A hierarchical set of image segmentations is a set of several image segmentations of the same image at different levels of detail in which the segmentations at coarser levels of detail can be produced from simple merges of regions at finer levels of detail. In [1], Tilton, et a1 describes an approach for producing hierarchical segmentations (called HSEG) and gave a progress report on exploiting these hierarchical segmentations for image information mining. The HSEG algorithm is a hybrid of region growing and constrained spectral clustering that produces a hierarchical set of image segmentations based on detected convergence points. In the main, HSEG employs the hierarchical stepwise optimization (HSWO) approach to region growing, which was described as early as 1989 by Beaulieu and Goldberg. The HSWO approach seeks to produce segmentations that are more optimized than those produced by more classic approaches to region growing (e.g. Horowitz and T. Pavlidis, [3]). In addition, HSEG optionally interjects between HSWO region growing iterations, merges between spatially non-adjacent regions (i.e., spectrally based merging or clustering) constrained by a threshold derived from the previous HSWO region growing iteration. While the addition of constrained spectral clustering improves the utility of the segmentation results, especially for larger images, it also significantly increases HSEG s computational requirements. To counteract this, a computationally efficient recursive, divide-and-conquer, implementation of HSEG (RHSEG) was devised, which includes special code to avoid processing artifacts caused by RHSEG s recursive subdivision of the image data. The recursive nature of RHSEG makes for a straightforward parallel implementation. This paper describes the HSEG algorithm, its recursive formulation (referred to as RHSEG), and the implementation of RHSEG using massively parallel GNU-LINUX software. Results with Landsat TM data are included comparing RHSEG with classic

Characteristics of 454 pyrosequencing data--enabling realistic simulation with flowsim.

Science.gov (United States)

Balzer, Susanne; Malde, Ketil; Lanzén, Anders; Sharma, Animesh; Jonassen, Inge

2010-09-15

The commercial launch of 454 pyrosequencing in 2005 was a milestone in genome sequencing in terms of performance and cost. Throughout the three available releases, average read lengths have increased to approximately 500 base pairs and are thus approaching read lengths obtained from traditional Sanger sequencing. Study design of sequencing projects would benefit from being able to simulate experiments. We explore 454 raw data to investigate its characteristics and derive empirical distributions for the flow values generated by pyrosequencing. Based on our findings, we implement Flowsim, a simulator that generates realistic pyrosequencing data files of arbitrary size from a given set of input DNA sequences. We finally use our simulator to examine the impact of sequence lengths on the results of concrete whole-genome assemblies, and we suggest its use in planning of sequencing projects, benchmarking of assembly methods and other fields. Flowsim is freely available under the General Public License from http://blog.malde.org/index.php/flowsim/.

A massively parallel strategy for STR marker development, capture, and genotyping.

Science.gov (United States)

Kistler, Logan; Johnson, Stephen M; Irwin, Mitchell T; Louis, Edward E; Ratan, Aakrosh; Perry, George H

2017-09-06

Short tandem repeat (STR) variants are highly polymorphic markers that facilitate powerful population genetic analyses. STRs are especially valuable in conservation and ecological genetic research, yielding detailed information on population structure and short-term demographic fluctuations. Massively parallel sequencing has not previously been leveraged for scalable, efficient STR recovery. Here, we present a pipeline for developing STR markers directly from high-throughput shotgun sequencing data without a reference genome, and an approach for highly parallel target STR recovery. We employed our approach to capture a panel of 5000 STRs from a test group of diademed sifakas (Propithecus diadema, n = 3), endangered Malagasy rainforest lemurs, and we report extremely efficient recovery of targeted loci-97.3-99.6% of STRs characterized with ≥10x non-redundant sequence coverage. We then tested our STR capture strategy on P. diadema fecal DNA, and report robust initial results and suggestions for future implementations. In addition to STR targets, this approach also generates large, genome-wide single nucleotide polymorphism (SNP) panels from flanking regions. Our method provides a cost-effective and scalable solution for rapid recovery of large STR and SNP datasets in any species without needing a reference genome, and can be used even with suboptimal DNA more easily acquired in conservation and ecological studies. Published by Oxford University Press on behalf of Nucleic Acids Research 2017.

Differences Between Distributed and Parallel Systems

Energy Technology Data Exchange (ETDEWEB)

Brightwell, R.; Maccabe, A.B.; Rissen, R.

1998-10-01

Distributed systems have been studied for twenty years and are now coming into wider use as fast networks and powerful workstations become more readily available. In many respects a massively parallel computer resembles a network of workstations and it is tempting to port a distributed operating system to such a machine. However, there are significant differences between these two environments and a parallel operating system is needed to get the best performance out of a massively parallel system. This report characterizes the differences between distributed systems, networks of workstations, and massively parallel systems and analyzes the impact of these differences on operating system design. In the second part of the report, we introduce Puma, an operating system specifically developed for massively parallel systems. We describe Puma portals, the basic building blocks for message passing paradigms implemented on top of Puma, and show how the differences observed in the first part of the report have influenced the design and implementation of Puma.

CHOLLA: A NEW MASSIVELY PARALLEL HYDRODYNAMICS CODE FOR ASTROPHYSICAL SIMULATION

International Nuclear Information System (INIS)

Schneider, Evan E.; Robertson, Brant E.

2015-01-01

We present Computational Hydrodynamics On ParaLLel Architectures (Cholla ), a new three-dimensional hydrodynamics code that harnesses the power of graphics processing units (GPUs) to accelerate astrophysical simulations. Cholla models the Euler equations on a static mesh using state-of-the-art techniques, including the unsplit Corner Transport Upwind algorithm, a variety of exact and approximate Riemann solvers, and multiple spatial reconstruction techniques including the piecewise parabolic method (PPM). Using GPUs, Cholla evolves the fluid properties of thousands of cells simultaneously and can update over 10 million cells per GPU-second while using an exact Riemann solver and PPM reconstruction. Owing to the massively parallel architecture of GPUs and the design of the Cholla code, astrophysical simulations with physically interesting grid resolutions (≳256 3 ) can easily be computed on a single device. We use the Message Passing Interface library to extend calculations onto multiple devices and demonstrate nearly ideal scaling beyond 64 GPUs. A suite of test problems highlights the physical accuracy of our modeling and provides a useful comparison to other codes. We then use Cholla to simulate the interaction of a shock wave with a gas cloud in the interstellar medium, showing that the evolution of the cloud is highly dependent on its density structure. We reconcile the computed mixing time of a turbulent cloud with a realistic density distribution destroyed by a strong shock with the existing analytic theory for spherical cloud destruction by describing the system in terms of its median gas density

CHOLLA: A NEW MASSIVELY PARALLEL HYDRODYNAMICS CODE FOR ASTROPHYSICAL SIMULATION

Energy Technology Data Exchange (ETDEWEB)

Schneider, Evan E.; Robertson, Brant E. [Steward Observatory, University of Arizona, 933 North Cherry Avenue, Tucson, AZ 85721 (United States)

2015-04-15

We present Computational Hydrodynamics On ParaLLel Architectures (Cholla ), a new three-dimensional hydrodynamics code that harnesses the power of graphics processing units (GPUs) to accelerate astrophysical simulations. Cholla models the Euler equations on a static mesh using state-of-the-art techniques, including the unsplit Corner Transport Upwind algorithm, a variety of exact and approximate Riemann solvers, and multiple spatial reconstruction techniques including the piecewise parabolic method (PPM). Using GPUs, Cholla evolves the fluid properties of thousands of cells simultaneously and can update over 10 million cells per GPU-second while using an exact Riemann solver and PPM reconstruction. Owing to the massively parallel architecture of GPUs and the design of the Cholla code, astrophysical simulations with physically interesting grid resolutions (≳256{sup 3}) can easily be computed on a single device. We use the Message Passing Interface library to extend calculations onto multiple devices and demonstrate nearly ideal scaling beyond 64 GPUs. A suite of test problems highlights the physical accuracy of our modeling and provides a useful comparison to other codes. We then use Cholla to simulate the interaction of a shock wave with a gas cloud in the interstellar medium, showing that the evolution of the cloud is highly dependent on its density structure. We reconcile the computed mixing time of a turbulent cloud with a realistic density distribution destroyed by a strong shock with the existing analytic theory for spherical cloud destruction by describing the system in terms of its median gas density.

Phase space simulation of collisionless stellar systems on the massively parallel processor

International Nuclear Information System (INIS)

White, R.L.

1987-01-01

A numerical technique for solving the collisionless Boltzmann equation describing the time evolution of a self gravitating fluid in phase space was implemented on the Massively Parallel Processor (MPP). The code performs calculations for a two dimensional phase space grid (with one space and one velocity dimension). Some results from calculations are presented. The execution speed of the code is comparable to the speed of a single processor of a Cray-XMP. Advantages and disadvantages of the MPP architecture for this type of problem are discussed. The nearest neighbor connectivity of the MPP array does not pose a significant obstacle. Future MPP-like machines should have much more local memory and easier access to staging memory and disks in order to be effective for this type of problem

A quantitative assessment of the Hadoop framework for analyzing massively parallel DNA sequencing data.

Science.gov (United States)

Siretskiy, Alexey; Sundqvist, Tore; Voznesenskiy, Mikhail; Spjuth, Ola

2015-01-01

New high-throughput technologies, such as massively parallel sequencing, have transformed the life sciences into a data-intensive field. The most common e-infrastructure for analyzing this data consists of batch systems that are based on high-performance computing resources; however, the bioinformatics software that is built on this platform does not scale well in the general case. Recently, the Hadoop platform has emerged as an interesting option to address the challenges of increasingly large datasets with distributed storage, distributed processing, built-in data locality, fault tolerance, and an appealing programming methodology. In this work we introduce metrics and report on a quantitative comparison between Hadoop and a single node of conventional high-performance computing resources for the tasks of short read mapping and variant calling. We calculate efficiency as a function of data size and observe that the Hadoop platform is more efficient for biologically relevant data sizes in terms of computing hours for both split and un-split data files. We also quantify the advantages of the data locality provided by Hadoop for NGS problems, and show that a classical architecture with network-attached storage will not scale when computing resources increase in numbers. Measurements were performed using ten datasets of different sizes, up to 100 gigabases, using the pipeline implemented in Crossbow. To make a fair comparison, we implemented an improved preprocessor for Hadoop with better performance for splittable data files. For improved usability, we implemented a graphical user interface for Crossbow in a private cloud environment using the CloudGene platform. All of the code and data in this study are freely available as open source in public repositories. From our experiments we can conclude that the improved Hadoop pipeline scales better than the same pipeline on high-performance computing resources, we also conclude that Hadoop is an economically viable

Animated computer graphics models of space and earth sciences data generated via the massively parallel processor

Science.gov (United States)

Treinish, Lloyd A.; Gough, Michael L.; Wildenhain, W. David

1987-01-01

The capability was developed of rapidly producing visual representations of large, complex, multi-dimensional space and earth sciences data sets via the implementation of computer graphics modeling techniques on the Massively Parallel Processor (MPP) by employing techniques recently developed for typically non-scientific applications. Such capabilities can provide a new and valuable tool for the understanding of complex scientific data, and a new application of parallel computing via the MPP. A prototype system with such capabilities was developed and integrated into the National Space Science Data Center's (NSSDC) Pilot Climate Data System (PCDS) data-independent environment for computer graphics data display to provide easy access to users. While developing these capabilities, several problems had to be solved independently of the actual use of the MPP, all of which are outlined.

Massively Parallel Assimilation of TOGA/TAO and Topex/Poseidon Measurements into a Quasi Isopycnal Ocean General Circulation Model Using an Ensemble Kalman Filter

Science.gov (United States)

Keppenne, Christian L.; Rienecker, Michele; Borovikov, Anna Y.; Suarez, Max

1999-01-01

A massively parallel ensemble Kalman filter (EnKF)is used to assimilate temperature data from the TOGA/TAO array and altimetry from TOPEX/POSEIDON into a Pacific basin version of the NASA Seasonal to Interannual Prediction Project (NSIPP)ls quasi-isopycnal ocean general circulation model. The EnKF is an approximate Kalman filter in which the error-covariance propagation step is modeled by the integration of multiple instances of a numerical model. An estimate of the true error covariances is then inferred from the distribution of the ensemble of model state vectors. This inplementation of the filter takes advantage of the inherent parallelism in the EnKF algorithm by running all the model instances concurrently. The Kalman filter update step also occurs in parallel by having each processor process the observations that occur in the region of physical space for which it is responsible. The massively parallel data assimilation system is validated by withholding some of the data and then quantifying the extent to which the withheld information can be inferred from the assimilation of the remaining data. The distributions of the forecast and analysis error covariances predicted by the ENKF are also examined.

Identification of the bovine Arachnomelia mutation by massively parallel sequencing implicates sulfite oxidase (SUOX in bone development.

Directory of Open Access Journals (Sweden)

Cord Drögemüller

2010-08-01

Full Text Available Arachnomelia is a monogenic recessive defect of skeletal development in cattle. The causative mutation was previously mapped to a ∼7 Mb interval on chromosome 5. Here we show that array-based sequence capture and massively parallel sequencing technology, combined with the typical family structure in livestock populations, facilitates the identification of the causative mutation. We re-sequenced the entire critical interval in a healthy partially inbred cow carrying one copy of the critical chromosome segment in its ancestral state and one copy of the same segment with the arachnomelia mutation, and we detected a single heterozygous position. The genetic makeup of several partially inbred cattle provides extremely strong support for the causality of this mutation. The mutation represents a single base insertion leading to a premature stop codon in the coding sequence of the SUOX gene and is perfectly associated with the arachnomelia phenotype. Our findings suggest an important role for sulfite oxidase in bone development.

Identification of the Bovine Arachnomelia Mutation by Massively Parallel Sequencing Implicates Sulfite Oxidase (SUOX) in Bone Development

Science.gov (United States)

Drögemüller, Cord; Tetens, Jens; Sigurdsson, Snaevar; Gentile, Arcangelo; Testoni, Stefania; Lindblad-Toh, Kerstin; Leeb, Tosso

2010-01-01

Arachnomelia is a monogenic recessive defect of skeletal development in cattle. The causative mutation was previously mapped to a ∼7 Mb interval on chromosome 5. Here we show that array-based sequence capture and massively parallel sequencing technology, combined with the typical family structure in livestock populations, facilitates the identification of the causative mutation. We re-sequenced the entire critical interval in a healthy partially inbred cow carrying one copy of the critical chromosome segment in its ancestral state and one copy of the same segment with the arachnomelia mutation, and we detected a single heterozygous position. The genetic makeup of several partially inbred cattle provides extremely strong support for the causality of this mutation. The mutation represents a single base insertion leading to a premature stop codon in the coding sequence of the SUOX gene and is perfectly associated with the arachnomelia phenotype. Our findings suggest an important role for sulfite oxidase in bone development. PMID:20865119

Development of an ELA-DRA gene typing method based on pyrosequencing technology.

Science.gov (United States)

Díaz, S; Echeverría, M G; It, V; Posik, D M; Rogberg-Muñoz, A; Pena, N L; Peral-García, P; Vega-Pla, J L; Giovambattista, G

2008-11-01

The polymorphism of equine lymphocyte antigen (ELA) class II DRA gene had been detected by polymerase chain reaction-single-strand conformational polymorphism (PCR-SSCP) and reference strand-mediated conformation analysis. These methodologies allowed to identify 11 ELA-DRA exon 2 sequences, three of which are widely distributed among domestic horse breeds. Herein, we describe the development of a pyrosequencing-based method applicable to ELA-DRA typing, by screening samples from eight different horse breeds previously typed by PCR-SSCP. This sequence-based method would be useful in high-throughput genotyping of major histocompatibility complex genes in horses and other animal species, making this system interesting as a rapid screening method for animal genotyping of immune-related genes.

Detection of arboviruses and other micro-organisms in experimentally infected mosquitoes using massively parallel sequencing.

Directory of Open Access Journals (Sweden)

Sonja Hall-Mendelin

Full Text Available Human disease incidence attributed to arbovirus infection is increasing throughout the world, with effective control interventions limited by issues of sustainability, insecticide resistance and the lack of effective vaccines. Several promising control strategies are currently under development, such as the release of mosquitoes trans-infected with virus-blocking Wolbachia bacteria. Implementation of any control program is dependent on effective virus surveillance and a thorough understanding of virus-vector interactions. Massively parallel sequencing has enormous potential for providing comprehensive genomic information that can be used to assess many aspects of arbovirus ecology, as well as to evaluate novel control strategies. To demonstrate proof-of-principle, we analyzed Aedes aegypti or Aedes albopictus experimentally infected with dengue, yellow fever or chikungunya viruses. Random amplification was used to prepare sufficient template for sequencing on the Personal Genome Machine. Viral sequences were present in all infected mosquitoes. In addition, in most cases, we were also able to identify the mosquito species and mosquito micro-organisms, including the bacterial endosymbiont Wolbachia. Importantly, naturally occurring Wolbachia strains could be differentiated from strains that had been trans-infected into the mosquito. The method allowed us to assemble near full-length viral genomes and detect other micro-organisms without prior sequence knowledge, in a single reaction. This is a step toward the application of massively parallel sequencing as an arbovirus surveillance tool. It has the potential to provide insight into virus transmission dynamics, and has applicability to the post-release monitoring of Wolbachia in mosquito populations.

Running ATLAS workloads within massively parallel distributed applications using Athena Multi-Process framework (AthenaMP)

CERN Document Server

Calafiura, Paolo; The ATLAS collaboration; Seuster, Rolf; Tsulaia, Vakhtang; van Gemmeren, Peter

2015-01-01

AthenaMP is a multi-process version of the ATLAS reconstruction and data analysis framework Athena. By leveraging Linux fork and copy-on-write, it allows the sharing of memory pages between event processors running on the same compute node with little to no change in the application code. Originally targeted to optimize the memory footprint of reconstruction jobs, AthenaMP has demonstrated that it can reduce the memory usage of certain confugurations of ATLAS production jobs by a factor of 2. AthenaMP has also evolved to become the parallel event-processing core of the recently developed ATLAS infrastructure for fine-grained event processing (Event Service) which allows to run AthenaMP inside massively parallel distributed applications on hundreds of compute nodes simultaneously. We present the architecture of AthenaMP, various strategies implemented by AthenaMP for scheduling workload to worker processes (for example: Shared Event Queue and Shared Distributor of Event Tokens) and the usage of AthenaMP in the...

Running ATLAS workloads within massively parallel distributed applications using Athena Multi-Process framework (AthenaMP)

CERN Document Server

Calafiura, Paolo; Seuster, Rolf; Tsulaia, Vakhtang; van Gemmeren, Peter

2015-01-01

AthenaMP is a multi-process version of the ATLAS reconstruction, simulation and data analysis framework Athena. By leveraging Linux fork and copy-on-write, it allows for sharing of memory pages between event processors running on the same compute node with little to no change in the application code. Originally targeted to optimize the memory footprint of reconstruction jobs, AthenaMP has demonstrated that it can reduce the memory usage of certain configurations of ATLAS production jobs by a factor of 2. AthenaMP has also evolved to become the parallel event-processing core of the recently developed ATLAS infrastructure for fine-grained event processing (Event Service) which allows to run AthenaMP inside massively parallel distributed applications on hundreds of compute nodes simultaneously. We present the architecture of AthenaMP, various strategies implemented by AthenaMP for scheduling workload to worker processes (for example: Shared Event Queue and Shared Distributor of Event Tokens) and the usage of Ath...

Genotypic tropism testing by massively parallel sequencing: qualitative and quantitative analysis

Directory of Open Access Journals (Sweden)

Thiele Bernhard

2011-05-01

Full Text Available Abstract Background Inferring viral tropism from genotype is a fast and inexpensive alternative to phenotypic testing. While being highly predictive when performed on clonal samples, sensitivity of predicting CXCR4-using (X4 variants drops substantially in clinical isolates. This is mainly attributed to minor variants not detected by standard bulk-sequencing. Massively parallel sequencing (MPS detects single clones thereby being much more sensitive. Using this technology we wanted to improve genotypic prediction of coreceptor usage. Methods Plasma samples from 55 antiretroviral-treated patients tested for coreceptor usage with the Monogram Trofile Assay were sequenced with standard population-based approaches. Fourteen of these samples were selected for further analysis with MPS. Tropism was predicted from each sequence with geno2pheno[coreceptor]. Results Prediction based on bulk-sequencing yielded 59.1% sensitivity and 90.9% specificity compared to the trofile assay. With MPS, 7600 reads were generated on average per isolate. Minorities of sequences with high confidence in CXCR4-usage were found in all samples, irrespective of phenotype. When using the default false-positive-rate of geno2pheno[coreceptor] (10%, and defining a minority cutoff of 5%, the results were concordant in all but one isolate. Conclusions The combination of MPS and coreceptor usage prediction results in a fast and accurate alternative to phenotypic assays. The detection of X4-viruses in all isolates suggests that coreceptor usage as well as fitness of minorities is important for therapy outcome. The high sensitivity of this technology in combination with a quantitative description of the viral population may allow implementing meaningful cutoffs for predicting response to CCR5-antagonists in the presence of X4-minorities.

Genotypic tropism testing by massively parallel sequencing: qualitative and quantitative analysis.

Science.gov (United States)

Däumer, Martin; Kaiser, Rolf; Klein, Rolf; Lengauer, Thomas; Thiele, Bernhard; Thielen, Alexander

2011-05-13

Inferring viral tropism from genotype is a fast and inexpensive alternative to phenotypic testing. While being highly predictive when performed on clonal samples, sensitivity of predicting CXCR4-using (X4) variants drops substantially in clinical isolates. This is mainly attributed to minor variants not detected by standard bulk-sequencing. Massively parallel sequencing (MPS) detects single clones thereby being much more sensitive. Using this technology we wanted to improve genotypic prediction of coreceptor usage. Plasma samples from 55 antiretroviral-treated patients tested for coreceptor usage with the Monogram Trofile Assay were sequenced with standard population-based approaches. Fourteen of these samples were selected for further analysis with MPS. Tropism was predicted from each sequence with geno2pheno[coreceptor]. Prediction based on bulk-sequencing yielded 59.1% sensitivity and 90.9% specificity compared to the trofile assay. With MPS, 7600 reads were generated on average per isolate. Minorities of sequences with high confidence in CXCR4-usage were found in all samples, irrespective of phenotype. When using the default false-positive-rate of geno2pheno[coreceptor] (10%), and defining a minority cutoff of 5%, the results were concordant in all but one isolate. The combination of MPS and coreceptor usage prediction results in a fast and accurate alternative to phenotypic assays. The detection of X4-viruses in all isolates suggests that coreceptor usage as well as fitness of minorities is important for therapy outcome. The high sensitivity of this technology in combination with a quantitative description of the viral population may allow implementing meaningful cutoffs for predicting response to CCR5-antagonists in the presence of X4-minorities.

High fidelity thermal-hydraulic analysis using CFD and massively parallel computers

International Nuclear Information System (INIS)

Weber, D.P.; Wei, T.Y.C.; Brewster, R.A.; Rock, Daniel T.; Rizwan-uddin

2000-01-01

Thermal-hydraulic analyses play an important role in design and reload analysis of nuclear power plants. These analyses have historically relied on early generation computational fluid dynamics capabilities, originally developed in the 1960s and 1970s. Over the last twenty years, however, dramatic improvements in both computational fluid dynamics codes in the commercial sector and in computing power have taken place. These developments offer the possibility of performing large scale, high fidelity, core thermal hydraulics analysis. Such analyses will allow a determination of the conservatism employed in traditional design approaches and possibly justify the operation of nuclear power systems at higher powers without compromising safety margins. The objective of this work is to demonstrate such a large scale analysis approach using a state of the art CFD code, STAR-CD, and the computing power of massively parallel computers, provided by IBM. A high fidelity representation of a current generation PWR was analyzed with the STAR-CD CFD code and the results were compared to traditional analyses based on the VIPRE code. Current design methodology typically involves a simplified representation of the assemblies, where a single average pin is used in each assembly to determine the hot assembly from a whole core analysis. After determining this assembly, increased refinement is used in the hot assembly, and possibly some of its neighbors, to refine the analysis for purposes of calculating DNBR. This latter calculation is performed with sub-channel codes such as VIPRE. The modeling simplifications that are used involve the approximate treatment of surrounding assemblies and coarse representation of the hot assembly, where the subchannel is the lowest level of discretization. In the high fidelity analysis performed in this study, both restrictions have been removed. Within the hot assembly, several hundred thousand to several million computational zones have been used, to

Space-charge-dominated beam dynamics simulations using the massively parallel processors (MPPs) of the Cray T3D

International Nuclear Information System (INIS)

Liu, H.

1996-01-01

Computer simulations using the multi-particle code PARMELA with a three-dimensional point-by-point space charge algorithm have turned out to be very helpful in supporting injector commissioning and operations at Thomas Jefferson National Accelerator Facility (Jefferson Lab, formerly called CEBAF). However, this algorithm, which defines a typical N 2 problem in CPU time scaling, is very time-consuming when N, the number of macro-particles, is large. Therefore, it is attractive to use massively parallel processors (MPPs) to speed up the simulations. Motivated by this, the authors modified the space charge subroutine for using the MPPs of the Cray T3D. The techniques used to parallelize and optimize the code on the T3D are discussed in this paper. The performance of the code on the T3D is examined in comparison with a Parallel Vector Processing supercomputer of the Cray C90 and an HP 735/15 high-end workstation

Practical parallel computing

CERN Document Server

Morse, H Stephen

1994-01-01

Practical Parallel Computing provides information pertinent to the fundamental aspects of high-performance parallel processing. This book discusses the development of parallel applications on a variety of equipment.Organized into three parts encompassing 12 chapters, this book begins with an overview of the technology trends that converge to favor massively parallel hardware over traditional mainframes and vector machines. This text then gives a tutorial introduction to parallel hardware architectures. Other chapters provide worked-out examples of programs using several parallel languages. Thi

A MapReduce-Based Parallel Frequent Pattern Growth Algorithm for Spatiotemporal Association Analysis of Mobile Trajectory Big Data

Directory of Open Access Journals (Sweden)

Dawen Xia

2018-01-01

Full Text Available Frequent pattern mining is an effective approach for spatiotemporal association analysis of mobile trajectory big data in data-driven intelligent transportation systems. While existing parallel algorithms have been successfully applied to frequent pattern mining of large-scale trajectory data, two major challenges are how to overcome the inherent defects of Hadoop to cope with taxi trajectory big data including massive small files and how to discover the implicitly spatiotemporal frequent patterns with MapReduce. To conquer these challenges, this paper presents a MapReduce-based Parallel Frequent Pattern growth (MR-PFP algorithm to analyze the spatiotemporal characteristics of taxi operating using large-scale taxi trajectories with massive small file processing strategies on a Hadoop platform. More specifically, we first implement three methods, that is, Hadoop Archives (HAR, CombineFileInputFormat (CFIF, and Sequence Files (SF, to overcome the existing defects of Hadoop and then propose two strategies based on their performance evaluations. Next, we incorporate SF into Frequent Pattern growth (FP-growth algorithm and then implement the optimized FP-growth algorithm on a MapReduce framework. Finally, we analyze the characteristics of taxi operating in both spatial and temporal dimensions by MR-PFP in parallel. The results demonstrate that MR-PFP is superior to existing Parallel FP-growth (PFP algorithm in efficiency and scalability.

A massive parallel sequencing workflow for diagnostic genetic testing of mismatch repair genes

Science.gov (United States)

Hansen, Maren F; Neckmann, Ulrike; Lavik, Liss A S; Vold, Trine; Gilde, Bodil; Toft, Ragnhild K; Sjursen, Wenche

2014-01-01

The purpose of this study was to develop a massive parallel sequencing (MPS) workflow for diagnostic analysis of mismatch repair (MMR) genes using the GS Junior system (Roche). A pathogenic variant in one of four MMR genes, (MLH1, PMS2, MSH6, and MSH2), is the cause of Lynch Syndrome (LS), which mainly predispose to colorectal cancer. We used an amplicon-based sequencing method allowing specific and preferential amplification of the MMR genes including PMS2, of which several pseudogenes exist. The amplicons were pooled at different ratios to obtain coverage uniformity and maximize the throughput of a single-GS Junior run. In total, 60 previously identified and distinct variants (substitutions and indels), were sequenced by MPS and successfully detected. The heterozygote detection range was from 19% to 63% and dependent on sequence context and coverage. We were able to distinguish between false-positive and true-positive calls in homopolymeric regions by cross-sample comparison and evaluation of flow signal distributions. In addition, we filtered variants according to a predefined status, which facilitated variant annotation. Our study shows that implementation of MPS in routine diagnostics of LS can accelerate sample throughput and reduce costs without compromising sensitivity, compared to Sanger sequencing. PMID:24689082

SWAMP+: multiple subsequence alignment using associative massive parallelism

Energy Technology Data Exchange (ETDEWEB)

Steinfadt, Shannon Irene [Los Alamos National Laboratory; Baker, Johnnie W [KENT STATE UNIV.

2010-10-18

A new parallel algorithm SWAMP+ incorporates the Smith-Waterman sequence alignment on an associative parallel model known as ASC. It is a highly sensitive parallel approach that expands traditional pairwise sequence alignment. This is the first parallel algorithm to provide multiple non-overlapping, non-intersecting subsequence alignments with the accuracy of Smith-Waterman. The efficient algorithm provides multiple alignments similar to BLAST while creating a better workflow for the end users. The parallel portions of the code run in O(m+n) time using m processors. When m = n, the algorithmic analysis becomes O(n) with a coefficient of two, yielding a linear speedup. Implementation of the algorithm on the SIMD ClearSpeed CSX620 confirms this theoretical linear speedup with real timings.

Metabarcoding Analysis of Phytophthora Diversity Using Genus-Specific Primers and 454 Pyrosequencing.

Science.gov (United States)

Prigigallo, Maria I; Abdelfattah, Ahmed; Cacciola, Santa O; Faedda, Roberto; Sanzani, Simona M; Cooke, David E L; Schena, L

2016-03-01

A metabarcoding method based on genus-specific primers and 454 pyrosequencing was utilized to investigate the genetic diversity of Phytophthora spp. in soil and root samples of potted plants, from eight nurseries. Pyrosequencing enabled the detection of 25 Phytophthora phylotypes distributed in seven different clades and provided a much higher resolution than a corresponding cloning/Sanger sequencing approach. Eleven of these phylotypes, including P. cactorum, P. citricola s.str., P. palmivora, P. palmivora-like, P. megasperma or P. gonapodyides, P. ramorum, and five putative new Phytophthora species phylogenetically related to clades 1, 2, 4, 6, and 7 were detected only with the 454 pyrosequencing approach. We also found an additional 18 novel records of a phylotype in a particular nursery that were not detected with cloning/Sanger sequencing. Several aspects confirmed the reliability of the method: (i) many identical sequence types were identified independently in different nurseries, (ii) most sequence types identified with 454 pyrosequencing were identical to those from the cloning/Sanger sequencing approach and/or perfectly matched GenBank deposited sequences, and (iii) the divergence noted between sequence types of putative new Phytophthora species and all other detected sequences was sufficient to rule out sequencing errors. The proposed method represents a powerful tool to study Phytophthora diversity providing that particular attention is paid to the analysis of 454 pyrosequencing raw read sequences and to the identification of sequence types.

Parallel computing works!

CERN Document Server

Fox, Geoffrey C; Messina, Guiseppe C

2014-01-01

A clear illustration of how parallel computers can be successfully appliedto large-scale scientific computations. This book demonstrates how avariety of applications in physics, biology, mathematics and other scienceswere implemented on real parallel computers to produce new scientificresults. It investigates issues of fine-grained parallelism relevant forfuture supercomputers with particular emphasis on hypercube architecture. The authors describe how they used an experimental approach to configuredifferent massively parallel machines, design and implement basic systemsoftware, and develop

Three pillars for achieving quantum mechanical molecular dynamics simulations of huge systems: Divide-and-conquer, density-functional tight-binding, and massively parallel computation.

Science.gov (United States)

Nishizawa, Hiroaki; Nishimura, Yoshifumi; Kobayashi, Masato; Irle, Stephan; Nakai, Hiromi

2016-08-05

The linear-scaling divide-and-conquer (DC) quantum chemical methodology is applied to the density-functional tight-binding (DFTB) theory to develop a massively parallel program that achieves on-the-fly molecular reaction dynamics simulations of huge systems from scratch. The functions to perform large scale geometry optimization and molecular dynamics with DC-DFTB potential energy surface are implemented to the program called DC-DFTB-K. A novel interpolation-based algorithm is developed for parallelizing the determination of the Fermi level in the DC method. The performance of the DC-DFTB-K program is assessed using a laboratory computer and the K computer. Numerical tests show the high efficiency of the DC-DFTB-K program, a single-point energy gradient calculation of a one-million-atom system is completed within 60 s using 7290 nodes of the K computer. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

PFLOTRAN User Manual: A Massively Parallel Reactive Flow and Transport Model for Describing Surface and Subsurface Processes

Energy Technology Data Exchange (ETDEWEB)

Lichtner, Peter C. [OFM Research, Redmond, WA (United States); Hammond, Glenn E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lu, Chuan [Idaho National Lab. (INL), Idaho Falls, ID (United States); Karra, Satish [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Bisht, Gautam [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Andre, Benjamin [National Center for Atmospheric Research, Boulder, CO (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Mills, Richard [Intel Corporation, Portland, OR (United States); Univ. of Tennessee, Knoxville, TN (United States); Kumar, Jitendra [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2015-01-20

PFLOTRAN solves a system of generally nonlinear partial differential equations describing multi-phase, multicomponent and multiscale reactive flow and transport in porous materials. The code is designed to run on massively parallel computing architectures as well as workstations and laptops (e.g. Hammond et al., 2011). Parallelization is achieved through domain decomposition using the PETSc (Portable Extensible Toolkit for Scientific Computation) libraries for the parallelization framework (Balay et al., 1997). PFLOTRAN has been developed from the ground up for parallel scalability and has been run on up to 218 processor cores with problem sizes up to 2 billion degrees of freedom. Written in object oriented Fortran 90, the code requires the latest compilers compatible with Fortran 2003. At the time of this writing this requires gcc 4.7.x, Intel 12.1.x and PGC compilers. As a requirement of running problems with a large number of degrees of freedom, PFLOTRAN allows reading input data that is too large to fit into memory allotted to a single processor core. The current limitation to the problem size PFLOTRAN can handle is the limitation of the HDF5 file format used for parallel IO to 32 bit integers. Noting that 2³² = 4; 294; 967; 296, this gives an estimate of the maximum problem size that can be currently run with PFLOTRAN. Hopefully this limitation will be remedied in the near future.

Pyrosequencing for classification of human FcγRIIIA allotypes: a comparison with PCR-based techniques.

Science.gov (United States)

Matlawska-Wasowska, Ksenia; Gale, James M; Nickl, Christian K; Khalili, Parisa; Shirley, Brian; Wilson, Bridget S; Vasef, Mohammad A; Winter, Stuart S

2014-12-01

Surface-specific antigens expressed by hematopoietic cells are attractive targets for antibody-mediated immunotherapy. Monoclonal antibodies (mAbs) involve various mechanisms to eliminate target cells, including antibody-dependent cellular cytotoxicity (ADCC)- and phagocytosis (ADCP)-mediated killing through natural killer (NK) and macrophage effector cells bearing FcγRIIIA (CD16). The clinical efficacy of ADCC is particularly impacted by a single nucleotide polymorphism (SNP) found in the gene encoding FcγRIIIA (FCGR3A), which generates a variable distribution of the 158 V/V, F/V or F/F CD16 allotypes (F = phenylalanine, V = valine) in the normal human population. Currently, most patients are not screened for CD16 allotypes, creating the potential to include in their treatment a mAb-based therapy that may have limited benefit. Therefore, it is important to identify CD16 allotypes when considering mAb therapies that require ADCC/ADCP. The objective of this study was to develop a reliable PCR-based assay for classification of human FcγRIIIA allotypes. We studied 42 normal human subjects for the incidence of FcγRIIIA-158 polymorphisms using comparative molecular approaches. The results of our study showed 100% accuracy in genotyping by pyrosequencing. In contrast, nested PCR-based allele-specific restriction assay and quantitative PCR techniques proved to be relatively less sensitive and less specific in distinguishing variant genotypes. Since the efficacy of the mAb-based targeted immunotherapy may be highly dependent upon the CD16 polymorphism in a given individual, we recommend pyrosequencing for CD16 allotype testing.

Integrated massively parallel sequencing of 15 autosomal STRs and Amelogenin using a simplified library preparation approach.

Science.gov (United States)

Xue, Jian; Wu, Riga; Pan, Yajiao; Wang, Shunxia; Qu, Baowang; Qin, Ying; Shi, Yuequn; Zhang, Chuchu; Li, Ran; Zhang, Liyan; Zhou, Cheng; Sun, Hongyu

2018-04-02

Massively parallel sequencing (MPS) technologies, also termed as next-generation sequencing (NGS), are becoming increasingly popular in study of short tandem repeats (STR). However, current library preparation methods are usually based on ligation or two-round PCR that requires more steps, making it time-consuming (about 2 days), laborious and expensive. In this study, a 16-plex STR typing system was designed with fusion primer strategy based on the Ion Torrent S5 XL platform which could effectively resolve the above challenges for forensic DNA database-type samples (bloodstains, saliva stains, etc.). The efficiency of this system was tested in 253 Han Chinese participants. The libraries were prepared without DNA isolation and adapter ligation, and the whole process only required approximately 5 h. The proportion of thoroughly genotyped samples in which all the 16 loci were successfully genotyped was 86% (220/256). Of the samples, 99.7% showed 100% concordance between NGS-based STR typing and capillary electrophoresis (CE)-based STR typing. The inconsistency might have been caused by off-ladder alleles and mutations in primer binding sites. Overall, this panel enabled the large-scale genotyping of the DNA samples with controlled quality and quantity because it is a simple, operation-friendly process flow that saves labor, time and costs. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Strategien zur HLA-Typisierung mit PyrosequencingTM

OpenAIRE

Entz, Patricia

2006-01-01

Der Haupthistokompatibilitätskomplex ist durch seine biologische Funktion eine für die Diagnostik und Forschung äußerst wichtige Region im humanen Genom. Die Untersuchung von HLA-Genorten stellt ein wichtiges Instrument in der molekulargenetischen Praxis dar. Die Pyrosequencing-Technik ist gut geeignet, um kurze DNA-Abschnitte mit weitgehend bekannter Sequenz schnell und effizient zu untersuchen. Ziel dieser Arbeit war die Entwicklung von Pyrosequencing-basierten Methoden zur HLA-Typisierung....

Frequency of Usher syndrome type 1 in deaf children by massively parallel DNA sequencing.

Science.gov (United States)

Yoshimura, Hidekane; Miyagawa, Maiko; Kumakawa, Kozo; Nishio, Shin-Ya; Usami, Shin-Ichi

2016-05-01

Usher syndrome type 1 (USH1) is the most severe of the three USH subtypes due to its profound hearing loss, absent vestibular response and retinitis pigmentosa appearing at a prepubescent age. Six causative genes have been identified for USH1, making early diagnosis and therapy possible through DNA testing. Targeted exon sequencing of selected genes using massively parallel DNA sequencing (MPS) technology enables clinicians to systematically tackle previously intractable monogenic disorders and improve molecular diagnosis. Using MPS along with direct sequence analysis, we screened 227 unrelated non-syndromic deaf children and detected recessive mutations in USH1 causative genes in five patients (2.2%): three patients harbored MYO7A mutations and one each carried CDH23 or PCDH15 mutations. As indicated by an earlier genotype-phenotype correlation study of the CDH23 and PCDH15 genes, we considered the latter two patients to have USH1. Based on clinical findings, it was also highly likely that one patient with MYO7A mutations possessed USH1 due to a late onset age of walking. This first report describing the frequency (1.3-2.2%) of USH1 among non-syndromic deaf children highlights the importance of comprehensive genetic testing for early disease diagnosis.

Inter-laboratory evaluation of the EUROFORGEN Global ancestry-informative SNP panel by massively parallel sequencing using the Ion PGM™.

Science.gov (United States)

Eduardoff, M; Gross, T E; Santos, C; de la Puente, M; Ballard, D; Strobl, C; Børsting, C; Morling, N; Fusco, L; Hussing, C; Egyed, B; Souto, L; Uacyisrael, J; Syndercombe Court, D; Carracedo, Á; Lareu, M V; Schneider, P M; Parson, W; Phillips, C; Parson, W; Phillips, C

2016-07-01

The EUROFORGEN Global ancestry-informative SNP (AIM-SNPs) panel is a forensic multiplex of 128 markers designed to differentiate an individual's ancestry from amongst the five continental population groups of Africa, Europe, East Asia, Native America, and Oceania. A custom multiplex of AmpliSeq™ PCR primers was designed for the Global AIM-SNPs to perform massively parallel sequencing using the Ion PGM™ system. This study assessed individual SNP genotyping precision using the Ion PGM™, the forensic sensitivity of the multiplex using dilution series, degraded DNA plus simple mixtures, and the ancestry differentiation power of the final panel design, which required substitution of three original ancestry-informative SNPs with alternatives. Fourteen populations that had not been previously analyzed were genotyped using the custom multiplex and these studies allowed assessment of genotyping performance by comparison of data across five laboratories. Results indicate a low level of genotyping error can still occur from sequence misalignment caused by homopolymeric tracts close to the target SNP, despite careful scrutiny of candidate SNPs at the design stage. Such sequence misalignment required the exclusion of component SNP rs2080161 from the Global AIM-SNPs panel. However, the overall genotyping precision and sensitivity of this custom multiplex indicates the Ion PGM™ assay for the Global AIM-SNPs is highly suitable for forensic ancestry analysis with massively parallel sequencing. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE

Directory of Open Access Journals (Sweden)

Pietro Quaglio

2017-05-01

Full Text Available Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs. STPs are hypothesized to play a role in the communication of information in the computational process operated by the cerebral cortex. A variety of statistical methods for the detection of STPs have been developed and applied to electrophysiological recordings, but such methods scale poorly with the current size of available parallel spike train recordings (more than 100 neurons. In this work, we introduce a novel method capable of overcoming the computational and statistical limits of existing analysis techniques in detecting repeating STPs within massively parallel spike trains (MPST. We employ advanced data mining techniques to efficiently extract repeating sequences of spikes from the data. Then, we introduce and compare two alternative approaches to distinguish statistically significant patterns from chance sequences. The first approach uses a measure known as conceptual stability, of which we investigate a computationally cheap approximation for applications to such large data sets. The second approach is based on the evaluation of pattern statistical significance. In particular, we provide an extension to STPs of a method we recently introduced for the evaluation of statistical significance of synchronous spike patterns. The performance of the two approaches is evaluated in terms of computational load and statistical power on a variety of artificial data sets that replicate specific features of experimental data. Both methods provide an effective and robust procedure for detection of STPs in MPST data. The method based on significance evaluation shows the best overall performance, although at a higher computational cost. We name the novel procedure the spatio-temporal Spike PAttern Detection and Evaluation (SPADE analysis.

Fast Simulation of Large-Scale Floods Based on GPU Parallel Computing

Directory of Open Access Journals (Sweden)

Qiang Liu

2018-05-01

Full Text Available Computing speed is a significant issue of large-scale flood simulations for real-time response to disaster prevention and mitigation. Even today, most of the large-scale flood simulations are generally run on supercomputers due to the massive amounts of data and computations necessary. In this work, a two-dimensional shallow water model based on an unstructured Godunov-type finite volume scheme was proposed for flood simulation. To realize a fast simulation of large-scale floods on a personal computer, a Graphics Processing Unit (GPU-based, high-performance computing method using the OpenACC application was adopted to parallelize the shallow water model. An unstructured data management method was presented to control the data transportation between the GPU and CPU (Central Processing Unit with minimum overhead, and then both computation and data were offloaded from the CPU to the GPU, which exploited the computational capability of the GPU as much as possible. The parallel model was validated using various benchmarks and real-world case studies. The results demonstrate that speed-ups of up to one order of magnitude can be achieved in comparison with the serial model. The proposed parallel model provides a fast and reliable tool with which to quickly assess flood hazards in large-scale areas and, thus, has a bright application prospect for dynamic inundation risk identification and disaster assessment.

Streaming Parallel GPU Acceleration of Large-Scale filter-based Spiking Neural Networks

NARCIS (Netherlands)

L.P. Slazynski (Leszek); S.M. Bohte (Sander)

2012-01-01

htmlabstractThe arrival of graphics processing (GPU) cards suitable for massively parallel computing promises a↵ordable large-scale neural network simulation previously only available at supercomputing facil- ities. While the raw numbers suggest that GPUs may outperform CPUs by at least an order of

Characterization of Olkiluoto bacterial and archaeal communities by 454 pyrosequencing

Energy Technology Data Exchange (ETDEWEB)

Bomberg, M.; Nyyssoenen, M.; Itaevaara, M. [VTT Technical Research Centre of Finland, Espoo (Finland)

2012-06-15

Recent advancement in sequencing technologies, 'Next Generation Sequencing', such as FLX 454 pyrosequencing has made it possible to obtain large amounts of sequence data where previously only few sequences could be obtained. This technique is especially useful for the study of community composition of uncultured microbial populations in environmental samples. In this project, the FLX 454 pyrosequencing technique was used to obtain up to 20 000 16S rRNA sequences or 10 000 mRNA sequences from each sample for identification of the microbial species composition as well as for comparison of the microbial communities between different samples. This project focused on the characterization of active microbial communities in the groundwater at the final disposal site of high radioactive wastes in Olkiluoto by FLX 454 pyrosequencing of the bacterial and archaeal ribosomal RNA as well as of the mRNA transcripts of the dsrB gene and mcrA gene of sulphate reducing bacteria and methanogenic archaea, respectively. Specific emphasis was put on studying the relationship of active and latent sulphate reducers and methanogens by qPCR due to their important roles in deep geobiochemical processes connected to copper corrosion. Seven packered boreholes were sampled anaerobically in Olkiluoto during 2009-2010. Groundwater was pumped from specific depths and the microbial cells werecollected by filtration on a membrane. Active microbial communities were studied based on RNA extracted from the membranes and translated to copy DNA, followed by sequencing by 454 Tag pyrosequencing. A total of 27 different bacterial and 17 archaeal taxonomic groups were detected.

Characterization of Olkiluoto bacterial and archaeal communities by 454 pyrosequencing

Energy Technology Data Exchange (ETDEWEB)

Bomberg, M; Nyyssoenen, M; Itaevaara, M [VTT Technical Research Centre of Finland, Espoo (Finland)

2012-06-15

Recent advancement in sequencing technologies, 'Next Generation Sequencing', such as FLX 454 pyrosequencing has made it possible to obtain large amounts of sequence data where previously only few sequences could be obtained. This technique is especially useful for the study of community composition of uncultured microbial populations in environmental samples. In this project, the FLX 454 pyrosequencing technique was used to obtain up to 20 000 16S rRNA sequences or 10 000 mRNA sequences from each sample for identification of the microbial species composition as well as for comparison of the microbial communities between different samples. This project focused on the characterization of active microbial communities in the groundwater at the final disposal site of high radioactive wastes in Olkiluoto by FLX 454 pyrosequencing of the bacterial and archaeal ribosomal RNA as well as of the mRNA transcripts of the dsrB gene and mcrA gene of sulphate reducing bacteria and methanogenic archaea, respectively. Specific emphasis was put on studying the relationship of active and latent sulphate reducers and methanogens by qPCR due to their important roles in deep geobiochemical processes connected to copper corrosion. Seven packered boreholes were sampled anaerobically in Olkiluoto during 2009-2010. Groundwater was pumped from specific depths and the microbial cells werecollected by filtration on a membrane. Active microbial communities were studied based on RNA extracted from the membranes and translated to copy DNA, followed by sequencing by 454 Tag pyrosequencing. A total of 27 different bacterial and 17 archaeal taxonomic groups were detected.

Characterization of Olkiluoto bacterial and archaeal communities by 454 pyrosequencing

International Nuclear Information System (INIS)

Bomberg, M.; Nyyssoenen, M.; Itaevaara, M.

2012-06-01

Recent advancement in sequencing technologies, 'Next Generation Sequencing', such as FLX 454 pyrosequencing has made it possible to obtain large amounts of sequence data where previously only few sequences could be obtained. This technique is especially useful for the study of community composition of uncultured microbial populations in environmental samples. In this project, the FLX 454 pyrosequencing technique was used to obtain up to 20 000 16S rRNA sequences or 10 000 mRNA sequences from each sample for identification of the microbial species composition as well as for comparison of the microbial communities between different samples. This project focused on the characterization of active microbial communities in the groundwater at the final disposal site of high radioactive wastes in Olkiluoto by FLX 454 pyrosequencing of the bacterial and archaeal ribosomal RNA as well as of the mRNA transcripts of the dsrB gene and mcrA gene of sulphate reducing bacteria and methanogenic archaea, respectively. Specific emphasis was put on studying the relationship of active and latent sulphate reducers and methanogens by qPCR due to their important roles in deep geobiochemical processes connected to copper corrosion. Seven packered boreholes were sampled anaerobically in Olkiluoto during 2009-2010. Groundwater was pumped from specific depths and the microbial cells werecollected by filtration on a membrane. Active microbial communities were studied based on RNA extracted from the membranes and translated to copy DNA, followed by sequencing by 454 Tag pyrosequencing. A total of 27 different bacterial and 17 archaeal taxonomic groups were detected

Introduction to massively-parallel computing in high-energy physics

CERN Document Server

AUTHOR|(CDS)2083520

1993-01-01

Ever since computers were first used for scientific and numerical work, there has existed an "arms race" between the technical development of faster computing hardware, and the desires of scientists to solve larger problems in shorter time-scales. However, the vast leaps in processor performance achieved through advances in semi-conductor science have reached a hiatus as the technology comes up against the physical limits of the speed of light and quantum effects. This has lead all high performance computer manufacturers to turn towards a parallel architecture for their new machines. In these lectures we will introduce the history and concepts behind parallel computing, and review the various parallel architectures and software environments currently available. We will then introduce programming methodologies that allow efficient exploitation of parallel machines, and present case studies of the parallelization of typical High Energy Physics codes for the two main classes of parallel computing architecture (S...

Lessons learned from microsatellite development for nonmodel organisms using 454 pyrosequencing

Czech Academy of Sciences Publication Activity Database

Schoebel, C. N.; Brodbeck, S.; Buehler, D.; Cornejo, C.; Gajurel, J.; Hartikainen, H.; Keller, D.; Leys, M.; Říčanová, Štěpánka; Segelbacher, G.; Werth, S.; Csencsics, D.

2013-01-01

Roč. 26, č. 3 (2013), s. 600-611 ISSN 1010-061X Institutional support: RVO:68081766 Keywords : comparative studies * conservation genetics * massively parallel sequencing * next generation sequencing technology * population genetics * shotgun sequencing Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.483, year: 2013

A Parallel Adaboost-Backpropagation Neural Network for Massive Image Dataset Classification

Science.gov (United States)

Cao, Jianfang; Chen, Lichao; Wang, Min; Shi, Hao; Tian, Yun

2016-01-01

Image classification uses computers to simulate human understanding and cognition of images by automatically categorizing images. This study proposes a faster image classification approach that parallelizes the traditional Adaboost-Backpropagation (BP) neural network using the MapReduce parallel programming model. First, we construct a strong classifier by assembling the outputs of 15 BP neural networks (which are individually regarded as weak classifiers) based on the Adaboost algorithm. Second, we design Map and Reduce tasks for both the parallel Adaboost-BP neural network and the feature extraction algorithm. Finally, we establish an automated classification model by building a Hadoop cluster. We use the Pascal VOC2007 and Caltech256 datasets to train and test the classification model. The results are superior to those obtained using traditional Adaboost-BP neural network or parallel BP neural network approaches. Our approach increased the average classification accuracy rate by approximately 14.5% and 26.0% compared to the traditional Adaboost-BP neural network and parallel BP neural network, respectively. Furthermore, the proposed approach requires less computation time and scales very well as evaluated by speedup, sizeup and scaleup. The proposed approach may provide a foundation for automated large-scale image classification and demonstrates practical value. PMID:27905520

Microplanktonic community structure in a coastal system relative to a Phaeocystis bloom inferred from morphological and tag pyrosequencing methods.

Directory of Open Access Journals (Sweden)

Sébastien Monchy

Full Text Available BACKGROUND: Massive phytoplankton blooms, like the recurrent Phaeocystis proliferation observed every year in the Eastern English Channel (EEC, have a significant influence on the overall planktonic community structure and their food web dynamics. As well as being an important area for local fisheries, the EEC is an ideal ecosystem for work on microbial diversity. This is because, although its environmental context is relatively complex, it is reasonably well understood due to several years of monitoring and morphological observations of its planktonic organisms. The objective of our study was to better understand the under-explored microbial eukaryotic diversity relative to the Phaeocystis bloom. METHODOLOGY AND PRINCIPAL FINDINGS: The community structure of microplankton (diatoms, haptophytes, ciliates and dinoflagellates was studied through morphological observations and tag pyrosequencing. During the annual Phaeocystis spring bloom, the phytoplankton biomass increased by 34-fold, while the microzooplankton biomass showed a 4-fold increase, representing on average about 4.6% of the biomass of their phytoplankton prey. Tag pyrosequencing unveiled an extensive diversity of Gymnodiniaceae, with G. spirale and G. fusiformis representing the most abundant reads. An extended diversity of Phaeocystales, with partial 18S rDNA genes sequence identity as low as 85% was found, with taxa corresponding to P. globosa, but also to unknown Phaeocystaceae. CONCLUSIONS: Morphological analyses and pyrosequencing were generally in accordance with capturing frequency shifts of abundant taxa. Tag pyrosequencing allowed highlighting the maintenance of microplankton diversity during the Phaeocystis bloom and the increase of the taxa presenting low number of reads (minor taxa along with the dominant ones in response to biotic and/or abiotic changing conditions. Although molecular approaches have enhanced our perception on diversity, it has come to light that the

Pyrosequencing Based Microbial Community Analysis of Stabilized Mine Soils

Science.gov (United States)

Park, J. E.; Lee, B. T.; Son, A.

2015-12-01

Heavy metals leached from exhausted mines have been causing severe environmental problems in nearby soils and groundwater. Environmental mitigation was performed based on the heavy metal stabilization using Calcite and steel slag in Korea. Since the soil stabilization only temporarily immobilizes the contaminants to soil matrix, the potential risk of re-leaching heavy metal still exists. Therefore the follow-up management of stabilized soils and the corresponding evaluation methods are required to avoid the consequent contamination from the stabilized soils. In this study, microbial community analysis using pyrosequencing was performed for assessing the potential leaching of the stabilized soils. As a result of rarefaction curve and Chao1 and Shannon indices, the stabilized soil has shown lower richness and diversity as compared to non-contaminated negative control. At the phyla level, as the degree of contamination increases, most of phyla decreased with only exception of increased proteobacteria. Among proteobacteria, gamma-proteobacteria increased against the heavy metal contamination. At the species level, Methylobacter tundripaludum of gamma-proteobacteria showed the highest relative portion of microbial community, indicating that methanotrophs may play an important role in either solubilization or immobilization of heavy metals in stabilized soils.

Bacterial flora-typing with targeted, chip-based Pyrosequencing

Directory of Open Access Journals (Sweden)

El-Sayed Yasser Y

2007-11-01

Full Text Available Abstract Background The metagenomic analysis of microbial communities holds the potential to improve our understanding of the role of microbes in clinical conditions. Recent, dramatic improvements in DNA sequencing throughput and cost will enable such analyses on individuals. However, such advances in throughput generally come at the cost of shorter read-lengths, limiting the discriminatory power of each read. In particular, classifying the microbial content of samples by sequencing the Results We describe a method for identifying the phylogenetic content of bacterial samples using high-throughput Pyrosequencing targeted at the 16S rRNA gene. Our analysis is adapted to the shorter read-lengths of such technology and uses a database of 16S rDNA to determine the most specific phylogenetic classification for reads, resulting in a weighted phylogenetic tree characterizing the content of the sample. We present results for six samples obtained from the human vagina during pregnancy that corroborates previous studies using conventional techniques. Next, we analyze the power of our method to classify reads at each level of the phylogeny using simulation experiments. We assess the impacts of read-length and database completeness on our method, and predict how we do as technology improves and more bacteria are sequenced. Finally, we study the utility of targeting specific 16S variable regions and show that such an approach considerably improves results for certain types of microbial samples. Using simulation, our method can be used to determine the most informative variable region. Conclusion This study provides positive validation of the effectiveness of targeting 16S metagenomes using short-read sequencing technology. Our methodology allows us to infer the most specific assignment of the sequence reads within the phylogeny, and to identify the most discriminative variable region to target. The analysis of high-throughput Pyrosequencing on human flora

Analysis of genetically modified organisms by pyrosequencing on a portable photodiode-based bioluminescence sequencer.

Science.gov (United States)

Song, Qinxin; Wei, Guijiang; Zhou, Guohua

2014-07-01

A portable bioluminescence analyser for detecting the DNA sequence of genetically modified organisms (GMOs) was developed by using a photodiode (PD) array. Pyrosequencing on eight genes (zSSIIb, Bt11 and Bt176 gene of genetically modified maize; Lectin, 35S-CTP4, CP4EPSPS, CaMV35S promoter and NOS terminator of the genetically modified Roundup ready soya) was successfully detected with this instrument. The corresponding limit of detection (LOD) was 0.01% with 35 PCR cycles. The maize and soya available from three different provenances in China were detected. The results indicate that pyrosequencing using the small size of the detector is a simple, inexpensive, and reliable way in a farm/field test of GMO analysis. Copyright © 2014 Elsevier Ltd. All rights reserved.

Massively parallel read mapping on GPUs with the q-group index and PEANUT

NARCIS (Netherlands)

J. Köster (Johannes); S. Rahmann (Sven)

2014-01-01

textabstractWe present the q-group index, a novel data structure for read mapping tailored towards graphics processing units (GPUs) with a small memory footprint and efficient parallel algorithms for querying and building. On top of the q-group index we introduce PEANUT, a highly parallel GPU-based

Sliding window analyses for optimal selection of mini-barcodes, and application to 454-pyrosequencing for specimen identification from degraded DNA.

Directory of Open Access Journals (Sweden)

Stephane Boyer

Full Text Available DNA barcoding remains a challenge when applied to diet analyses, ancient DNA studies, environmental DNA samples and, more generally, in any cases where DNA samples have not been adequately preserved. Because the size of the commonly used barcoding marker (COI is over 600 base pairs (bp, amplification fails when the DNA molecule is degraded into smaller fragments. However, relevant information for specimen identification may not be evenly distributed along the barcoding region, and a shorter target can be sufficient for identification purposes. This study proposes a new, widely applicable, method to compare the performance of all potential 'mini-barcodes' for a given molecular marker and to objectively select the shortest and most informative one. Our method is based on a sliding window analysis implemented in the new R package SPIDER (Species IDentity and Evolution in R. This method is applicable to any taxon and any molecular marker. Here, it was tested on earthworm DNA that had been degraded through digestion by carnivorous landsnails. A 100 bp region of 16 S rDNA was selected as the shortest informative fragment (mini-barcode required for accurate specimen identification. Corresponding primers were designed and used to amplify degraded earthworm (prey DNA from 46 landsnail (predator faeces using 454-pyrosequencing. This led to the detection of 18 earthworm species in the diet of the snail. We encourage molecular ecologists to use this method to objectively select the most informative region of the gene they aim to amplify from degraded DNA. The method and tools provided here, can be particularly useful (1 when dealing with degraded DNA for which only small fragments can be amplified, (2 for cases where no consensus has yet been reached on the appropriate barcode gene, or (3 to allow direct analysis of short reads derived from massively parallel sequencing without the need for bioinformatic consolidation.

Sliding window analyses for optimal selection of mini-barcodes, and application to 454-pyrosequencing for specimen identification from degraded DNA.

Science.gov (United States)

Boyer, Stephane; Brown, Samuel D J; Collins, Rupert A; Cruickshank, Robert H; Lefort, Marie-Caroline; Malumbres-Olarte, Jagoba; Wratten, Stephen D

2012-01-01

DNA barcoding remains a challenge when applied to diet analyses, ancient DNA studies, environmental DNA samples and, more generally, in any cases where DNA samples have not been adequately preserved. Because the size of the commonly used barcoding marker (COI) is over 600 base pairs (bp), amplification fails when the DNA molecule is degraded into smaller fragments. However, relevant information for specimen identification may not be evenly distributed along the barcoding region, and a shorter target can be sufficient for identification purposes. This study proposes a new, widely applicable, method to compare the performance of all potential 'mini-barcodes' for a given molecular marker and to objectively select the shortest and most informative one. Our method is based on a sliding window analysis implemented in the new R package SPIDER (Species IDentity and Evolution in R). This method is applicable to any taxon and any molecular marker. Here, it was tested on earthworm DNA that had been degraded through digestion by carnivorous landsnails. A 100 bp region of 16 S rDNA was selected as the shortest informative fragment (mini-barcode) required for accurate specimen identification. Corresponding primers were designed and used to amplify degraded earthworm (prey) DNA from 46 landsnail (predator) faeces using 454-pyrosequencing. This led to the detection of 18 earthworm species in the diet of the snail. We encourage molecular ecologists to use this method to objectively select the most informative region of the gene they aim to amplify from degraded DNA. The method and tools provided here, can be particularly useful (1) when dealing with degraded DNA for which only small fragments can be amplified, (2) for cases where no consensus has yet been reached on the appropriate barcode gene, or (3) to allow direct analysis of short reads derived from massively parallel sequencing without the need for bioinformatic consolidation.

Parallel computing by Monte Carlo codes MVP/GMVP

International Nuclear Information System (INIS)

Nagaya, Yasunobu; Nakagawa, Masayuki; Mori, Takamasa

2001-01-01

General-purpose Monte Carlo codes MVP/GMVP are well-vectorized and thus enable us to perform high-speed Monte Carlo calculations. In order to achieve more speedups, we parallelized the codes on the different types of parallel computing platforms or by using a standard parallelization library MPI. The platforms used for benchmark calculations are a distributed-memory vector-parallel computer Fujitsu VPP500, a distributed-memory massively parallel computer Intel paragon and a distributed-memory scalar-parallel computer Hitachi SR2201, IBM SP2. As mentioned generally, linear speedup could be obtained for large-scale problems but parallelization efficiency decreased as the batch size per a processing element(PE) was smaller. It was also found that the statistical uncertainty for assembly powers was less than 0.1% by the PWR full-core calculation with more than 10 million histories and it took about 1.5 hours by massively parallel computing. (author)

Microbial analysis in primary and persistent endodontic infections by using pyrosequencing.

Science.gov (United States)

Hong, Bo-Young; Lee, Tae-Kwon; Lim, Sang-Min; Chang, Seok Woo; Park, Joonhong; Han, Seung Hyun; Zhu, Qiang; Safavi, Kamran E; Fouad, Ashraf F; Kum, Kee Yeon

2013-09-01

The aim of this study was to investigate the bacterial community profile of intracanal microbiota in primary and persistent endodontic infections associated with asymptomatic chronic apical periodontitis by using GS-FLX Titanium pyrosequencing. The null hypothesis was that there is no difference in diversity of overall bacterial community profiles between primary and persistent infections. Pyrosequencing analysis from 10 untreated and 8 root-filled samples was conducted. Analysis from 18 samples yielded total of 124,767 16S rRNA gene sequences (with a mean of 6932 reads per sample) that were taxonomically assigned into 803 operational taxonomic units (3% distinction), 148 genera, and 10 phyla including unclassified. Bacteroidetes was the most abundant phylum in both primary and persistent infections. There were no significant differences in bacterial diversity between the 2 infection groups (P > .05). The bacterial community profile that was based on dendrogram showed that bacterial population in both infections was not significantly different in their structure and composition (P > .05). The present pyrosequencing study demonstrates that persistent infections have as diverse bacterial community as primary infections. Copyright © 2013 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

A task parallel implementation of fast multipole methods

KAUST Repository

Taura, Kenjiro; Nakashima, Jun; Yokota, Rio; Maruyama, Naoya

2012-01-01

This paper describes a task parallel implementation of ExaFMM, an open source implementation of fast multipole methods (FMM), using a lightweight task parallel library MassiveThreads. Although there have been many attempts on parallelizing FMM

Cellular Automata-Based Parallel Random Number Generators Using FPGAs

Directory of Open Access Journals (Sweden)

David H. K. Hoe

2012-01-01

Full Text Available Cellular computing represents a new paradigm for implementing high-speed massively parallel machines. Cellular automata (CA, which consist of an array of locally connected processing elements, are a basic form of a cellular-based architecture. The use of field programmable gate arrays (FPGAs for implementing CA accelerators has shown promising results. This paper investigates the design of CA-based pseudo-random number generators (PRNGs using an FPGA platform. To improve the quality of the random numbers that are generated, the basic CA structure is enhanced in two ways. First, the addition of a superrule to each CA cell is considered. The resulting self-programmable CA (SPCA uses the superrule to determine when to make a dynamic rule change in each CA cell. The superrule takes its inputs from neighboring cells and can be considered itself a second CA working in parallel with the main CA. When implemented on an FPGA, the use of lookup tables in each logic cell removes any restrictions on how the super-rules should be defined. Second, a hybrid configuration is formed by combining a CA with a linear feedback shift register (LFSR. This is advantageous for FPGA designs due to the compactness of the LFSR implementations. A standard software package for statistically evaluating the quality of random number sequences known as Diehard is used to validate the results. Both the SPCA and the hybrid CA/LFSR were found to pass all the Diehard tests.

Feasibility studies for a high energy physics MC program on massive parallel platforms

International Nuclear Information System (INIS)

Bertolotto, L.M.; Peach, K.J.; Apostolakis, J.; Bruschini, C.E.; Calafiura, P.; Gagliardi, F.; Metcalf, M.; Norton, A.; Panzer-Steindel, B.

1994-01-01

The parallelization of a Monte Carlo program for the NA48 experiment is presented. As a first step, a task farming structure was realized. Based on this, a further step, making use of a distributed database for showers in the electro-magnetic calorimeter, was implemented. Further possibilities for using parallel processing for a quasi-real time calibration of the calorimeter are described

Regional-scale calculation of the LS factor using parallel processing

Science.gov (United States)

Liu, Kai; Tang, Guoan; Jiang, Ling; Zhu, A.-Xing; Yang, Jianyi; Song, Xiaodong

2015-05-01

With the increase of data resolution and the increasing application of USLE over large areas, the existing serial implementation of algorithms for computing the LS factor is becoming a bottleneck. In this paper, a parallel processing model based on message passing interface (MPI) is presented for the calculation of the LS factor, so that massive datasets at a regional scale can be processed efficiently. The parallel model contains algorithms for calculating flow direction, flow accumulation, drainage network, slope, slope length and the LS factor. According to the existence of data dependence, the algorithms are divided into local algorithms and global algorithms. Parallel strategy are designed according to the algorithm characters including the decomposition method for maintaining the integrity of the results, optimized workflow for reducing the time taken for exporting the unnecessary intermediate data and a buffer-communication-computation strategy for improving the communication efficiency. Experiments on a multi-node system show that the proposed parallel model allows efficient calculation of the LS factor at a regional scale with a massive dataset.

Allele-Specific DNA Methylation Detection by Pyrosequencing®

DEFF Research Database (Denmark)

Kristensen, Lasse Sommer; Johansen, Jens Vilstrup; Grønbæk, Kirsten

2015-01-01

DNA methylation is an epigenetic modification that plays important roles in healthy as well as diseased cells, by influencing the transcription of genes. In spite the fact that human somatic cells are diploid, most of the currently available methods for the study of DNA methylation do not provide......-effective protocol for allele-specific DNA methylation detection based on Pyrosequencing(®) of methylation-specific PCR (MSP) products including a single nucleotide polymorphism (SNP) within the amplicon....

Massively parallel sequencing and genome-wide copy number analysis revealed a clonal relationship in benign metastasizing leiomyoma

Science.gov (United States)

Lee, Li-Yu; Lin, Gigin; Chen, Shu-Jen; Lu, Yen-Jung; Huang, Huei-Jean; Yen, Chi-Feng; Han, Chien Min; Lee, Yun-Shien; Wang, Tzu-Hao; Chao, Angel

2017-01-01

Benign metastasizing leiomyoma (BML) is a rare disease entity typically presenting as multiple extrauterine leiomyomas associated with a uterine leiomyoma. It has been hypothesized that the extrauterine leiomyomata represent distant metastasis of the uterine leiomyoma. To date, the only molecular evidence supporting this hypothesis was derived from clonality analyses based on X-chromosome inactivation assays. Here, we sought to address this issue by examining paired specimens of synchronous pulmonary and uterine leiomyomata from three patients using targeted massively parallel sequencing and molecular inversion probe array analysis for detecting somatic mutations and copy number aberrations. We detected identical non-hot-spot somatic mutations and similar patterns of copy number aberrations (CNAs) in paired pulmonary and uterine leiomyomata from two patients, indicating the clonal relationship between pulmonary and uterine leiomyomata. In addition to loss of chromosome 22q found in the literature, we identified additional recurrent CNAs including losses of chromosome 3q and 11q. In conclusion, our findings of the clonal relationship between synchronous pulmonary and uterine leiomyomas support the hypothesis that BML represents a condition wherein a uterine leiomyoma disseminates to distant extrauterine locations. PMID:28533481

Massively parallel sequencing and genome-wide copy number analysis revealed a clonal relationship in benign metastasizing leiomyoma.

Science.gov (United States)

Wu, Ren-Chin; Chao, An-Shine; Lee, Li-Yu; Lin, Gigin; Chen, Shu-Jen; Lu, Yen-Jung; Huang, Huei-Jean; Yen, Chi-Feng; Han, Chien Min; Lee, Yun-Shien; Wang, Tzu-Hao; Chao, Angel

2017-07-18

Benign metastasizing leiomyoma (BML) is a rare disease entity typically presenting as multiple extrauterine leiomyomas associated with a uterine leiomyoma. It has been hypothesized that the extrauterine leiomyomata represent distant metastasis of the uterine leiomyoma. To date, the only molecular evidence supporting this hypothesis was derived from clonality analyses based on X-chromosome inactivation assays. Here, we sought to address this issue by examining paired specimens of synchronous pulmonary and uterine leiomyomata from three patients using targeted massively parallel sequencing and molecular inversion probe array analysis for detecting somatic mutations and copy number aberrations. We detected identical non-hot-spot somatic mutations and similar patterns of copy number aberrations (CNAs) in paired pulmonary and uterine leiomyomata from two patients, indicating the clonal relationship between pulmonary and uterine leiomyomata. In addition to loss of chromosome 22q found in the literature, we identified additional recurrent CNAs including losses of chromosome 3q and 11q. In conclusion, our findings of the clonal relationship between synchronous pulmonary and uterine leiomyomas support the hypothesis that BML represents a condition wherein a uterine leiomyoma disseminates to distant extrauterine locations.

A parallel solution for high resolution histological image analysis.

Science.gov (United States)

Bueno, G; González, R; Déniz, O; García-Rojo, M; González-García, J; Fernández-Carrobles, M M; Vállez, N; Salido, J

2012-10-01

This paper describes a general methodology for developing parallel image processing algorithms based on message passing for high resolution images (on the order of several Gigabytes). These algorithms have been applied to histological images and must be executed on massively parallel processing architectures. Advances in new technologies for complete slide digitalization in pathology have been combined with developments in biomedical informatics. However, the efficient use of these digital slide systems is still a challenge. The image processing that these slides are subject to is still limited both in terms of data processed and processing methods. The work presented here focuses on the need to design and develop parallel image processing tools capable of obtaining and analyzing the entire gamut of information included in digital slides. Tools have been developed to assist pathologists in image analysis and diagnosis, and they cover low and high-level image processing methods applied to histological images. Code portability, reusability and scalability have been tested by using the following parallel computing architectures: distributed memory with massive parallel processors and two networks, INFINIBAND and Myrinet, composed of 17 and 1024 nodes respectively. The parallel framework proposed is flexible, high performance solution and it shows that the efficient processing of digital microscopic images is possible and may offer important benefits to pathology laboratories. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Parallel computing of physical maps--a comparative study in SIMD and MIMD parallelism.

Science.gov (United States)

Bhandarkar, S M; Chirravuri, S; Arnold, J

1996-01-01

Ordering clones from a genomic library into physical maps of whole chromosomes presents a central computational problem in genetics. Chromosome reconstruction via clone ordering is usually isomorphic to the NP-complete Optimal Linear Arrangement problem. Parallel SIMD and MIMD algorithms for simulated annealing based on Markov chain distribution are proposed and applied to the problem of chromosome reconstruction via clone ordering. Perturbation methods and problem-specific annealing heuristics are proposed and described. The SIMD algorithms are implemented on a 2048 processor MasPar MP-2 system which is an SIMD 2-D toroidal mesh architecture whereas the MIMD algorithms are implemented on an 8 processor Intel iPSC/860 which is an MIMD hypercube architecture. A comparative analysis of the various SIMD and MIMD algorithms is presented in which the convergence, speedup, and scalability characteristics of the various algorithms are analyzed and discussed. On a fine-grained, massively parallel SIMD architecture with a low synchronization overhead such as the MasPar MP-2, a parallel simulated annealing algorithm based on multiple periodically interacting searches performs the best. For a coarse-grained MIMD architecture with high synchronization overhead such as the Intel iPSC/860, a parallel simulated annealing algorithm based on multiple independent searches yields the best results. In either case, distribution of clonal data across multiple processors is shown to exacerbate the tendency of the parallel simulated annealing algorithm to get trapped in a local optimum.

Massively parallel diffuse optical tomography

Energy Technology Data Exchange (ETDEWEB)

Sandusky, John V.; Pitts, Todd A.

2017-09-05

Diffuse optical tomography systems and methods are described herein. In a general embodiment, the diffuse optical tomography system comprises a plurality of sensor heads, the plurality of sensor heads comprising respective optical emitter systems and respective sensor systems. A sensor head in the plurality of sensors heads is caused to act as an illuminator, such that its optical emitter system transmits a transillumination beam towards a portion of a sample. Other sensor heads in the plurality of sensor heads act as observers, detecting portions of the transillumination beam that radiate from the sample in the fields of view of the respective sensory systems of the other sensor heads. Thus, sensor heads in the plurality of sensors heads generate sensor data in parallel.

Parallel algorithm of real-time infrared image restoration based on total variation theory

Science.gov (United States)

Zhu, Ran; Li, Miao; Long, Yunli; Zeng, Yaoyuan; An, Wei

2015-10-01

Image restoration is a necessary preprocessing step for infrared remote sensing applications. Traditional methods allow us to remove the noise but penalize too much the gradients corresponding to edges. Image restoration techniques based on variational approaches can solve this over-smoothing problem for the merits of their well-defined mathematical modeling of the restore procedure. The total variation (TV) of infrared image is introduced as a L1 regularization term added to the objective energy functional. It converts the restoration process to an optimization problem of functional involving a fidelity term to the image data plus a regularization term. Infrared image restoration technology with TV-L1 model exploits the remote sensing data obtained sufficiently and preserves information at edges caused by clouds. Numerical implementation algorithm is presented in detail. Analysis indicates that the structure of this algorithm can be easily implemented in parallelization. Therefore a parallel implementation of the TV-L1 filter based on multicore architecture with shared memory is proposed for infrared real-time remote sensing systems. Massive computation of image data is performed in parallel by cooperating threads running simultaneously on multiple cores. Several groups of synthetic infrared image data are used to validate the feasibility and effectiveness of the proposed parallel algorithm. Quantitative analysis of measuring the restored image quality compared to input image is presented. Experiment results show that the TV-L1 filter can restore the varying background image reasonably, and that its performance can achieve the requirement of real-time image processing.

[Sensitivity and specificity of nested PCR pyrosequencing in hepatitis B virus drug resistance gene testing].

Science.gov (United States)

Sun, Shumei; Zhou, Hao; Zhou, Bin; Hu, Ziyou; Hou, Jinlin; Sun, Jian

2012-05-01

To evaluate the sensitivity and specificity of nested PCR combined with pyrosequencing in the detection of HBV drug-resistance gene. RtM204I (ATT) mutant and rtM204 (ATG) nonmutant plasmids mixed at different ratios were detected for mutations using nested-PCR combined with pyrosequencing, and the results were compared with those by conventional PCR pyrosequencing to analyze the linearity and consistency of the two methods. Clinical specimens with different viral loads were examined for drug-resistant mutations using nested PCR pyrosequencing and nested PCR combined with dideoxy sequencing (Sanger) for comparison of the detection sensitivity and specificity. The fitting curves demonstrated good linearity of both conventional PCR pyrosequencing and nested PCR pyrosequencing (R(2)>0.99, PNested PCR showed a better consistency with the predicted value than conventional PCR, and was superior to conventional PCR for detection of samples containing 90% mutant plasmid. In the detection of clinical specimens, Sanger sequencing had a significantly lower sensitivity than nested PCR pyrosequencing (92% vs 100%, Pnested PCR and Sanger sequencing method, nested PCR pyrosequencing has a higher sensitivity especially in clinical specimens with low viral copies, which can be important for early detection of HBV mutant strains and hence more effective clinical management.

Parallel processing architecture for H.264 deblocking filter on multi-core platforms

Science.gov (United States)

Prasad, Durga P.; Sonachalam, Sekar; Kunchamwar, Mangesh K.; Gunupudi, Nageswara Rao

2012-03-01

Massively parallel computing (multi-core) chips offer outstanding new solutions that satisfy the increasing demand for high resolution and high quality video compression technologies such as H.264. Such solutions not only provide exceptional quality but also efficiency, low power, and low latency, previously unattainable in software based designs. While custom hardware and Application Specific Integrated Circuit (ASIC) technologies may achieve lowlatency, low power, and real-time performance in some consumer devices, many applications require a flexible and scalable software-defined solution. The deblocking filter in H.264 encoder/decoder poses difficult implementation challenges because of heavy data dependencies and the conditional nature of the computations. Deblocking filter implementations tend to be fixed and difficult to reconfigure for different needs. The ability to scale up for higher quality requirements such as 10-bit pixel depth or a 4:2:2 chroma format often reduces the throughput of a parallel architecture designed for lower feature set. A scalable architecture for deblocking filtering, created with a massively parallel processor based solution, means that the same encoder or decoder will be deployed in a variety of applications, at different video resolutions, for different power requirements, and at higher bit-depths and better color sub sampling patterns like YUV, 4:2:2, or 4:4:4 formats. Low power, software-defined encoders/decoders may be implemented using a massively parallel processor array, like that found in HyperX technology, with 100 or more cores and distributed memory. The large number of processor elements allows the silicon device to operate more efficiently than conventional DSP or CPU technology. This software programing model for massively parallel processors offers a flexible implementation and a power efficiency close to that of ASIC solutions. This work describes a scalable parallel architecture for an H.264 compliant deblocking

Parallel algorithms for interactive manipulation of digital terrain models

Science.gov (United States)

Davis, E. W.; Mcallister, D. F.; Nagaraj, V.

1988-01-01

Interactive three-dimensional graphics applications, such as terrain data representation and manipulation, require extensive arithmetic processing. Massively parallel machines are attractive for this application since they offer high computational rates, and grid connected architectures provide a natural mapping for grid based terrain models. Presented here are algorithms for data movement on the massive parallel processor (MPP) in support of pan and zoom functions over large data grids. It is an extension of earlier work that demonstrated real-time performance of graphics functions on grids that were equal in size to the physical dimensions of the MPP. When the dimensions of a data grid exceed the processing array size, data is packed in the array memory. Windows of the total data grid are interactively selected for processing. Movement of packed data is needed to distribute items across the array for efficient parallel processing. Execution time for data movement was found to exceed that for arithmetic aspects of graphics functions. Performance figures are given for routines written in MPP Pascal.

Position-specific automated processing of V3 env ultra-deep pyrosequencing data for predicting HIV-1 tropism.

Science.gov (United States)

Jeanne, Nicolas; Saliou, Adrien; Carcenac, Romain; Lefebvre, Caroline; Dubois, Martine; Cazabat, Michelle; Nicot, Florence; Loiseau, Claire; Raymond, Stéphanie; Izopet, Jacques; Delobel, Pierre

2015-11-20

HIV-1 coreceptor usage must be accurately determined before starting CCR5 antagonist-based treatment as the presence of undetected minor CXCR4-using variants can cause subsequent virological failure. Ultra-deep pyrosequencing of HIV-1 V3 env allows to detect low levels of CXCR4-using variants that current genotypic approaches miss. However, the computation of the mass of sequence data and the need to identify true minor variants while excluding artifactual sequences generated during amplification and ultra-deep pyrosequencing is rate-limiting. Arbitrary fixed cut-offs below which minor variants are discarded are currently used but the errors generated during ultra-deep pyrosequencing are sequence-dependant rather than random. We have developed an automated processing of HIV-1 V3 env ultra-deep pyrosequencing data that uses biological filters to discard artifactual or non-functional V3 sequences followed by statistical filters to determine position-specific sensitivity thresholds, rather than arbitrary fixed cut-offs. It allows to retain authentic sequences with point mutations at V3 positions of interest and discard artifactual ones with accurate sensitivity thresholds.

Three-dimensional gyrokinetic particle-in-cell simulation of plasmas on a massively parallel computer: Final report on LDRD Core Competency Project, FY 1991--FY 1993

International Nuclear Information System (INIS)

Byers, J.A.; Williams, T.J.; Cohen, B.I.; Dimits, A.M.

1994-01-01

One of the programs of the Magnetic fusion Energy (MFE) Theory and computations Program is studying the anomalous transport of thermal energy across the field lines in the core of a tokamak. We use the method of gyrokinetic particle-in-cell simulation in this study. For this LDRD project we employed massively parallel processing, new algorithms, and new algorithms, and new formal techniques to improve this research. Specifically, we sought to take steps toward: researching experimentally-relevant parameters in our simulations, learning parallel computing to have as a resource for our group, and achieving a 100 x speedup over our starting-point Cray2 simulation code's performance

High-Efficient Parallel CAVLC Encoders on Heterogeneous Multicore Architectures

Directory of Open Access Journals (Sweden)

H. Y. Su

2012-04-01

Full Text Available This article presents two high-efficient parallel realizations of the context-based adaptive variable length coding (CAVLC based on heterogeneous multicore processors. By optimizing the architecture of the CAVLC encoder, three kinds of dependences are eliminated or weaken, including the context-based data dependence, the memory accessing dependence and the control dependence. The CAVLC pipeline is divided into three stages: two scans, coding, and lag packing, and be implemented on two typical heterogeneous multicore architectures. One is a block-based SIMD parallel CAVLC encoder on multicore stream processor STORM. The other is a component-oriented SIMT parallel encoder on massively parallel architecture GPU. Both of them exploited rich data-level parallelism. Experiments results show that compared with the CPU version, more than 70 times of speedup can be obtained for STORM and over 50 times for GPU. The implementation of encoder on STORM can make a real-time processing for 1080p @30fps and GPU-based version can satisfy the requirements for 720p real-time encoding. The throughput of the presented CAVLC encoders is more than 10 times higher than that of published software encoders on DSP and multicore platforms.

TIA: algorithms for development of identity-linked SNP islands for analysis by massively parallel DNA sequencing.

Science.gov (United States)

Farris, M Heath; Scott, Andrew R; Texter, Pamela A; Bartlett, Marta; Coleman, Patricia; Masters, David

2018-04-11

Single nucleotide polymorphisms (SNPs) located within the human genome have been shown to have utility as markers of identity in the differentiation of DNA from individual contributors. Massively parallel DNA sequencing (MPS) technologies and human genome SNP databases allow for the design of suites of identity-linked target regions, amenable to sequencing in a multiplexed and massively parallel manner. Therefore, tools are needed for leveraging the genotypic information found within SNP databases for the discovery of genomic targets that can be evaluated on MPS platforms. The SNP island target identification algorithm (TIA) was developed as a user-tunable system to leverage SNP information within databases. Using data within the 1000 Genomes Project SNP database, human genome regions were identified that contain globally ubiquitous identity-linked SNPs and that were responsive to targeted resequencing on MPS platforms. Algorithmic filters were used to exclude target regions that did not conform to user-tunable SNP island target characteristics. To validate the accuracy of TIA for discovering these identity-linked SNP islands within the human genome, SNP island target regions were amplified from 70 contributor genomic DNA samples using the polymerase chain reaction. Multiplexed amplicons were sequenced using the Illumina MiSeq platform, and the resulting sequences were analyzed for SNP variations. 166 putative identity-linked SNPs were targeted in the identified genomic regions. Of the 309 SNPs that provided discerning power across individual SNP profiles, 74 previously undefined SNPs were identified during evaluation of targets from individual genomes. Overall, DNA samples of 70 individuals were uniquely identified using a subset of the suite of identity-linked SNP islands. TIA offers a tunable genome search tool for the discovery of targeted genomic regions that are scalable in the population frequency and numbers of SNPs contained within the SNP island regions

Removing Noise From Pyrosequenced Amplicons

Directory of Open Access Journals (Sweden)

Davenport Russell J

2011-01-01

Full Text Available Abstract Background In many environmental genomics applications a homologous region of DNA from a diverse sample is first amplified by PCR and then sequenced. The next generation sequencing technology, 454 pyrosequencing, has allowed much larger read numbers from PCR amplicons than ever before. This has revolutionised the study of microbial diversity as it is now possible to sequence a substantial fraction of the 16S rRNA genes in a community. However, there is a growing realisation that because of the large read numbers and the lack of consensus sequences it is vital to distinguish noise from true sequence diversity in this data. Otherwise this leads to inflated estimates of the number of types or operational taxonomic units (OTUs present. Three sources of error are important: sequencing error, PCR single base substitutions and PCR chimeras. We present AmpliconNoise, a development of the PyroNoise algorithm that is capable of separately removing 454 sequencing errors and PCR single base errors. We also introduce a novel chimera removal program, Perseus, that exploits the sequence abundances associated with pyrosequencing data. We use data sets where samples of known diversity have been amplified and sequenced to quantify the effect of each of the sources of error on OTU inflation and to validate these algorithms. Results AmpliconNoise outperforms alternative algorithms substantially reducing per base error rates for both the GS FLX and latest Titanium protocol. All three sources of error lead to inflation of diversity estimates. In particular, chimera formation has a hitherto unrealised importance which varies according to amplification protocol. We show that AmpliconNoise allows accurate estimates of OTU number. Just as importantly AmpliconNoise generates the right OTUs even at low sequence differences. We demonstrate that Perseus has very high sensitivity, able to find 99% of chimeras, which is critical when these are present at high

Parallel plasma fluid turbulence calculations

International Nuclear Information System (INIS)

Leboeuf, J.N.; Carreras, B.A.; Charlton, L.A.; Drake, J.B.; Lynch, V.E.; Newman, D.E.; Sidikman, K.L.; Spong, D.A.

1994-01-01

The study of plasma turbulence and transport is a complex problem of critical importance for fusion-relevant plasmas. To this day, the fluid treatment of plasma dynamics is the best approach to realistic physics at the high resolution required for certain experimentally relevant calculations. Core and edge turbulence in a magnetic fusion device have been modeled using state-of-the-art, nonlinear, three-dimensional, initial-value fluid and gyrofluid codes. Parallel implementation of these models on diverse platforms--vector parallel (National Energy Research Supercomputer Center's CRAY Y-MP C90), massively parallel (Intel Paragon XP/S 35), and serial parallel (clusters of high-performance workstations using the Parallel Virtual Machine protocol)--offers a variety of paths to high resolution and significant improvements in real-time efficiency, each with its own advantages. The largest and most efficient calculations have been performed at the 200 Mword memory limit on the C90 in dedicated mode, where an overlap of 12 to 13 out of a maximum of 16 processors has been achieved with a gyrofluid model of core fluctuations. The richness of the physics captured by these calculations is commensurate with the increased resolution and efficiency and is limited only by the ingenuity brought to the analysis of the massive amounts of data generated

Massively parallel E-beam inspection: enabling next-generation patterned defect inspection for wafer and mask manufacturing

Science.gov (United States)

Malloy, Matt; Thiel, Brad; Bunday, Benjamin D.; Wurm, Stefan; Mukhtar, Maseeh; Quoi, Kathy; Kemen, Thomas; Zeidler, Dirk; Eberle, Anna Lena; Garbowski, Tomasz; Dellemann, Gregor; Peters, Jan Hendrik

2015-03-01

SEMATECH aims to identify and enable disruptive technologies to meet the ever-increasing demands of semiconductor high volume manufacturing (HVM). As such, a program was initiated in 2012 focused on high-speed e-beam defect inspection as a complement, and eventual successor, to bright field optical patterned defect inspection [1]. The primary goal is to enable a new technology to overcome the key gaps that are limiting modern day inspection in the fab; primarily, throughput and sensitivity to detect ultra-small critical defects. The program specifically targets revolutionary solutions based on massively parallel e-beam technologies, as opposed to incremental improvements to existing e-beam and optical inspection platforms. Wafer inspection is the primary target, but attention is also being paid to next generation mask inspection. During the first phase of the multi-year program multiple technologies were reviewed, a down-selection was made to the top candidates, and evaluations began on proof of concept systems. A champion technology has been selected and as of late 2014 the program has begun to move into the core technology maturation phase in order to enable eventual commercialization of an HVM system. Performance data from early proof of concept systems will be shown along with roadmaps to achieving HVM performance. SEMATECH's vision for moving from early-stage development to commercialization will be shown, including plans for development with industry leading technology providers.

LiNbO3: A photovoltaic substrate for massive parallel manipulation and patterning of nano-objects

International Nuclear Information System (INIS)

Carrascosa, M.; García-Cabañes, A.; Jubera, M.; Ramiro, J. B.; Agulló-López, F.

2015-01-01

The application of evanescent photovoltaic (PV) fields, generated by visible illumination of Fe:LiNbO 3 substrates, for parallel massive trapping and manipulation of micro- and nano-objects is critically reviewed. The technique has been often referred to as photovoltaic or photorefractive tweezers. The main advantage of the new method is that the involved electrophoretic and/or dielectrophoretic forces do not require any electrodes and large scale manipulation of nano-objects can be easily achieved using the patterning capabilities of light. The paper describes the experimental techniques for particle trapping and the main reported experimental results obtained with a variety of micro- and nano-particles (dielectric and conductive) and different illumination configurations (single beam, holographic geometry, and spatial light modulator projection). The report also pays attention to the physical basis of the method, namely, the coupling of the evanescent photorefractive fields to the dielectric response of the nano-particles. The role of a number of physical parameters such as the contrast and spatial periodicities of the illumination pattern or the particle deposition method is discussed. Moreover, the main properties of the obtained particle patterns in relation to potential applications are summarized, and first demonstrations reviewed. Finally, the PV method is discussed in comparison to other patterning strategies, such as those based on the pyroelectric response and the electric fields associated to domain poling of ferroelectric materials

Targeted capture massively parallel sequencing analysis of LCIS and invasive lobular cancer: Repertoire of somatic genetic alterations and clonal relationships.

Science.gov (United States)

Sakr, Rita A; Schizas, Michail; Carniello, Jose V Scarpa; Ng, Charlotte K Y; Piscuoglio, Salvatore; Giri, Dilip; Andrade, Victor P; De Brot, Marina; Lim, Raymond S; Towers, Russell; Weigelt, Britta; Reis-Filho, Jorge S; King, Tari A

2016-02-01

Lobular carcinoma in situ (LCIS) has been proposed as a non-obligate precursor of invasive lobular carcinoma (ILC). Here we sought to define the repertoire of somatic genetic alterations in pure LCIS and in synchronous LCIS and ILC using targeted massively parallel sequencing. DNA samples extracted from microdissected LCIS, ILC and matched normal breast tissue or peripheral blood from 30 patients were subjected to massively parallel sequencing targeting all exons of 273 genes, including the genes most frequently mutated in breast cancer and DNA repair-related genes. Single nucleotide variants and insertions and deletions were identified using state-of-the-art bioinformatics approaches. The constellation of somatic mutations found in LCIS (n = 34) and ILC (n = 21) were similar, with the most frequently mutated genes being CDH1 (56% and 66%, respectively), PIK3CA (41% and 52%, respectively) and CBFB (12% and 19%, respectively). Among 19 LCIS and ILC synchronous pairs, 14 (74%) had at least one identical mutation in common, including identical PIK3CA and CDH1 mutations. Paired analysis of independent foci of LCIS from 3 breasts revealed at least one common mutation in each of the 3 pairs (CDH1, PIK3CA, CBFB and PKHD1L1). LCIS and ILC have a similar repertoire of somatic mutations, with PIK3CA and CDH1 being the most frequently mutated genes. The presence of identical mutations between LCIS-LCIS and LCIS-ILC pairs demonstrates that LCIS is a clonal neoplastic lesion, and provides additional evidence that at least some LCIS are non-obligate precursors of ILC. Copyright © 2015 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Massively parallel unsupervised single-particle cryo-EM data clustering via statistical manifold learning.

Directory of Open Access Journals (Sweden)

Jiayi Wu

Full Text Available Structural heterogeneity in single-particle cryo-electron microscopy (cryo-EM data represents a major challenge for high-resolution structure determination. Unsupervised classification may serve as the first step in the assessment of structural heterogeneity. However, traditional algorithms for unsupervised classification, such as K-means clustering and maximum likelihood optimization, may classify images into wrong classes with decreasing signal-to-noise-ratio (SNR in the image data, yet demand increased computational costs. Overcoming these limitations requires further development of clustering algorithms for high-performance cryo-EM data processing. Here we introduce an unsupervised single-particle clustering algorithm derived from a statistical manifold learning framework called generative topographic mapping (GTM. We show that unsupervised GTM clustering improves classification accuracy by about 40% in the absence of input references for data with lower SNRs. Applications to several experimental datasets suggest that our algorithm can detect subtle structural differences among classes via a hierarchical clustering strategy. After code optimization over a high-performance computing (HPC environment, our software implementation was able to generate thousands of reference-free class averages within hours in a massively parallel fashion, which allows a significant improvement on ab initio 3D reconstruction and assists in the computational purification of homogeneous datasets for high-resolution visualization.

Massively parallel unsupervised single-particle cryo-EM data clustering via statistical manifold learning.

Science.gov (United States)

Wu, Jiayi; Ma, Yong-Bei; Congdon, Charles; Brett, Bevin; Chen, Shuobing; Xu, Yaofang; Ouyang, Qi; Mao, Youdong

2017-01-01

Structural heterogeneity in single-particle cryo-electron microscopy (cryo-EM) data represents a major challenge for high-resolution structure determination. Unsupervised classification may serve as the first step in the assessment of structural heterogeneity. However, traditional algorithms for unsupervised classification, such as K-means clustering and maximum likelihood optimization, may classify images into wrong classes with decreasing signal-to-noise-ratio (SNR) in the image data, yet demand increased computational costs. Overcoming these limitations requires further development of clustering algorithms for high-performance cryo-EM data processing. Here we introduce an unsupervised single-particle clustering algorithm derived from a statistical manifold learning framework called generative topographic mapping (GTM). We show that unsupervised GTM clustering improves classification accuracy by about 40% in the absence of input references for data with lower SNRs. Applications to several experimental datasets suggest that our algorithm can detect subtle structural differences among classes via a hierarchical clustering strategy. After code optimization over a high-performance computing (HPC) environment, our software implementation was able to generate thousands of reference-free class averages within hours in a massively parallel fashion, which allows a significant improvement on ab initio 3D reconstruction and assists in the computational purification of homogeneous datasets for high-resolution visualization.

Research in Parallel Algorithms and Software for Computational Aerosciences

Science.gov (United States)

Domel, Neal D.

1996-01-01

Phase 1 is complete for the development of a computational fluid dynamics CFD) parallel code with automatic grid generation and adaptation for the Euler analysis of flow over complex geometries. SPLITFLOW, an unstructured Cartesian grid code developed at Lockheed Martin Tactical Aircraft Systems, has been modified for a distributed memory/massively parallel computing environment. The parallel code is operational on an SGI network, Cray J90 and C90 vector machines, SGI Power Challenge, and Cray T3D and IBM SP2 massively parallel machines. Parallel Virtual Machine (PVM) is the message passing protocol for portability to various architectures. A domain decomposition technique was developed which enforces dynamic load balancing to improve solution speed and memory requirements. A host/node algorithm distributes the tasks. The solver parallelizes very well, and scales with the number of processors. Partially parallelized and non-parallelized tasks consume most of the wall clock time in a very fine grain environment. Timing comparisons on a Cray C90 demonstrate that Parallel SPLITFLOW runs 2.4 times faster on 8 processors than its non-parallel counterpart autotasked over 8 processors.

Accurate CpG and non-CpG cytosine methylation analysis by high-throughput locus-specific pyrosequencing in plants.

Science.gov (United States)

How-Kit, Alexandre; Daunay, Antoine; Mazaleyrat, Nicolas; Busato, Florence; Daviaud, Christian; Teyssier, Emeline; Deleuze, Jean-François; Gallusci, Philippe; Tost, Jörg

2015-07-01

Pyrosequencing permits accurate quantification of DNA methylation of specific regions where the proportions of the C/T polymorphism induced by sodium bisulfite treatment of DNA reflects the DNA methylation level. The commercially available high-throughput locus-specific pyrosequencing instruments allow for the simultaneous analysis of 96 samples, but restrict the DNA methylation analysis to CpG dinucleotide sites, which can be limiting in many biological systems. In contrast to mammals where DNA methylation occurs nearly exclusively on CpG dinucleotides, plants genomes harbor DNA methylation also in other sequence contexts including CHG and CHH motives, which cannot be evaluated by these pyrosequencing instruments due to software limitations. Here, we present a complete pipeline for accurate CpG and non-CpG cytosine methylation analysis at single base-resolution using high-throughput locus-specific pyrosequencing. The devised approach includes the design and validation of PCR amplification on bisulfite-treated DNA and pyrosequencing assays as well as the quantification of the methylation level at every cytosine from the raw peak intensities of the Pyrograms by two newly developed Visual Basic Applications. Our method presents accurate and reproducible results as exemplified by the cytosine methylation analysis of the promoter regions of two Tomato genes (NOR and CNR) encoding transcription regulators of fruit ripening during different stages of fruit development. Our results confirmed a significant and temporally coordinated loss of DNA methylation on specific cytosines during the early stages of fruit development in both promoters as previously shown by WGBS. The manuscript describes thus the first high-throughput locus-specific DNA methylation analysis in plants using pyrosequencing.

Ultrascalable petaflop parallel supercomputer

Science.gov (United States)

Blumrich, Matthias A [Ridgefield, CT; Chen, Dong [Croton On Hudson, NY; Chiu, George [Cross River, NY; Cipolla, Thomas M [Katonah, NY; Coteus, Paul W [Yorktown Heights, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Hall, Shawn [Pleasantville, NY; Haring, Rudolf A [Cortlandt Manor, NY; Heidelberger, Philip [Cortlandt Manor, NY; Kopcsay, Gerard V [Yorktown Heights, NY; Ohmacht, Martin [Yorktown Heights, NY; Salapura, Valentina [Chappaqua, NY; Sugavanam, Krishnan [Mahopac, NY; Takken, Todd [Brewster, NY

2010-07-20

A massively parallel supercomputer of petaOPS-scale includes node architectures based upon System-On-a-Chip technology, where each processing node comprises a single Application Specific Integrated Circuit (ASIC) having up to four processing elements. The ASIC nodes are interconnected by multiple independent networks that optimally maximize the throughput of packet communications between nodes with minimal latency. The multiple networks may include three high-speed networks for parallel algorithm message passing including a Torus, collective network, and a Global Asynchronous network that provides global barrier and notification functions. These multiple independent networks may be collaboratively or independently utilized according to the needs or phases of an algorithm for optimizing algorithm processing performance. The use of a DMA engine is provided to facilitate message passing among the nodes without the expenditure of processing resources at the node.

Massive parallelization of a 3D finite difference electromagnetic forward solution using domain decomposition methods on multiple CUDA enabled GPUs

Science.gov (United States)

Schultz, A.

2010-12-01

3D forward solvers lie at the core of inverse formulations used to image the variation of electrical conductivity within the Earth's interior. This property is associated with variations in temperature, composition, phase, presence of volatiles, and in specific settings, the presence of groundwater, geothermal resources, oil/gas or minerals. The high cost of 3D solutions has been a stumbling block to wider adoption of 3D methods. Parallel algorithms for modeling frequency domain 3D EM problems have not achieved wide scale adoption, with emphasis on fairly coarse grained parallelism using MPI and similar approaches. The communications bandwidth as well as the latency required to send and receive network communication packets is a limiting factor in implementing fine grained parallel strategies, inhibiting wide adoption of these algorithms. Leading Graphics Processor Unit (GPU) companies now produce GPUs with hundreds of GPU processor cores per die. The footprint, in silicon, of the GPU's restricted instruction set is much smaller than the general purpose instruction set required of a CPU. Consequently, the density of processor cores on a GPU can be much greater than on a CPU. GPUs also have local memory, registers and high speed communication with host CPUs, usually through PCIe type interconnects. The extremely low cost and high computational power of GPUs provides the EM geophysics community with an opportunity to achieve fine grained (i.e. massive) parallelization of codes on low cost hardware. The current generation of GPUs (e.g. NVidia Fermi) provides 3 billion transistors per chip die, with nearly 500 processor cores and up to 6 GB of fast (DDR5) GPU memory. This latest generation of GPU supports fast hardware double precision (64 bit) floating point operations of the type required for frequency domain EM forward solutions. Each Fermi GPU board can sustain nearly 1 TFLOP in double precision, and multiple boards can be installed in the host computer system. We

A task parallel implementation of fast multipole methods

KAUST Repository

Taura, Kenjiro

2012-11-01

This paper describes a task parallel implementation of ExaFMM, an open source implementation of fast multipole methods (FMM), using a lightweight task parallel library MassiveThreads. Although there have been many attempts on parallelizing FMM, experiences have almost exclusively been limited to formulation based on flat homogeneous parallel loops. FMM in fact contains operations that cannot be readily expressed in such conventional but restrictive models. We show that task parallelism, or parallel recursions in particular, allows us to parallelize all operations of FMM naturally and scalably. Moreover it allows us to parallelize a \\'\\'mutual interaction\\'\\' for force/potential evaluation, which is roughly twice as efficient as a more conventional, unidirectional force/potential evaluation. The net result is an open source FMM that is clearly among the fastest single node implementations, including those on GPUs; with a million particles on a 32 cores Sandy Bridge 2.20GHz node, it completes a single time step including tree construction and force/potential evaluation in 65 milliseconds. The study clearly showcases both programmability and performance benefits of flexible parallel constructs over more monolithic parallel loops. © 2012 IEEE.

Pyrosequencing analysis of the gyrB gene to differentiate bacteria responsible for diarrheal diseases.

Science.gov (United States)

Hou, X-L; Cao, Q-Y; Jia, H-Y; Chen, Z

2008-07-01

Pathogens causing acute diarrhea include a large variety of species from Enterobacteriaceae and Vibrionaceae. A method based on pyrosequencing was used here to differentiate bacteria commonly associated with diarrhea in China; the method is targeted to a partial amplicon of the gyrB gene, which encodes the B subunit of DNA gyrase. Twenty-eight specific polymorphic positions were identified from sequence alignment of a large sequence dataset and targeted using 17 sequencing primers. Of 95 isolates tested, belonging to 13 species within 7 genera, most could be identified to the species level; O157 type could be differentiated from other E. coli types; Salmonella enterica subsp. enterica could be identified at the serotype level; the genus Shigella, except for S. boydii and S. dysenteriae, could also be identified. All these isolates were also subjected to conventional sequencing of a relatively long ( approximately1.2 kb) region of gyrB DNA; these results confirmed those with pyrosequencing. Twenty-two fecal samples were surveyed, the results of which were concordant with culture-based bacterial identification, and the pathogen detection limit with simulated stool specimens was 10(4) CFU/ml. DNA from different pathogens was also mixed to simulate a case of multibacterial infection, and the generated signals correlated well with the mix ratio. In summary, the gyrB-based pyrosequencing approach proved to have significant reliability and discriminatory power for enteropathogenic bacterial identification and provided a fast and effective method for clinical diagnosis.

Magnetohydrodynamics: Parallel computation of the dynamics of thermonuclear and astrophysical plasmas. 1. Annual report of massively parallel computing pilot project 93MPR05

International Nuclear Information System (INIS)

1994-08-01

This is the first annual report of the MPP pilot project 93MPR05. In this pilot project four research groups with different, complementary backgrounds collaborate with the aim to develop new algorithms and codes to simulate the magnetohydrodynamics of thermonuclear and astrophysical plasmas on massively parallel machines. The expected speed-up is required to simulate the dynamics of the hot plasmas of interest which are characterized by very large magnetic Reynolds numbers and, hence, require high spatial and temporal resolutions (for details see section 1). The four research groups that collaborated to produce the results reported here are: The MHD group of Prof. Dr. J.P. Goedbloed at the FOM-Institute for Plasma Physics 'Rijnhuizen' in Nieuwegein, the group of Prof. Dr. H. van der Vorst at the Mathematics Institute of Utrecht University, the group of Prof. Dr. A.G. Hearn at the Astronomical Institute of Utrecht University, and the group of Dr. Ir. H.J.J. te Riele at the CWI in Amsterdam. The full project team met frequently during this first project year to discuss progress reports, current problems, etc. (see section 2). The main results of the first project year are: - Proof of the scalability of typical linear and nonlinear MHD codes - development and testing of a parallel version of the Arnoldi algorithm - development and testing of alternative methods for solving large non-Hermitian eigenvalue problems - porting of the 3D nonlinear semi-implicit time evolution code HERA to an MPP system. The steps that were scheduled to reach these intended results are given in section 3. (orig./WL)

Magnetohydrodynamics: Parallel computation of the dynamics of thermonuclear and astrophysical plasmas. 1. Annual report of massively parallel computing pilot project 93MPR05

Energy Technology Data Exchange (ETDEWEB)

NONE

1994-08-01

This is the first annual report of the MPP pilot project 93MPR05. In this pilot project four research groups with different, complementary backgrounds collaborate with the aim to develop new algorithms and codes to simulate the magnetohydrodynamics of thermonuclear and astrophysical plasmas on massively parallel machines. The expected speed-up is required to simulate the dynamics of the hot plasmas of interest which are characterized by very large magnetic Reynolds numbers and, hence, require high spatial and temporal resolutions (for details see section 1). The four research groups that collaborated to produce the results reported here are: The MHD group of Prof. Dr. J.P. Goedbloed at the FOM-Institute for Plasma Physics `Rijnhuizen` in Nieuwegein, the group of Prof. Dr. H. van der Vorst at the Mathematics Institute of Utrecht University, the group of Prof. Dr. A.G. Hearn at the Astronomical Institute of Utrecht University, and the group of Dr. Ir. H.J.J. te Riele at the CWI in Amsterdam. The full project team met frequently during this first project year to discuss progress reports, current problems, etc. (see section 2). The main results of the first project year are: - Proof of the scalability of typical linear and nonlinear MHD codes - development and testing of a parallel version of the Arnoldi algorithm - development and testing of alternative methods for solving large non-Hermitian eigenvalue problems - porting of the 3D nonlinear semi-implicit time evolution code HERA to an MPP system. The steps that were scheduled to reach these intended results are given in section 3. (orig./WL).

Rapid detection and identification of Bacillus anthracis in food using pyrosequencing technology.

Science.gov (United States)

Amoako, Kingsley K; Janzen, Timothy W; Shields, Michael J; Hahn, Kristen R; Thomas, Matthew C; Goji, Noriko

2013-08-01

The development of advanced methodologies for the detection of Bacillus anthracis has been evolving rapidly since the release of the anthrax spores in the mail in 2001. Recent advances in detection and identification techniques could prove to be an essential component in the defense against biological attacks. Sequence based such as pyrosequencing, which has the capability to determine short DNA stretches in real-time using biotinylated PCR amplicons, has potential biodefense applications. Using markers from the virulence plasmids (pXO1 and pXO2) and chromosomal regions, we have demonstrated the power of this technology in the rapid, specific and sensitive detection of B. anthracis spores in food matrices including milk, juice, bottled water, and processed meat. The combined use of immunomagnetic separation and pyrosequencing showed positive detection when liquid foods (bottled water, milk, juice), and processed meat were experimentally inoculated with 6CFU/mL and 6CFU/g, respectively, without an enrichment step. Pyrosequencing is completed in about 60min (following PCR amplification) and yields accurate and reliable results with an added layer of confidence. The entire assay (from sample preparation to sequencing information) can be completed in about 7.5h. A typical run on food samples yielded 67-80bp reads with 94-100% identity to the expected sequence. This sequence based approach is a novel application for the detection of anthrax spores in food with potential application in foodborne bioterrorism response and biodefense involving the use of anthrax spores. Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.

Enabling inspection solutions for future mask technologies through the development of massively parallel E-Beam inspection

Science.gov (United States)

Malloy, Matt; Thiel, Brad; Bunday, Benjamin D.; Wurm, Stefan; Jindal, Vibhu; Mukhtar, Maseeh; Quoi, Kathy; Kemen, Thomas; Zeidler, Dirk; Eberle, Anna Lena; Garbowski, Tomasz; Dellemann, Gregor; Peters, Jan Hendrik

2015-09-01

The new device architectures and materials being introduced for sub-10nm manufacturing, combined with the complexity of multiple patterning and the need for improved hotspot detection strategies, have pushed current wafer inspection technologies to their limits. In parallel, gaps in mask inspection capability are growing as new generations of mask technologies are developed to support these sub-10nm wafer manufacturing requirements. In particular, the challenges associated with nanoimprint and extreme ultraviolet (EUV) mask inspection require new strategies that enable fast inspection at high sensitivity. The tradeoffs between sensitivity and throughput for optical and e-beam inspection are well understood. Optical inspection offers the highest throughput and is the current workhorse of the industry for both wafer and mask inspection. E-beam inspection offers the highest sensitivity but has historically lacked the throughput required for widespread adoption in the manufacturing environment. It is unlikely that continued incremental improvements to either technology will meet tomorrow's requirements, and therefore a new inspection technology approach is required; one that combines the high-throughput performance of optical with the high-sensitivity capabilities of e-beam inspection. To support the industry in meeting these challenges SUNY Poly SEMATECH has evaluated disruptive technologies that can meet the requirements for high volume manufacturing (HVM), for both the wafer fab [1] and the mask shop. Highspeed massively parallel e-beam defect inspection has been identified as the leading candidate for addressing the key gaps limiting today's patterned defect inspection techniques. As of late 2014 SUNY Poly SEMATECH completed a review, system analysis, and proof of concept evaluation of multiple e-beam technologies for defect inspection. A champion approach has been identified based on a multibeam technology from Carl Zeiss. This paper includes a discussion on the

Massively parallel algorithms for trace-driven cache simulations

Science.gov (United States)

Nicol, David M.; Greenberg, Albert G.; Lubachevsky, Boris D.

1991-01-01

Trace driven cache simulation is central to computer design. A trace is a very long sequence of reference lines from main memory. At the t(exp th) instant, reference x sub t is hashed into a set of cache locations, the contents of which are then compared with x sub t. If at the t sup th instant x sub t is not present in the cache, then it is said to be a miss, and is loaded into the cache set, possibly forcing the replacement of some other memory line, and making x sub t present for the (t+1) sup st instant. The problem of parallel simulation of a subtrace of N references directed to a C line cache set is considered, with the aim of determining which references are misses and related statistics. A simulation method is presented for the Least Recently Used (LRU) policy, which regradless of the set size C runs in time O(log N) using N processors on the exclusive read, exclusive write (EREW) parallel model. A simpler LRU simulation algorithm is given that runs in O(C log N) time using N/log N processors. Timings are presented of the second algorithm's implementation on the MasPar MP-1, a machine with 16384 processors. A broad class of reference based line replacement policies are considered, which includes LRU as well as the Least Frequently Used and Random replacement policies. A simulation method is presented for any such policy that on any trace of length N directed to a C line set runs in the O(C log N) time with high probability using N processors on the EREW model. The algorithms are simple, have very little space overhead, and are well suited for SIMD implementation.

Optimisation of a parallel ocean general circulation model

OpenAIRE

M. I. Beare; D. P. Stevens

1997-01-01

International audience; This paper presents the development of a general-purpose parallel ocean circulation model, for use on a wide range of computer platforms, from traditional scalar machines to workstation clusters and massively parallel processors. Parallelism is provided, as a modular option, via high-level message-passing routines, thus hiding the technical intricacies from the user. An initial implementation highlights that the parallel efficiency of the model is adversely affected by...

Parallel implementation of the PHOENIX generalized stellar atmosphere program. II. Wavelength parallelization

International Nuclear Information System (INIS)

Baron, E.; Hauschildt, Peter H.

1998-01-01

We describe an important addition to the parallel implementation of our generalized nonlocal thermodynamic equilibrium (NLTE) stellar atmosphere and radiative transfer computer program PHOENIX. In a previous paper in this series we described data and task parallel algorithms we have developed for radiative transfer, spectral line opacity, and NLTE opacity and rate calculations. These algorithms divided the work spatially or by spectral lines, that is, distributing the radial zones, individual spectral lines, or characteristic rays among different processors and employ, in addition, task parallelism for logically independent functions (such as atomic and molecular line opacities). For finite, monotonic velocity fields, the radiative transfer equation is an initial value problem in wavelength, and hence each wavelength point depends upon the previous one. However, for sophisticated NLTE models of both static and moving atmospheres needed to accurately describe, e.g., novae and supernovae, the number of wavelength points is very large (200,000 - 300,000) and hence parallelization over wavelength can lead both to considerable speedup in calculation time and the ability to make use of the aggregate memory available on massively parallel supercomputers. Here, we describe an implementation of a pipelined design for the wavelength parallelization of PHOENIX, where the necessary data from the processor working on a previous wavelength point is sent to the processor working on the succeeding wavelength point as soon as it is known. Our implementation uses a MIMD design based on a relatively small number of standard message passing interface (MPI) library calls and is fully portable between serial and parallel computers. copyright 1998 The American Astronomical Society

Efficient numerical methods for fluid- and electrodynamics on massively parallel systems

Energy Technology Data Exchange (ETDEWEB)

Zudrop, Jens

2016-07-01

In the last decade, computer technology has evolved rapidly. Modern high performance computing systems offer a tremendous amount of computing power in the range of a few peta floating point operations per second. In contrast, numerical software development is much slower and most existing simulation codes cannot exploit the full computing power of these systems. Partially, this is due to the numerical methods themselves and partially it is related to bottlenecks within the parallelization concept and its data structures. The goal of the thesis is the development of numerical algorithms and corresponding data structures to remedy both kinds of parallelization bottlenecks. The approach is based on a co-design of the numerical schemes (including numerical analysis) and their realizations in algorithms and software. Various kinds of applications, from multicomponent flows (Lattice Boltzmann Method) to electrodynamics (Discontinuous Galerkin Method) to embedded geometries (Octree), are considered and efficiency of the developed approaches is demonstrated for large scale simulations.

Implementation of an Agent-Based Parallel Tissue Modelling Framework for the Intel MIC Architecture

Directory of Open Access Journals (Sweden)

Maciej Cytowski

2017-01-01

Full Text Available Timothy is a novel large scale modelling framework that allows simulating of biological processes involving different cellular colonies growing and interacting with variable environment. Timothy was designed for execution on massively parallel High Performance Computing (HPC systems. The high parallel scalability of the implementation allows for simulations of up to 109 individual cells (i.e., simulations at tissue spatial scales of up to 1 cm3 in size. With the recent advancements of the Timothy model, it has become critical to ensure appropriate performance level on emerging HPC architectures. For instance, the introduction of blood vessels supplying nutrients to the tissue is a very important step towards realistic simulations of complex biological processes, but it greatly increased the computational complexity of the model. In this paper, we describe the process of modernization of the application in order to achieve high computational performance on HPC hybrid systems based on modern Intel® MIC architecture. Experimental results on the Intel Xeon Phi™ coprocessor x100 and the Intel Xeon Phi processor x200 are presented.

Towards anatomic scale agent-based modeling with a massively parallel spatially explicit general-purpose model of enteric tissue (SEGMEnT_HPC).

Science.gov (United States)

Cockrell, Robert Chase; Christley, Scott; Chang, Eugene; An, Gary

2015-01-01

Perhaps the greatest challenge currently facing the biomedical research community is the ability to integrate highly detailed cellular and molecular mechanisms to represent clinical disease states as a pathway to engineer effective therapeutics. This is particularly evident in the representation of organ-level pathophysiology in terms of abnormal tissue structure, which, through histology, remains a mainstay in disease diagnosis and staging. As such, being able to generate anatomic scale simulations is a highly desirable goal. While computational limitations have previously constrained the size and scope of multi-scale computational models, advances in the capacity and availability of high-performance computing (HPC) resources have greatly expanded the ability of computational models of biological systems to achieve anatomic, clinically relevant scale. Diseases of the intestinal tract are exemplary examples of pathophysiological processes that manifest at multiple scales of spatial resolution, with structural abnormalities present at the microscopic, macroscopic and organ-levels. In this paper, we describe a novel, massively parallel computational model of the gut, the Spatially Explicitly General-purpose Model of Enteric Tissue_HPC (SEGMEnT_HPC), which extends an existing model of the gut epithelium, SEGMEnT, in order to create cell-for-cell anatomic scale simulations. We present an example implementation of SEGMEnT_HPC that simulates the pathogenesis of ileal pouchitis, and important clinical entity that affects patients following remedial surgery for ulcerative colitis.

Parallel computing of a climate model on the dawn 1000 by domain decomposition method

Science.gov (United States)

Bi, Xunqiang

1997-12-01

In this paper the parallel computing of a grid-point nine-level atmospheric general circulation model on the Dawn 1000 is introduced. The model was developed by the Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences (CAS). The Dawn 1000 is a MIMD massive parallel computer made by National Research Center for Intelligent Computer (NCIC), CAS. A two-dimensional domain decomposition method is adopted to perform the parallel computing. The potential ways to increase the speed-up ratio and exploit more resources of future massively parallel supercomputation are also discussed.

Parallelized Seeded Region Growing Using CUDA

Directory of Open Access Journals (Sweden)

Seongjin Park

2014-01-01

Full Text Available This paper presents a novel method for parallelizing the seeded region growing (SRG algorithm using Compute Unified Device Architecture (CUDA technology, with intention to overcome the theoretical weakness of SRG algorithm of its computation time being directly proportional to the size of a segmented region. The segmentation performance of the proposed CUDA-based SRG is compared with SRG implementations on single-core CPUs, quad-core CPUs, and shader language programming, using synthetic datasets and 20 body CT scans. Based on the experimental results, the CUDA-based SRG outperforms the other three implementations, advocating that it can substantially assist the segmentation during massive CT screening tests.

Hybrid massively parallel fast sweeping method for static Hamilton–Jacobi equations

Energy Technology Data Exchange (ETDEWEB)

Detrixhe, Miles, E-mail: mdetrixhe@engineering.ucsb.edu [Department of Mechanical Engineering (United States); University of California Santa Barbara, Santa Barbara, CA, 93106 (United States); Gibou, Frédéric, E-mail: fgibou@engineering.ucsb.edu [Department of Mechanical Engineering (United States); University of California Santa Barbara, Santa Barbara, CA, 93106 (United States); Department of Computer Science (United States); Department of Mathematics (United States)

2016-10-01

The fast sweeping method is a popular algorithm for solving a variety of static Hamilton–Jacobi equations. Fast sweeping algorithms for parallel computing have been developed, but are severely limited. In this work, we present a multilevel, hybrid parallel algorithm that combines the desirable traits of two distinct parallel methods. The fine and coarse grained components of the algorithm take advantage of heterogeneous computer architecture common in high performance computing facilities. We present the algorithm and demonstrate its effectiveness on a set of example problems including optimal control, dynamic games, and seismic wave propagation. We give results for convergence, parallel scaling, and show state-of-the-art speedup values for the fast sweeping method.

Hybrid massively parallel fast sweeping method for static Hamilton–Jacobi equations

International Nuclear Information System (INIS)

Detrixhe, Miles; Gibou, Frédéric

2016-01-01

The fast sweeping method is a popular algorithm for solving a variety of static Hamilton–Jacobi equations. Fast sweeping algorithms for parallel computing have been developed, but are severely limited. In this work, we present a multilevel, hybrid parallel algorithm that combines the desirable traits of two distinct parallel methods. The fine and coarse grained components of the algorithm take advantage of heterogeneous computer architecture common in high performance computing facilities. We present the algorithm and demonstrate its effectiveness on a set of example problems including optimal control, dynamic games, and seismic wave propagation. We give results for convergence, parallel scaling, and show state-of-the-art speedup values for the fast sweeping method.

Scalable parallel prefix solvers for discrete ordinates transport

International Nuclear Information System (INIS)

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

2009-01-01

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

ESPRIT-Forest: Parallel clustering of massive amplicon sequence data in subquadratic time.

Science.gov (United States)

Cai, Yunpeng; Zheng, Wei; Yao, Jin; Yang, Yujie; Mai, Volker; Mao, Qi; Sun, Yijun

2017-04-01

The rapid development of sequencing technology has led to an explosive accumulation of genomic sequence data. Clustering is often the first step to perform in sequence analysis, and hierarchical clustering is one of the most commonly used approaches for this purpose. However, it is currently computationally expensive to perform hierarchical clustering of extremely large sequence datasets due to its quadratic time and space complexities. In this paper we developed a new algorithm called ESPRIT-Forest for parallel hierarchical clustering of sequences. The algorithm achieves subquadratic time and space complexity and maintains a high clustering accuracy comparable to the standard method. The basic idea is to organize sequences into a pseudo-metric based partitioning tree for sub-linear time searching of nearest neighbors, and then use a new multiple-pair merging criterion to construct clusters in parallel using multiple threads. The new algorithm was tested on the human microbiome project (HMP) dataset, currently one of the largest published microbial 16S rRNA sequence dataset. Our experiment demonstrated that with the power of parallel computing it is now compu- tationally feasible to perform hierarchical clustering analysis of tens of millions of sequences. The software is available at http://www.acsu.buffalo.edu/∼yijunsun/lab/ESPRIT-Forest.html.

Mapping robust parallel multigrid algorithms to scalable memory architectures

Science.gov (United States)

Overman, Andrea; Vanrosendale, John

1993-01-01

The convergence rate of standard multigrid algorithms degenerates on problems with stretched grids or anisotropic operators. The usual cure for this is the use of line or plane relaxation. However, multigrid algorithms based on line and plane relaxation have limited and awkward parallelism and are quite difficult to map effectively to highly parallel architectures. Newer multigrid algorithms that overcome anisotropy through the use of multiple coarse grids rather than relaxation are better suited to massively parallel architectures because they require only simple point-relaxation smoothers. In this paper, we look at the parallel implementation of a V-cycle multiple semicoarsened grid (MSG) algorithm on distributed-memory architectures such as the Intel iPSC/860 and Paragon computers. The MSG algorithms provide two levels of parallelism: parallelism within the relaxation or interpolation on each grid and across the grids on each multigrid level. Both levels of parallelism must be exploited to map these algorithms effectively to parallel architectures. This paper describes a mapping of an MSG algorithm to distributed-memory architectures that demonstrates how both levels of parallelism can be exploited. The result is a robust and effective multigrid algorithm for distributed-memory machines.

Massively Parallel Polar Decomposition on Distributed-Memory Systems

KAUST Repository

Ltaief, Hatem

2018-01-01

We present a high-performance implementation of the Polar Decomposition (PD) on distributed-memory systems. Building upon on the QR-based Dynamically Weighted Halley (QDWH) algorithm, the key idea lies in finding the best rational approximation for the scalar sign function, which also corresponds to the polar factor for symmetric matrices, to further accelerate the QDWH convergence. Based on the Zolotarev rational functions—introduced by Zolotarev (ZOLO) in 1877— this new PD algorithm ZOLO-PD converges within two iterations even for ill-conditioned matrices, instead of the original six iterations needed for QDWH. ZOLO-PD uses the property of Zolotarev functions that optimality is maintained when two functions are composed in an appropriate manner. The resulting ZOLO-PD has a convergence rate up to seventeen, in contrast to the cubic convergence rate for QDWH. This comes at the price of higher arithmetic costs and memory footprint. These extra floating-point operations can, however, be processed in an embarrassingly parallel fashion. We demonstrate performance using up to 102, 400 cores on two supercomputers. We demonstrate that, in the presence of a large number of processing units, ZOLO-PD is able to outperform QDWH by up to 2.3X speedup, especially in situations where QDWH runs out of work, for instance, in the strong scaling mode of operation.

'Iconic' tracking algorithms for high energy physics using the TRAX-I massively parallel processor

International Nuclear Information System (INIS)

Vesztergombi, G.

1989-01-01

TRAX-I, a cost-effective parallel microcomputer, applying associative string processor (ASP) architecture with 16 K parallel processing elements, is being built by Aspex Microsystems Ltd. (UK). When applied to the tracking problem of very complex events with several hundred tracks, the large number of processors allows one to dedicate one or more processors to each wire (in MWPC), each pixel (in digitized images from streamer chambers or other visual detectors), or each pad (in TPC) to perform very efficient pattern recognition. Some linear tracking algorithms based on this ''ionic'' representation are presented. (orig.)

'Iconic' tracking algorithms for high energy physics using the TRAX-I massively parallel processor

International Nuclear Information System (INIS)

Vestergombi, G.

1989-11-01

TRAX-I, a cost-effective parallel microcomputer, applying Associative String Processor (ASP) architecture with 16 K parallel processing elements, is being built by Aspex Microsystems Ltd. (UK). When applied to the tracking problem of very complex events with several hundred tracks, the large number of processors allows one to dedicate one or more processors to each wire (in MWPC), each pixel (in digitized images from streamer chambers or other visual detectors), or each pad (in TPC) to perform very efficient pattern recognition. Some linear tracking algorithms based on this 'iconic' representation are presented. (orig.)

Optimizing a massive parallel sequencing workflow for quantitative miRNA expression analysis.

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Francesca Cordero

Full Text Available BACKGROUND: Massive Parallel Sequencing methods (MPS can extend and improve the knowledge obtained by conventional microarray technology, both for mRNAs and short non-coding RNAs, e.g. miRNAs. The processing methods used to extract and interpret the information are an important aspect of dealing with the vast amounts of data generated from short read sequencing. Although the number of computational tools for MPS data analysis is constantly growing, their strengths and weaknesses as part of a complex analytical pipe-line have not yet been well investigated. PRIMARY FINDINGS: A benchmark MPS miRNA dataset, resembling a situation in which miRNAs are spiked in biological replication experiments was assembled by merging a publicly available MPS spike-in miRNAs data set with MPS data derived from healthy donor peripheral blood mononuclear cells. Using this data set we observed that short reads counts estimation is strongly under estimated in case of duplicates miRNAs, if whole genome is used as reference. Furthermore, the sensitivity of miRNAs detection is strongly dependent by the primary tool used in the analysis. Within the six aligners tested, specifically devoted to miRNA detection, SHRiMP and MicroRazerS show the highest sensitivity. Differential expression estimation is quite efficient. Within the five tools investigated, two of them (DESseq, baySeq show a very good specificity and sensitivity in the detection of differential expression. CONCLUSIONS: The results provided by our analysis allow the definition of a clear and simple analytical optimized workflow for miRNAs digital quantitative analysis.

Optimizing a massive parallel sequencing workflow for quantitative miRNA expression analysis.

Science.gov (United States)

Cordero, Francesca; Beccuti, Marco; Arigoni, Maddalena; Donatelli, Susanna; Calogero, Raffaele A

2012-01-01

Massive Parallel Sequencing methods (MPS) can extend and improve the knowledge obtained by conventional microarray technology, both for mRNAs and short non-coding RNAs, e.g. miRNAs. The processing methods used to extract and interpret the information are an important aspect of dealing with the vast amounts of data generated from short read sequencing. Although the number of computational tools for MPS data analysis is constantly growing, their strengths and weaknesses as part of a complex analytical pipe-line have not yet been well investigated. A benchmark MPS miRNA dataset, resembling a situation in which miRNAs are spiked in biological replication experiments was assembled by merging a publicly available MPS spike-in miRNAs data set with MPS data derived from healthy donor peripheral blood mononuclear cells. Using this data set we observed that short reads counts estimation is strongly under estimated in case of duplicates miRNAs, if whole genome is used as reference. Furthermore, the sensitivity of miRNAs detection is strongly dependent by the primary tool used in the analysis. Within the six aligners tested, specifically devoted to miRNA detection, SHRiMP and MicroRazerS show the highest sensitivity. Differential expression estimation is quite efficient. Within the five tools investigated, two of them (DESseq, baySeq) show a very good specificity and sensitivity in the detection of differential expression. The results provided by our analysis allow the definition of a clear and simple analytical optimized workflow for miRNAs digital quantitative analysis.

Parallel thermal radiation transport in two dimensions

International Nuclear Information System (INIS)

Smedley-Stevenson, R.P.; Ball, S.R.

2003-01-01

This paper describes the distributed memory parallel implementation of a deterministic thermal radiation transport algorithm in a 2-dimensional ALE hydrodynamics code. The parallel algorithm consists of a variety of components which are combined in order to produce a state of the art computational capability, capable of solving large thermal radiation transport problems using Blue-Oak, the 3 Tera-Flop MPP (massive parallel processors) computing facility at AWE (United Kingdom). Particular aspects of the parallel algorithm are described together with examples of the performance on some challenging applications. (author)

Parallel thermal radiation transport in two dimensions

Energy Technology Data Exchange (ETDEWEB)

Smedley-Stevenson, R.P.; Ball, S.R. [AWE Aldermaston (United Kingdom)

2003-07-01

This paper describes the distributed memory parallel implementation of a deterministic thermal radiation transport algorithm in a 2-dimensional ALE hydrodynamics code. The parallel algorithm consists of a variety of components which are combined in order to produce a state of the art computational capability, capable of solving large thermal radiation transport problems using Blue-Oak, the 3 Tera-Flop MPP (massive parallel processors) computing facility at AWE (United Kingdom). Particular aspects of the parallel algorithm are described together with examples of the performance on some challenging applications. (author)

Dissecting Cell-Type Composition and Activity-Dependent Transcriptional State in Mammalian Brains by Massively Parallel Single-Nucleus RNA-Seq.

Science.gov (United States)

Hu, Peng; Fabyanic, Emily; Kwon, Deborah Y; Tang, Sheng; Zhou, Zhaolan; Wu, Hao

2017-12-07

Massively parallel single-cell RNA sequencing can precisely resolve cellular diversity in a high-throughput manner at low cost, but unbiased isolation of intact single cells from complex tissues such as adult mammalian brains is challenging. Here, we integrate sucrose-gradient-assisted purification of nuclei with droplet microfluidics to develop a highly scalable single-nucleus RNA-seq approach (sNucDrop-seq), which is free of enzymatic dissociation and nucleus sorting. By profiling ∼18,000 nuclei isolated from cortical tissues of adult mice, we demonstrate that sNucDrop-seq not only accurately reveals neuronal and non-neuronal subtype composition with high sensitivity but also enables in-depth analysis of transient transcriptional states driven by neuronal activity, at single-cell resolution, in vivo. Copyright © 2017 Elsevier Inc. All rights reserved.

Endpoint-based parallel data processing in a parallel active messaging interface of a parallel computer

Science.gov (United States)

Archer, Charles J.; Blocksome, Michael A.; Ratterman, Joseph D.; Smith, Brian E.

2014-08-12

Endpoint-based parallel data processing in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI composed of data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes coupled for data communications through the PAMI, including establishing a data communications geometry, the geometry specifying, for tasks representing processes of execution of the parallel application, a set of endpoints that are used in collective operations of the PAMI including a plurality of endpoints for one of the tasks; receiving in endpoints of the geometry an instruction for a collective operation; and executing the instruction for a collective operation through the endpoints in dependence upon the geometry, including dividing data communications operations among the plurality of endpoints for one of the tasks.

Pyrosequencing for Rapid Detection of Mycobacterium tuberculosis Resistance to Rifampin, Isoniazid, and Fluoroquinolones ▿

Science.gov (United States)

Bravo, Lulette Tricia C.; Tuohy, Marion J.; Ang, Concepcion; Destura, Raul V.; Mendoza, Myrna; Procop, Gary W.; Gordon, Steven M.; Hall, Geraldine S.; Shrestha, Nabin K.

2009-01-01

After isoniazid and rifampin (rifampicin), the next pivotal drug class in Mycobacterium tuberculosis treatment is the fluoroquinolone class. Mutations in resistance-determining regions (RDR) of the rpoB, katG, and gyrA genes occur with frequencies of 97%, 50%, and 85% among M. tuberculosis isolates resistant to rifampin, isoniazid, and fluoroquinolones, respectively. Sequences are highly conserved, and certain mutations correlate well with phenotypic resistance. We developed a pyrosequencing assay to determine M. tuberculosis genotypic resistance to rifampin, isoniazid, and fluoroquinolones. We characterized 102 M. tuberculosis clinical isolates from the Philippines for susceptibility to rifampin, isoniazid, and ofloxacin by using the conventional submerged-disk proportion method and validated our pyrosequencing assay using these isolates. DNA was extracted and amplified by using PCR primers directed toward the RDR of the rpoB, katG, and gyrA genes, and pyrosequencing was performed on the extracts. The M. tuberculosis H37Rv strain (ATCC 25618) was used as the reference strain. The sensitivities and specificities of pyrosequencing were 96.7% and 97.3%, 63.8% and 100%, and 70.0% and 100% for the detection of resistance to rifampin, isoniazid, and ofloxacin, respectively. Pyrosequencing is thus a rapid and accurate method for detecting M. tuberculosis resistance to these three drugs. PMID:19846642

Program Transformation to Identify List-Based Parallel Skeletons

Directory of Open Access Journals (Sweden)

Venkatesh Kannan

2016-07-01

Full Text Available Algorithmic skeletons are used as building-blocks to ease the task of parallel programming by abstracting the details of parallel implementation from the developer. Most existing libraries provide implementations of skeletons that are defined over flat data types such as lists or arrays. However, skeleton-based parallel programming is still very challenging as it requires intricate analysis of the underlying algorithm and often uses inefficient intermediate data structures. Further, the algorithmic structure of a given program may not match those of list-based skeletons. In this paper, we present a method to automatically transform any given program to one that is defined over a list and is more likely to contain instances of list-based skeletons. This facilitates the parallel execution of a transformed program using existing implementations of list-based parallel skeletons. Further, by using an existing transformation called distillation in conjunction with our method, we produce transformed programs that contain fewer inefficient intermediate data structures.

AdiosStMan: Parallelizing Casacore Table Data System using Adaptive IO System

Science.gov (United States)

Wang, R.; Harris, C.; Wicenec, A.

2016-07-01

In this paper, we investigate the Casacore Table Data System (CTDS) used in the casacore and CASA libraries, and methods to parallelize it. CTDS provides a storage manager plugin mechanism for third-party developers to design and implement their own CTDS storage managers. Having this in mind, we looked into various storage backend techniques that can possibly enable parallel I/O for CTDS by implementing new storage managers. After carrying on benchmarks showing the excellent parallel I/O throughput of the Adaptive IO System (ADIOS), we implemented an ADIOS based parallel CTDS storage manager. We then applied the CASA MSTransform frequency split task to verify the ADIOS Storage Manager. We also ran a series of performance tests to examine the I/O throughput in a massively parallel scenario.

Rapid strategy for screening by pyrosequencing of influenza virus reassortants--candidates for live attenuated vaccines.

Science.gov (United States)

Shcherbik, Svetlana V; Pearce, Nicholas C; Levine, Marnie L; Klimov, Alexander I; Villanueva, Julie M; Bousse, Tatiana L

2014-01-01

Live attenuated influenza vaccine viruses (LAIVs) can be generated by classical reassortment of gene segments between a cold adapted, temperature sensitive and attenuated Master Donor Virus (MDV) and a seasonal wild-type (wt) virus. The vaccine candidates contain hemagglutinin (HA) and neuraminidase (NA) genes derived from the circulating wt viruses and the remaining six genes derived from the MDV strains. Rapid, efficient selection of the viruses with 6∶2 genome compositions from the large number of genetically different viruses generated during reassortment is essential for the biannual production schedule of vaccine viruses. This manuscript describes a new approach for the genotypic analysis of LAIV reassortant virus clones based on pyrosequencing. LAIV candidate viruses were created by classical reassortment of seasonal influenza A (H3N2) (A/Victoria/361/2011, A/Ohio/02/2012, A/Texas/50/2012) or influenza A (H7N9) (A/Anhui/1/2013) wt viruses with the MDV A/Leningrad/134/17/57(H2N2). Using strain-specific pyrosequencing assays, mixed gene variations were detected in the allantoic progenies during the cloning procedure. The pyrosequencing analysis also allowed for estimation of the relative abundance of segment variants in mixed populations. This semi-quantitative approach was used for selecting specific clones for the subsequent cloning procedures. The present study demonstrates that pyrosequencing analysis is a useful technique for rapid and reliable genotyping of reassortants and intermediate clones during the preparation of LAIV candidates, and can expedite the selection of vaccine virus candidates.

Rapid strategy for screening by pyrosequencing of influenza virus reassortants--candidates for live attenuated vaccines.

Directory of Open Access Journals (Sweden)

Svetlana V Shcherbik

Full Text Available BACKGROUND: Live attenuated influenza vaccine viruses (LAIVs can be generated by classical reassortment of gene segments between a cold adapted, temperature sensitive and attenuated Master Donor Virus (MDV and a seasonal wild-type (wt virus. The vaccine candidates contain hemagglutinin (HA and neuraminidase (NA genes derived from the circulating wt viruses and the remaining six genes derived from the MDV strains. Rapid, efficient selection of the viruses with 6∶2 genome compositions from the large number of genetically different viruses generated during reassortment is essential for the biannual production schedule of vaccine viruses. METHODOLOGY/PRINCIPAL FINDINGS: This manuscript describes a new approach for the genotypic analysis of LAIV reassortant virus clones based on pyrosequencing. LAIV candidate viruses were created by classical reassortment of seasonal influenza A (H3N2 (A/Victoria/361/2011, A/Ohio/02/2012, A/Texas/50/2012 or influenza A (H7N9 (A/Anhui/1/2013 wt viruses with the MDV A/Leningrad/134/17/57(H2N2. Using strain-specific pyrosequencing assays, mixed gene variations were detected in the allantoic progenies during the cloning procedure. The pyrosequencing analysis also allowed for estimation of the relative abundance of segment variants in mixed populations. This semi-quantitative approach was used for selecting specific clones for the subsequent cloning procedures. CONCLUSIONS/SIGNIFICANCE: The present study demonstrates that pyrosequencing analysis is a useful technique for rapid and reliable genotyping of reassortants and intermediate clones during the preparation of LAIV candidates, and can expedite the selection of vaccine virus candidates.

Massively parallel computation of PARASOL code on the Origin 3800 system

International Nuclear Information System (INIS)

Hosokawa, Masanari; Takizuka, Tomonori

2001-10-01

The divertor particle simulation code named PARASOL simulates open-field plasmas between divertor walls self-consistently by using an electrostatic PIC method and a binary collision Monte Carlo model. The PARASOL parallelized with MPI-1.1 for scalar parallel computer worked on Intel Paragon XP/S system. A system SGI Origin 3800 was newly installed (May, 2001). The parallel programming was improved at this switchover. As a result of the high-performance new hardware and this improvement, the PARASOL is speeded up by about 60 times with the same number of processors. (author)

Bayer image parallel decoding based on GPU

Science.gov (United States)

Hu, Rihui; Xu, Zhiyong; Wei, Yuxing; Sun, Shaohua

2012-11-01

In the photoelectrical tracking system, Bayer image is decompressed in traditional method, which is CPU-based. However, it is too slow when the images become large, for example, 2K×2K×16bit. In order to accelerate the Bayer image decoding, this paper introduces a parallel speedup method for NVIDA's Graphics Processor Unit (GPU) which supports CUDA architecture. The decoding procedure can be divided into three parts: the first is serial part, the second is task-parallelism part, and the last is data-parallelism part including inverse quantization, inverse discrete wavelet transform (IDWT) as well as image post-processing part. For reducing the execution time, the task-parallelism part is optimized by OpenMP techniques. The data-parallelism part could advance its efficiency through executing on the GPU as CUDA parallel program. The optimization techniques include instruction optimization, shared memory access optimization, the access memory coalesced optimization and texture memory optimization. In particular, it can significantly speed up the IDWT by rewriting the 2D (Tow-dimensional) serial IDWT into 1D parallel IDWT. Through experimenting with 1K×1K×16bit Bayer image, data-parallelism part is 10 more times faster than CPU-based implementation. Finally, a CPU+GPU heterogeneous decompression system was designed. The experimental result shows that it could achieve 3 to 5 times speed increase compared to the CPU serial method.

Tracking fungal community responses to maize plants by DNA- and RNA-based pyrosequencing.

Directory of Open Access Journals (Sweden)

Eiko E Kuramae

Full Text Available We assessed soil fungal diversity and community structure at two sampling times (t1 = 47 days and t2 = 104 days of plant age in pots associated with four maize cultivars, including two genetically modified (GM cultivars by high-throughput pyrosequencing of the 18S rRNA gene using DNA and RNA templates. We detected no significant differences in soil fungal diversity and community structure associated with different plant cultivars. However, DNA-based analyses yielded lower fungal OTU richness as compared to RNA-based analyses. Clear differences in fungal community structure were also observed in relation to sampling time and the nucleic acid pool targeted (DNA versus RNA. The most abundant soil fungi, as recovered by DNA-based methods, did not necessary represent the most "active" fungi (as recovered via RNA. Interestingly, RNA-derived community compositions at t1 were highly similar to DNA-derived communities at t2, based on presence/absence measures of OTUs. We recovered large proportions of fungal sequences belonging to arbuscular mycorrhizal fungi and Basidiomycota, especially at the RNA level, suggesting that these important and potentially beneficial fungi are not affected by the plant cultivars nor by GM traits (Bt toxin production. Our results suggest that even though DNA- and RNA-derived soil fungal communities can be very different at a given time, RNA composition may have a predictive power of fungal community development through time.

Parallelization of quantum molecular dynamics simulation code

International Nuclear Information System (INIS)

Kato, Kaori; Kunugi, Tomoaki; Shibahara, Masahiko; Kotake, Susumu

1998-02-01

A quantum molecular dynamics simulation code has been developed for the analysis of the thermalization of photon energies in the molecule or materials in Kansai Research Establishment. The simulation code is parallelized for both Scalar massively parallel computer (Intel Paragon XP/S75) and Vector parallel computer (Fujitsu VPP300/12). Scalable speed-up has been obtained with a distribution to processor units by division of particle group in both parallel computers. As a result of distribution to processor units not only by particle group but also by the particles calculation that is constructed with fine calculations, highly parallelization performance is achieved in Intel Paragon XP/S75. (author)

Parallel Tensor Compression for Large-Scale Scientific Data.

Energy Technology Data Exchange (ETDEWEB)

Kolda, Tamara G. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Ballard, Grey [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Austin, Woody Nathan [Univ. of Texas, Austin, TX (United States)

2015-10-01

As parallel computing trends towards the exascale, scientific data produced by high-fidelity simulations are growing increasingly massive. For instance, a simulation on a three-dimensional spatial grid with 512 points per dimension that tracks 64 variables per grid point for 128 time steps yields 8 TB of data. By viewing the data as a dense five way tensor, we can compute a Tucker decomposition to find inherent low-dimensional multilinear structure, achieving compression ratios of up to 10000 on real-world data sets with negligible loss in accuracy. So that we can operate on such massive data, we present the first-ever distributed memory parallel implementation for the Tucker decomposition, whose key computations correspond to parallel linear algebra operations, albeit with nonstandard data layouts. Our approach specifies a data distribution for tensors that avoids any tensor data redistribution, either locally or in parallel. We provide accompanying analysis of the computation and communication costs of the algorithms. To demonstrate the compression and accuracy of the method, we apply our approach to real-world data sets from combustion science simulations. We also provide detailed performance results, including parallel performance in both weak and strong scaling experiments.

Massively parallel sequencing and targeted exomes in familial kidney disease can diagnose underlying genetic disorders.

Science.gov (United States)

Mallett, Andrew J; McCarthy, Hugh J; Ho, Gladys; Holman, Katherine; Farnsworth, Elizabeth; Patel, Chirag; Fletcher, Jeffery T; Mallawaarachchi, Amali; Quinlan, Catherine; Bennetts, Bruce; Alexander, Stephen I

2017-12-01

Inherited kidney disease encompasses a broad range of disorders, with both multiple genes contributing to specific phenotypes and single gene defects having multiple clinical presentations. Advances in sequencing capacity may allow a genetic diagnosis for familial renal disease, by testing the increasing number of known causative genes. However, there has been limited translation of research findings of causative genes into clinical settings. Here, we report the results of a national accredited diagnostic genetic service for familial renal disease. An expert multidisciplinary team developed a targeted exomic sequencing approach with ten curated multigene panels (207 genes) and variant assessment individualized to the patient's phenotype. A genetic diagnosis (pathogenic genetic variant[s]) was identified in 58 of 135 families referred in two years. The genetic diagnosis rate was similar between families with a pediatric versus adult proband (46% vs 40%), although significant differences were found in certain panels such as atypical hemolytic uremic syndrome (88% vs 17%). High diagnostic rates were found for Alport syndrome (22 of 27) and tubular disorders (8 of 10), whereas the monogenic diagnostic rate for congenital anomalies of the kidney and urinary tract was one of 13. Quality reporting was aided by a strong clinical renal and genetic multidisciplinary committee review. Importantly, for a diagnostic service, few variants of uncertain significance were found with this targeted, phenotype-based approach. Thus, use of targeted massively parallel sequencing approaches in inherited kidney disease has a significant capacity to diagnose the underlying genetic disorder across most renal phenotypes. Copyright © 2017 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.

A massively parallel sequencing approach uncovers ancient origins and high genetic variability of endangered Przewalski's horses.

Science.gov (United States)

Goto, Hiroki; Ryder, Oliver A; Fisher, Allison R; Schultz, Bryant; Kosakovsky Pond, Sergei L; Nekrutenko, Anton; Makova, Kateryna D

2011-01-01

The endangered Przewalski's horse is the closest relative of the domestic horse and is the only true wild horse species surviving today. The question of whether Przewalski's horse is the direct progenitor of domestic horse has been hotly debated. Studies of DNA diversity within Przewalski's horses have been sparse but are urgently needed to ensure their successful reintroduction to the wild. In an attempt to resolve the controversy surrounding the phylogenetic position and genetic diversity of Przewalski's horses, we used massively parallel sequencing technology to decipher the complete mitochondrial and partial nuclear genomes for all four surviving maternal lineages of Przewalski's horses. Unlike single-nucleotide polymorphism (SNP) typing usually affected by ascertainment bias, the present method is expected to be largely unbiased. Three mitochondrial haplotypes were discovered-two similar ones, haplotypes I/II, and one substantially divergent from the other two, haplotype III. Haplotypes I/II versus III did not cluster together on a phylogenetic tree, rejecting the monophyly of Przewalski's horse maternal lineages, and were estimated to split 0.117-0.186 Ma, significantly preceding horse domestication. In the phylogeny based on autosomal sequences, Przewalski's horses formed a monophyletic clade, separate from the Thoroughbred domestic horse lineage. Our results suggest that Przewalski's horses have ancient origins and are not the direct progenitors of domestic horses. The analysis of the vast amount of sequence data presented here suggests that Przewalski's and domestic horse lineages diverged at least 0.117 Ma but since then have retained ancestral genetic polymorphism and/or experienced gene flow.

Community analysis of chronic wound bacteria using 16S rRNA gene-based pyrosequencing: impact of diabetes and antibiotics on chronic wound microbiota.

Directory of Open Access Journals (Sweden)

Lance B Price

Full Text Available BACKGROUND: Bacterial colonization is hypothesized to play a pathogenic role in the non-healing state of chronic wounds. We characterized wound bacteria from a cohort of chronic wound patients using a 16S rRNA gene-based pyrosequencing approach and assessed the impact of diabetes and antibiotics on chronic wound microbiota. METHODOLOGY/PRINCIPAL FINDINGS: We prospectively enrolled 24 patients at a referral wound center in Baltimore, MD; sampled patients' wounds by curette; cultured samples under aerobic and anaerobic conditions; and pyrosequenced the 16S rRNA V3 hypervariable region. The 16S rRNA gene-based analyses revealed an average of 10 different bacterial families in wounds--approximately 4 times more than estimated by culture-based analyses. Fastidious anaerobic bacteria belonging to the Clostridiales family XI were among the most prevalent bacteria identified exclusively by 16S rRNA gene-based analyses. Community-scale analyses showed that wound microbiota from antibiotic treated patients were significantly different from untreated patients (p = 0.007 and were characterized by increased Pseudomonadaceae abundance. These analyses also revealed that antibiotic use was associated with decreased Streptococcaceae among diabetics and that Streptococcaceae was more abundant among diabetics as compared to non-diabetics. CONCLUSIONS/SIGNIFICANCE: The 16S rRNA gene-based analyses revealed complex bacterial communities including anaerobic bacteria that may play causative roles in the non-healing state of some chronic wounds. Our data suggest that antimicrobial therapy alters community structure--reducing some bacteria while selecting for others.

Design considerations for parallel graphics libraries

Science.gov (United States)

Crockett, Thomas W.

1994-01-01

Applications which run on parallel supercomputers are often characterized by massive datasets. Converting these vast collections of numbers to visual form has proven to be a powerful aid to comprehension. For a variety of reasons, it may be desirable to provide this visual feedback at runtime. One way to accomplish this is to exploit the available parallelism to perform graphics operations in place. In order to do this, we need appropriate parallel rendering algorithms and library interfaces. This paper provides a tutorial introduction to some of the issues which arise in designing parallel graphics libraries and their underlying rendering algorithms. The focus is on polygon rendering for distributed memory message-passing systems. We illustrate our discussion with examples from PGL, a parallel graphics library which has been developed on the Intel family of parallel systems.

DIMACS Workshop on Interconnection Networks and Mapping, and Scheduling Parallel Computations

CERN Document Server

Rosenberg, Arnold L; Sotteau, Dominique; NSF Science and Technology Center in Discrete Mathematics and Theoretical Computer Science; Interconnection networks and mapping and scheduling parallel computations

1995-01-01

The interconnection network is one of the most basic components of a massively parallel computer system. Such systems consist of hundreds or thousands of processors interconnected to work cooperatively on computations. One of the central problems in parallel computing is the task of mapping a collection of processes onto the processors and routing network of a parallel machine. Once this mapping is done, it is critical to schedule computations within and communication among processor from universities and laboratories, as well as practitioners involved in the design, implementation, and application of massively parallel systems. Focusing on interconnection networks of parallel architectures of today and of the near future , the book includes topics such as network topologies,network properties, message routing, network embeddings, network emulation, mappings, and efficient scheduling. inputs for a process are available where and when the process is scheduled to be computed. This book contains the refereed pro...

New adaptive differencing strategy in the PENTRAN 3-d parallel Sn code

International Nuclear Information System (INIS)

Sjoden, G.E.; Haghighat, A.

1996-01-01

It is known that three-dimensional (3-D) discrete ordinates (S n ) transport problems require an immense amount of storage and computational effort to solve. For this reason, parallel codes that offer a capability to completely decompose the angular, energy, and spatial domains among a distributed network of processors are required. One such code recently developed is PENTRAN, which iteratively solves 3-D multi-group, anisotropic S n problems on distributed-memory platforms, such as the IBM-SP2. Because large problems typically contain several different material zones with various properties, available differencing schemes should automatically adapt to the transport physics in each material zone. To minimize the memory and message-passing overhead required for massively parallel S n applications, available differencing schemes in an adaptive strategy should also offer reasonable accuracy and positivity, yet require only the zeroth spatial moment of the transport equation; differencing schemes based on higher spatial moments, in spite of their greater accuracy, require at least twice the amount of storage and communication cost for implementation in a massively parallel transport code. This paper discusses a new adaptive differencing strategy that uses increasingly accurate schemes with low parallel memory and communication overhead. This strategy, implemented in PENTRAN, includes a new scheme, exponential directional averaged (EDA) differencing

Parallel Implicit Algorithms for CFD

Science.gov (United States)

Keyes, David E.

1998-01-01

The main goal of this project was efficient distributed parallel and workstation cluster implementations of Newton-Krylov-Schwarz (NKS) solvers for implicit Computational Fluid Dynamics (CFD.) "Newton" refers to a quadratically convergent nonlinear iteration using gradient information based on the true residual, "Krylov" to an inner linear iteration that accesses the Jacobian matrix only through highly parallelizable sparse matrix-vector products, and "Schwarz" to a domain decomposition form of preconditioning the inner Krylov iterations with primarily neighbor-only exchange of data between the processors. Prior experience has established that Newton-Krylov methods are competitive solvers in the CFD context and that Krylov-Schwarz methods port well to distributed memory computers. The combination of the techniques into Newton-Krylov-Schwarz was implemented on 2D and 3D unstructured Euler codes on the parallel testbeds that used to be at LaRC and on several other parallel computers operated by other agencies or made available by the vendors. Early implementations were made directly in Massively Parallel Integration (MPI) with parallel solvers we adapted from legacy NASA codes and enhanced for full NKS functionality. Later implementations were made in the framework of the PETSC library from Argonne National Laboratory, which now includes pseudo-transient continuation Newton-Krylov-Schwarz solver capability (as a result of demands we made upon PETSC during our early porting experiences). A secondary project pursued with funding from this contract was parallel implicit solvers in acoustics, specifically in the Helmholtz formulation. A 2D acoustic inverse problem has been solved in parallel within the PETSC framework.

Lemon : An MPI parallel I/O library for data encapsulation using LIME

NARCIS (Netherlands)

Deuzeman, Albert; Reker, Siebren; Urbach, Carsten

We introduce Lemon, an MPI parallel I/O library that provides efficient parallel I/O of both binary and metadata on massively parallel architectures. Motivated by the demands of the lattice Quantum Chromodynamics community, the data is stored in the SciDAC Lattice QCD Interchange Message

Cellular automata a parallel model

CERN Document Server

Mazoyer, J

1999-01-01

Cellular automata can be viewed both as computational models and modelling systems of real processes. This volume emphasises the first aspect. In articles written by leading researchers, sophisticated massive parallel algorithms (firing squad, life, Fischer's primes recognition) are treated. Their computational power and the specific complexity classes they determine are surveyed, while some recent results in relation to chaos from a new dynamic systems point of view are also presented. Audience: This book will be of interest to specialists of theoretical computer science and the parallelism challenge.

Massively parallel sequencing and the emergence of forensic genomics: Defining the policy and legal issues for law enforcement.

Science.gov (United States)

Scudder, Nathan; McNevin, Dennis; Kelty, Sally F; Walsh, Simon J; Robertson, James

2018-03-01

Use of DNA in forensic science will be significantly influenced by new technology in coming years. Massively parallel sequencing and forensic genomics will hasten the broadening of forensic DNA analysis beyond short tandem repeats for identity towards a wider array of genetic markers, in applications as diverse as predictive phenotyping, ancestry assignment, and full mitochondrial genome analysis. With these new applications come a range of legal and policy implications, as forensic science touches on areas as diverse as 'big data', privacy and protected health information. Although these applications have the potential to make a more immediate and decisive forensic intelligence contribution to criminal investigations, they raise policy issues that will require detailed consideration if this potential is to be realised. The purpose of this paper is to identify the scope of the issues that will confront forensic and user communities. Copyright © 2017 The Chartered Society of Forensic Sciences. All rights reserved.

Parallel image encryption algorithm based on discretized chaotic map

International Nuclear Information System (INIS)

Zhou Qing; Wong Kwokwo; Liao Xiaofeng; Xiang Tao; Hu Yue

2008-01-01

Recently, a variety of chaos-based algorithms were proposed for image encryption. Nevertheless, none of them works efficiently in parallel computing environment. In this paper, we propose a framework for parallel image encryption. Based on this framework, a new algorithm is designed using the discretized Kolmogorov flow map. It fulfills all the requirements for a parallel image encryption algorithm. Moreover, it is secure and fast. These properties make it a good choice for image encryption on parallel computing platforms

Frame-Based and Subpicture-Based Parallelization Approaches of the HEVC Video Encoder

Directory of Open Access Journals (Sweden)

Héctor Migallón

2018-05-01

Full Text Available The most recent video coding standard, High Efficiency Video Coding (HEVC, is able to significantly improve the compression performance at the expense of a huge computational complexity increase with respect to its predecessor, H.264/AVC. Parallel versions of the HEVC encoder may help to reduce the overall encoding time in order to make it more suitable for practical applications. In this work, we study two parallelization strategies. One of them follows a coarse-grain approach, where parallelization is based on frames, and the other one follows a fine-grain approach, where parallelization is performed at subpicture level. Two different frame-based approaches have been developed. The first one only uses MPI and the second one is a hybrid MPI/OpenMP algorithm. An exhaustive experimental test was carried out to study the performance of both approaches in order to find out the best setup in terms of parallel efficiency and coding performance. Both frame-based and subpicture-based approaches are compared under the same hardware platform. Although subpicture-based schemes provide an excellent performance with high-resolution video sequences, scalability is limited by resolution, and the coding performance worsens by increasing the number of processes. Conversely, the proposed frame-based approaches provide the best results with respect to both parallel performance (increasing scalability and coding performance (not degrading the rate/distortion behavior.

Investigation of the koala (Phascolarctos cinereus) hindgut microbiome via 16S pyrosequencing.

Science.gov (United States)

Barker, Christopher J; Gillett, Amber; Polkinghorne, Adam; Timms, Peter

2013-12-27

As a dietary source, the foliage of Eucalyptus spp. is low in available protein and carbohydrate while containing polyphenolic compounds that interfere with enzymatic digestion. To overcome this, the koala (Phascolarctos cinereus) has evolved a range of anatomical and physiological adaptations to assist with digestion and absorption of nutrients from this food source. Microbial fermentation of partially digested eucalyptus leaves is thought to be critical in this process, however, little is known about the composition and diversity of microorganisms that are associated with digestive health in this native species. In this study, we performed 16S rRNA gene pyrosequencing of caecum, colon and faecal pellet samples from two wild, free ranging, Queensland koalas. Our results reveal a highly complex and diverse ecosystem with considerable intra-individual variation. Although samples were dominated by sequences from the Bacteroidetes and Firmicutes phyla there was considerable variation at the genus level. This study is the first non-culture based microbiota analysis, using 454-amplicon pyrosequencing, and provides preliminary data to expand our understanding of the koala hindgut. Copyright © 2013 Elsevier B.V. All rights reserved.

Use of massively parallel computing to improve modelling accuracy within the nuclear sector

Directory of Open Access Journals (Sweden)

L M Evans

2016-06-01

This work presents recent advancements in three techniques: Uncertainty quantification (UQ; Cellular automata finite element (CAFE; Image based finite element methods (IBFEM. Case studies are presented demonstrating their suitability for use in nuclear engineering made possible by advancements in parallel computing hardware that is projected to be available for industry within the next decade costing of the order of $100k.

A bumpy ride on the diagnostic bench of massive parallel sequencing, the case of the mitochondrial genome.

Directory of Open Access Journals (Sweden)

Kim Vancampenhout

Full Text Available The advent of massive parallel sequencing (MPS has revolutionized the field of human molecular genetics, including the diagnostic study of mitochondrial (mt DNA dysfunction. The analysis of the complete mitochondrial genome using MPS platforms is now common and will soon outrun conventional sequencing. However, the development of a robust and reliable protocol is rather challenging. A previous pilot study for the re-sequencing of human mtDNA revealed an uneven coverage, affecting predominantly part of the plus strand. In an attempt to address this problem, we undertook a comparative study of standard and modified protocols for the Ion Torrent PGM system. We could not improve strand representation by altering the recommended shearing methodology of the standard workflow or omitting the DNA polymerase amplification step from the library construction process. However, we were able to associate coverage bias of the plus strand with a specific sequence motif. Additionally, we compared coverage and variant calling across technologies. The same samples were also sequenced on a MiSeq device which showed that coverage and heteroplasmic variant calling were much improved.

A safe an easy method for building consensus HIV sequences from 454 massively parallel sequencing data.

Science.gov (United States)

Fernández-Caballero Rico, Jose Ángel; Chueca Porcuna, Natalia; Álvarez Estévez, Marta; Mosquera Gutiérrez, María Del Mar; Marcos Maeso, María Ángeles; García, Federico

2018-02-01

To show how to generate a consensus sequence from the information of massive parallel sequences data obtained from routine HIV anti-retroviral resistance studies, and that may be suitable for molecular epidemiology studies. Paired Sanger (Trugene-Siemens) and next-generation sequencing (NGS) (454 GSJunior-Roche) HIV RT and protease sequences from 62 patients were studied. NGS consensus sequences were generated using Mesquite, using 10%, 15%, and 20% thresholds. Molecular evolutionary genetics analysis (MEGA) was used for phylogenetic studies. At a 10% threshold, NGS-Sanger sequences from 17/62 patients were phylogenetically related, with a median bootstrap-value of 88% (IQR83.5-95.5). Association increased to 36/62 sequences, median bootstrap 94% (IQR85.5-98)], using a 15% threshold. Maximum association was at the 20% threshold, with 61/62 sequences associated, and a median bootstrap value of 99% (IQR98-100). A safe method is presented to generate consensus sequences from HIV-NGS data at 20% threshold, which will prove useful for molecular epidemiological studies. Copyright © 2016 Elsevier España, S.L.U. and Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica. All rights reserved.

New Parallel Algorithms for Landscape Evolution Model

Science.gov (United States)

Jin, Y.; Zhang, H.; Shi, Y.

2017-12-01

Most landscape evolution models (LEM) developed in the last two decades solve the diffusion equation to simulate the transportation of surface sediments. This numerical approach is difficult to parallelize due to the computation of drainage area for each node, which needs huge amount of communication if run in parallel. In order to overcome this difficulty, we developed two parallel algorithms for LEM with a stream net. One algorithm handles the partition of grid with traditional methods and applies an efficient global reduction algorithm to do the computation of drainage areas and transport rates for the stream net; the other algorithm is based on a new partition algorithm, which partitions the nodes in catchments between processes first, and then partitions the cells according to the partition of nodes. Both methods focus on decreasing communication between processes and take the advantage of massive computing techniques, and numerical experiments show that they are both adequate to handle large scale problems with millions of cells. We implemented the two algorithms in our program based on the widely used finite element library deal.II, so that it can be easily coupled with ASPECT.

Pyrosequencing-Based Assays for Rapid Detection of HER2 and HER3 Mutations in Clinical Samples Uncover an E332E Mutation Affecting HER3 in Retroperitoneal Leiomyosarcoma

Directory of Open Access Journals (Sweden)

Paula González-Alonso

2015-08-01

Full Text Available Mutations in Human Epidermal Growth Factor Receptors (HER are associated with poor prognosis of several types of solid tumors. Although HER-mutation detection methods are currently available, such as Next-Generation Sequencing (NGS, alternative pyrosequencing allow the rapid characterization of specific mutations. We developed specific PCR-based pyrosequencing assays for identification of most prevalent HER2 and HER3 mutations, including S310F/Y, R678Q, L755M/P/S/W, V777A/L/M, 774-776 insertion, and V842I mutations in HER2, as well as M91I, V104M/L, D297N/V/Y, and E332E/K mutations in HER3. We tested 85 Formalin Fixed and Paraffin Embbeded (FFPE samples and we detected three HER2-V842I mutations in colorectal carcinoma (CRC, ovarian carcinoma, and pancreatic carcinoma patients, respectively, and a HER2-L755M mutation in a CRC specimen. We also determined the presence of a HER3-E332K mutation in an urothelial carcinoma sample, and two HER3-D297Y mutations, in both gastric adenocarcinoma and CRC specimens. The D297Y mutation was previously detected in breast and gastric tumors, but not in CRC. Moreover, we found a not-previously-described HER3-E332E synonymous mutation in a retroperitoneal leiomyosarcoma patient. The pyrosequencing assays presented here allow the detection and characterization of specific HER2 and HER3 mutations. These pyrosequencing assays might be implemented in routine diagnosis for molecular characterization of HER2/HER3 receptors as an alternative to complex NGS approaches.

Massive parallel electromagnetic field simulation program JEMS-FDTD design and implementation on jasmin

International Nuclear Information System (INIS)

Li Hanyu; Zhou Haijing; Dong Zhiwei; Liao Cheng; Chang Lei; Cao Xiaolin; Xiao Li

2010-01-01

A large-scale parallel electromagnetic field simulation program JEMS-FDTD(J Electromagnetic Solver-Finite Difference Time Domain) is designed and implemented on JASMIN (J parallel Adaptive Structured Mesh applications INfrastructure). This program can simulate propagation, radiation, couple of electromagnetic field by solving Maxwell equations on structured mesh explicitly with FDTD method. JEMS-FDTD is able to simulate billion-mesh-scale problems on thousands of processors. In this article, the program is verified by simulating the radiation of an electric dipole. A beam waveguide is simulated to demonstrate the capability of large scale parallel computation. A parallel performance test indicates that a high parallel efficiency is obtained. (authors)

Reliability-Based Optimization of Series Systems of Parallel Systems

DEFF Research Database (Denmark)

Enevoldsen, I.; Sørensen, John Dalsgaard

1993-01-01

Reliability-based design of structural systems is considered. In particular, systems where the reliability model is a series system of parallel systems are treated. A sensitivity analysis for this class of problems is presented. Optimization problems with series systems of parallel systems...... optimization of series systems of parallel systems, but it is also efficient in reliability-based optimization of series systems in general....

Development of parallel Fokker-Planck code ALLAp

International Nuclear Information System (INIS)

Batishcheva, A.A.; Sigmar, D.J.; Koniges, A.E.

1996-01-01

We report on our ongoing development of the 3D Fokker-Planck code ALLA for a highly collisional scrape-off-layer (SOL) plasma. A SOL with strong gradients of density and temperature in the spatial dimension is modeled. Our method is based on a 3-D adaptive grid (in space, magnitude of the velocity, and cosine of the pitch angle) and a second order conservative scheme. Note that the grid size is typically 100 x 257 x 65 nodes. It was shown in our previous work that only these capabilities make it possible to benchmark a 3D code against a spatially-dependent self-similar solution of a kinetic equation with the Landau collision term. In the present work we show results of a more precise benchmarking against the exact solutions of the kinetic equation using a new parallel code ALLAp with an improved method of parallelization and a modified boundary condition at the plasma edge. We also report first results from the code parallelization using Message Passing Interface for a Massively Parallel CRI T3D platform. We evaluate the ALLAp code performance versus the number of T3D processors used and compare its efficiency against a Work/Data Sharing parallelization scheme and a workstation version

Opportunities and challenges for the integration of massively parallel genomic sequencing into clinical practice: lessons from the ClinSeq project.

Science.gov (United States)

Biesecker, Leslie G

2012-04-01

The debate surrounding the return of results from high-throughput genomic interrogation encompasses many important issues including ethics, law, economics, and social policy. As well, the debate is also informed by the molecular, genetic, and clinical foundations of the emerging field of clinical genomics, which is based on this new technology. This article outlines the main biomedical considerations of sequencing technologies and demonstrates some of the early clinical experiences with the technology to enable the debate to stay focused on real-world practicalities. These experiences are based on early data from the ClinSeq project, which is a project to pilot the use of massively parallel sequencing in a clinical research context with a major aim to develop modes of returning results to individual subjects. The study has enrolled >900 subjects and generated exome sequence data on 572 subjects. These data are beginning to be interpreted and returned to the subjects, which provides examples of the potential usefulness and pitfalls of clinical genomics. There are numerous genetic results that can be readily derived from a genome including rare, high-penetrance traits, and carrier states. However, much work needs to be done to develop the tools and resources for genomic interpretation. The main lesson learned is that a genome sequence may be better considered as a health-care resource, rather than a test, one that can be interpreted and used over the lifetime of the patient.

From parallel to distributed computing for reactive scattering calculations

International Nuclear Information System (INIS)

Lagana, A.; Gervasi, O.; Baraglia, R.

1994-01-01

Some reactive scattering codes have been ported on different innovative computer architectures ranging from massively parallel machines to clustered workstations. The porting has required a drastic restructuring of the codes to single out computationally decoupled cpu intensive subsections. The suitability of different theoretical approaches for parallel and distributed computing restructuring is discussed and the efficiency of related algorithms evaluated

Investigating bacterial populations in styrene-degrading biofilters by 16S rDNA tag pyrosequencing.

Science.gov (United States)

Portune, Kevin J; Pérez, M Carmen; Álvarez-Hornos, F Javier; Gabaldón, Carmen

2015-01-01

Microbial biofilms are essential components in the elimination of pollutants within biofilters, yet still little is known regarding the complex relationships between microbial community structure and biodegradation function within these engineered ecosystems. To further explore this relationship, 16S rDNA tag pyrosequencing was applied to samples taken at four time points from a styrene-degrading biofilter undergoing variable operating conditions. Changes in microbial structure were observed between different stages of biofilter operation, and the level of styrene concentration was revealed to be a critical factor affecting these changes. Bacterial genera Azoarcus and Pseudomonas were among the dominant classified genera in the biofilter. Canonical correspondence analysis (CCA) and correlation analysis revealed that the genera Brevundimonas, Hydrogenophaga, and Achromobacter may play important roles in styrene degradation under increasing styrene concentrations. No significant correlations (P > 0.05) could be detected between biofilter operational/functional parameters and biodiversity measurements, although biological heterogeneity within biofilms and/or technical variability within pyrosequencing may have considerably affected these results. Percentages of selected bacterial taxonomic groups detected by fluorescence in situ hybridization (FISH) were compared to results from pyrosequencing in order to assess the effectiveness and limitations of each method for identifying each microbial taxon. Comparison of results revealed discrepancies between the two methods in the detected percentages of numerous taxonomic groups. Biases and technical limitations of both FISH and pyrosequencing, such as the binding of FISH probes to non-target microbial groups and lack of classification of sequences for defined taxonomic groups from pyrosequencing, may partially explain some differences between the two methods.

Rapid detection of the CYP2A6*12 hybrid allele by Pyrosequencing® technology

Directory of Open Access Journals (Sweden)

Gallagher Margaret L

2009-08-01

Full Text Available Abstract Background Identification of CYP2A6 alleles associated with reduced enzyme activity is important in the study of inter-individual differences in drug metabolism. CYP2A6*12 is a hybrid allele that results from unequal crossover between CYP2A6 and CYP2A7 genes. The 5' regulatory region and exons 1–2 are derived from CYP2A7, and exons 3–9 are derived from CYP2A6. Conventional methods for detection of CYP2A6*12 consist of two-step PCR protocols that are laborious and unsuitable for high-throughput genotyping. We developed a rapid and accurate method to detect the CYP2A6*12 allele by Pyrosequencing technology. Methods A single set of PCR primers was designed to specifically amplify both the CYP2A6*1 wild-type allele and the CYP2A6*12 hybrid allele. An internal Pyrosequencing primer was used to generate allele-specific sequence information, which detected homozygous wild-type, heterozygous hybrid, and homozygous hybrid alleles. We first validated the assay on 104 DNA samples that were also genotyped by conventional two-step PCR and by cycle sequencing. CYP2A6*12 allele frequencies were then determined using the Pyrosequencing assay on 181 multi-ethnic DNA samples from subjects of African American, European Caucasian, Pacific Rim, and Hispanic descent. Finally, we streamlined the Pyrosequencing assay by integrating liquid handling robotics into the workflow. Results Pyrosequencing results demonstrated 100% concordance with conventional two-step PCR and cycle sequencing methods. Allele frequency data showed slightly higher prevalence of the CYP2A6*12 allele in European Caucasians and Hispanics. Conclusion This Pyrosequencing assay proved to be a simple, rapid, and accurate alternative to conventional methods, which can be easily adapted to the needs of higher-throughput studies.

Scalable Strategies for Computing with Massive Data

Directory of Open Access Journals (Sweden)

Michael Kane

2013-11-01

Full Text Available This paper presents two complementary statistical computing frameworks that address challenges in parallel processing and the analysis of massive data. First, the foreach package allows users of the R programming environment to define parallel loops that may be run sequentially on a single machine, in parallel on a symmetric multiprocessing (SMP machine, or in cluster environments without platform-specific code. Second, the bigmemory package implements memory- and file-mapped data structures that provide (a access to arbitrarily large data while retaining a look and feel that is familiar to R users and (b data structures that are shared across processor cores in order to support efficient parallel computing techniques. Although these packages may be used independently, this paper shows how they can be used in combination to address challenges that have effectively been beyond the reach of researchers who lack specialized software development skills or expensive hardware.

Intragranular nucleation sites of massive gamma grains in a TiAl-based alloy

DEFF Research Database (Denmark)

Dey, Suhash Ranjan; Bouzy, E.; Hazotte, A.

2007-01-01

Massive gamma grains were generated in a TiAl-based alloy through ice-water quenching from the alpha domain. Apart from those located along alpha(2)/alpha(2) grain boundaries, a few massive gamma grains were detected inside the alpha(2) grains. Some of these intragranular grains were revealed...

Hypergraph partitioning implementation for parallelizing matrix-vector multiplication using CUDA GPU-based parallel computing

Science.gov (United States)

Murni, Bustamam, A.; Ernastuti, Handhika, T.; Kerami, D.

2017-07-01

Calculation of the matrix-vector multiplication in the real-world problems often involves large matrix with arbitrary size. Therefore, parallelization is needed to speed up the calculation process that usually takes a long time. Graph partitioning techniques that have been discussed in the previous studies cannot be used to complete the parallelized calculation of matrix-vector multiplication with arbitrary size. This is due to the assumption of graph partitioning techniques that can only solve the square and symmetric matrix. Hypergraph partitioning techniques will overcome the shortcomings of the graph partitioning technique. This paper addresses the efficient parallelization of matrix-vector multiplication through hypergraph partitioning techniques using CUDA GPU-based parallel computing. CUDA (compute unified device architecture) is a parallel computing platform and programming model that was created by NVIDIA and implemented by the GPU (graphics processing unit).

The Parallel System for Integrating Impact Models and Sectors (pSIMS)

Science.gov (United States)

Elliott, Joshua; Kelly, David; Chryssanthacopoulos, James; Glotter, Michael; Jhunjhnuwala, Kanika; Best, Neil; Wilde, Michael; Foster, Ian

2014-01-01

We present a framework for massively parallel climate impact simulations: the parallel System for Integrating Impact Models and Sectors (pSIMS). This framework comprises a) tools for ingesting and converting large amounts of data to a versatile datatype based on a common geospatial grid; b) tools for translating this datatype into custom formats for site-based models; c) a scalable parallel framework for performing large ensemble simulations, using any one of a number of different impacts models, on clusters, supercomputers, distributed grids, or clouds; d) tools and data standards for reformatting outputs to common datatypes for analysis and visualization; and e) methodologies for aggregating these datatypes to arbitrary spatial scales such as administrative and environmental demarcations. By automating many time-consuming and error-prone aspects of large-scale climate impacts studies, pSIMS accelerates computational research, encourages model intercomparison, and enhances reproducibility of simulation results. We present the pSIMS design and use example assessments to demonstrate its multi-model, multi-scale, and multi-sector versatility.

Time complexity analysis for distributed memory computers: implementation of parallel conjugate gradient method

NARCIS (Netherlands)

Hoekstra, A.G.; Sloot, P.M.A.; Haan, M.J.; Hertzberger, L.O.; van Leeuwen, J.

1991-01-01

New developments in Computer Science, both hardware and software, offer researchers, such as physicists, unprecedented possibilities to solve their computational intensive problems.However, full exploitation of e.g. new massively parallel computers, parallel languages or runtime environments

Optimisation of a parallel ocean general circulation model

Science.gov (United States)

Beare, M. I.; Stevens, D. P.

1997-10-01

This paper presents the development of a general-purpose parallel ocean circulation model, for use on a wide range of computer platforms, from traditional scalar machines to workstation clusters and massively parallel processors. Parallelism is provided, as a modular option, via high-level message-passing routines, thus hiding the technical intricacies from the user. An initial implementation highlights that the parallel efficiency of the model is adversely affected by a number of factors, for which optimisations are discussed and implemented. The resulting ocean code is portable and, in particular, allows science to be achieved on local workstations that could otherwise only be undertaken on state-of-the-art supercomputers.

Pyrosequencing and genetic diversity of microeukaryotes

DEFF Research Database (Denmark)

Harder, Christoffer Bugge

carefully selected waterworks (Article IV), where the bacterial metabolic diversity and its important for water purification was described. Building on this, the most important part of the thesis consists of two pyrosequencing analyses of protozoa with newly developed 18S primers. One specifically targets...... Cercozoa, a particularly abundant phylum of protozoa (Article III), on heath land that had been subjected to prolonged artificially induced drought in a Danish free-air climate-manipulation experiment (CLIMAITE). Article III showed that the testate cercozoan forms responded negatively to prolonged drought...

AMIDST: Analysis of MassIve Data STreams

DEFF Research Database (Denmark)

Masegosa, Andres; Martinez, Ana Maria; Borchani, Hanen

2015-01-01

The Analysis of MassIve Data STreams (AMIDST) Java toolbox provides a collection of scalable and parallel algorithms for inference and learning of hybrid Bayesian networks from data streams. The toolbox, available at http://amidst.github.io/toolbox/ under the Apache Software License version 2.......0, also efficiently leverages existing functionalities and algorithms by interfacing to software tools such as HUGIN and MOA....

Parallel adaptive simulations on unstructured meshes

International Nuclear Information System (INIS)

Shephard, M S; Jansen, K E; Sahni, O; Diachin, L A

2007-01-01

This paper discusses methods being developed by the ITAPS center to support the execution of parallel adaptive simulations on unstructured meshes. The paper first outlines the ITAPS approach to the development of interoperable mesh, geometry and field services to support the needs of SciDAC application in these areas. The paper then demonstrates the ability of unstructured adaptive meshing methods built on such interoperable services to effectively solve important physics problems. Attention is then focused on ITAPs' developing ability to solve adaptive unstructured mesh problems on massively parallel computers

Pyrosequencing of environmental soil samples reveals biodiversity of the Phytophthora resident community in chestnut forests.

Science.gov (United States)

Vannini, Andrea; Bruni, Natalia; Tomassini, Alessia; Franceschini, Selma; Vettraino, Anna Maria

2013-09-01

Pyrosequencing analysis was performed on soils from Italian chestnut groves to evaluate the diversity of the resident Phytophthora community. Sequences analysed with a custom database discriminated 15 pathogenic Phytophthoras including species common to chestnut soils, while a total of nine species were detected with baiting. The two sites studied differed in Phytophthora diversity and the presence of specific taxa responded to specific ecological traits of the sites. Furthermore, some species not previously recorded were represented by a discrete number of reads; among these species, Phytophthora ramorum was detected at both sites. Pyrosequencing was demonstrated to be a very sensitive technique to describe the Phytophthora community in soil and was able to detect species not easy to be isolated from soil with standard baiting techniques. In particular, pyrosequencing is an highly efficient tool for investigating the colonization of new environments by alien species, and for ecological and adaptive studies coupled with biological detection methods. This study represents the first application of pyrosequencing for describing Phytophthoras in environmental soil samples. © 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

Explorations of the implementation of a parallel IDW interpolation algorithm in a Linux cluster-based parallel GIS

Science.gov (United States)

Huang, Fang; Liu, Dingsheng; Tan, Xicheng; Wang, Jian; Chen, Yunping; He, Binbin

2011-04-01

To design and implement an open-source parallel GIS (OP-GIS) based on a Linux cluster, the parallel inverse distance weighting (IDW) interpolation algorithm has been chosen as an example to explore the working model and the principle of algorithm parallel pattern (APP), one of the parallelization patterns for OP-GIS. Based on an analysis of the serial IDW interpolation algorithm of GRASS GIS, this paper has proposed and designed a specific parallel IDW interpolation algorithm, incorporating both single process, multiple data (SPMD) and master/slave (M/S) programming modes. The main steps of the parallel IDW interpolation algorithm are: (1) the master node packages the related information, and then broadcasts it to the slave nodes; (2) each node calculates its assigned data extent along one row using the serial algorithm; (3) the master node gathers the data from all nodes; and (4) iterations continue until all rows have been processed, after which the results are outputted. According to the experiments performed in the course of this work, the parallel IDW interpolation algorithm can attain an efficiency greater than 0.93 compared with similar algorithms, which indicates that the parallel algorithm can greatly reduce processing time and maximize speed and performance.

A Self Consistent Multiprocessor Space Charge Algorithm that is Almost Embarrassingly Parallel

International Nuclear Information System (INIS)

Nissen, Edward; Erdelyi, B.; Manikonda, S.L.

2012-01-01

We present a space charge code that is self consistent, massively parallelizeable, and requires very little communication between computer nodes; making the calculation almost embarrassingly parallel. This method is implemented in the code COSY Infinity where the differential algebras used in this code are important to the algorithm's proper functioning. The method works by calculating the self consistent space charge distribution using the statistical moments of the test particles, and converting them into polynomial series coefficients. These coefficients are combined with differential algebraic integrals to form the potential, and electric fields. The result is a map which contains the effects of space charge. This method allows for massive parallelization since its statistics based solver doesn't require any binning of particles, and only requires a vector containing the partial sums of the statistical moments for the different nodes to be passed. All other calculations are done independently. The resulting maps can be used to analyze the system using normal form analysis, as well as advance particles in numbers and at speeds that were previously impossible.

Tinker-HP: a massively parallel molecular dynamics package for multiscale simulations of large complex systems with advanced point dipole polarizable force fields.

Science.gov (United States)

Lagardère, Louis; Jolly, Luc-Henri; Lipparini, Filippo; Aviat, Félix; Stamm, Benjamin; Jing, Zhifeng F; Harger, Matthew; Torabifard, Hedieh; Cisneros, G Andrés; Schnieders, Michael J; Gresh, Nohad; Maday, Yvon; Ren, Pengyu Y; Ponder, Jay W; Piquemal, Jean-Philip

2018-01-28

We present Tinker-HP, a massively MPI parallel package dedicated to classical molecular dynamics (MD) and to multiscale simulations, using advanced polarizable force fields (PFF) encompassing distributed multipoles electrostatics. Tinker-HP is an evolution of the popular Tinker package code that conserves its simplicity of use and its reference double precision implementation for CPUs. Grounded on interdisciplinary efforts with applied mathematics, Tinker-HP allows for long polarizable MD simulations on large systems up to millions of atoms. We detail in the paper the newly developed extension of massively parallel 3D spatial decomposition to point dipole polarizable models as well as their coupling to efficient Krylov iterative and non-iterative polarization solvers. The design of the code allows the use of various computer systems ranging from laboratory workstations to modern petascale supercomputers with thousands of cores. Tinker-HP proposes therefore the first high-performance scalable CPU computing environment for the development of next generation point dipole PFFs and for production simulations. Strategies linking Tinker-HP to Quantum Mechanics (QM) in the framework of multiscale polarizable self-consistent QM/MD simulations are also provided. The possibilities, performances and scalability of the software are demonstrated via benchmarks calculations using the polarizable AMOEBA force field on systems ranging from large water boxes of increasing size and ionic liquids to (very) large biosystems encompassing several proteins as well as the complete satellite tobacco mosaic virus and ribosome structures. For small systems, Tinker-HP appears to be competitive with the Tinker-OpenMM GPU implementation of Tinker. As the system size grows, Tinker-HP remains operational thanks to its access to distributed memory and takes advantage of its new algorithmic enabling for stable long timescale polarizable simulations. Overall, a several thousand-fold acceleration over

Exploration Of Deep Learning Algorithms Using Openacc Parallel Programming Model

KAUST Repository

Hamam, Alwaleed A.

2017-03-13

Deep learning is based on a set of algorithms that attempt to model high level abstractions in data. Specifically, RBM is a deep learning algorithm that used in the project to increase it\\'s time performance using some efficient parallel implementation by OpenACC tool with best possible optimizations on RBM to harness the massively parallel power of NVIDIA GPUs. GPUs development in the last few years has contributed to growing the concept of deep learning. OpenACC is a directive based ap-proach for computing where directives provide compiler hints to accelerate code. The traditional Restricted Boltzmann Ma-chine is a stochastic neural network that essentially perform a binary version of factor analysis. RBM is a useful neural net-work basis for larger modern deep learning model, such as Deep Belief Network. RBM parameters are estimated using an efficient training method that called Contrastive Divergence. Parallel implementation of RBM is available using different models such as OpenMP, and CUDA. But this project has been the first attempt to apply OpenACC model on RBM.

Exploration Of Deep Learning Algorithms Using Openacc Parallel Programming Model

KAUST Repository

Hamam, Alwaleed A.; Khan, Ayaz H.

2017-01-01

Deep learning is based on a set of algorithms that attempt to model high level abstractions in data. Specifically, RBM is a deep learning algorithm that used in the project to increase it's time performance using some efficient parallel implementation by OpenACC tool with best possible optimizations on RBM to harness the massively parallel power of NVIDIA GPUs. GPUs development in the last few years has contributed to growing the concept of deep learning. OpenACC is a directive based ap-proach for computing where directives provide compiler hints to accelerate code. The traditional Restricted Boltzmann Ma-chine is a stochastic neural network that essentially perform a binary version of factor analysis. RBM is a useful neural net-work basis for larger modern deep learning model, such as Deep Belief Network. RBM parameters are estimated using an efficient training method that called Contrastive Divergence. Parallel implementation of RBM is available using different models such as OpenMP, and CUDA. But this project has been the first attempt to apply OpenACC model on RBM.

Smoldyn on graphics processing units: massively parallel Brownian dynamics simulations.

Science.gov (United States)

Dematté, Lorenzo

2012-01-01

Space is a very important aspect in the simulation of biochemical systems; recently, the need for simulation algorithms able to cope with space is becoming more and more compelling. Complex and detailed models of biochemical systems need to deal with the movement of single molecules and particles, taking into consideration localized fluctuations, transportation phenomena, and diffusion. A common drawback of spatial models lies in their complexity: models can become very large, and their simulation could be time consuming, especially if we want to capture the systems behavior in a reliable way using stochastic methods in conjunction with a high spatial resolution. In order to deliver the promise done by systems biology to be able to understand a system as whole, we need to scale up the size of models we are able to simulate, moving from sequential to parallel simulation algorithms. In this paper, we analyze Smoldyn, a widely diffused algorithm for stochastic simulation of chemical reactions with spatial resolution and single molecule detail, and we propose an alternative, innovative implementation that exploits the parallelism of Graphics Processing Units (GPUs). The implementation executes the most computational demanding steps (computation of diffusion, unimolecular, and bimolecular reaction, as well as the most common cases of molecule-surface interaction) on the GPU, computing them in parallel on each molecule of the system. The implementation offers good speed-ups and real time, high quality graphics output

GPU-based parallel algorithm for blind image restoration using midfrequency-based methods

Science.gov (United States)

Xie, Lang; Luo, Yi-han; Bao, Qi-liang

2013-08-01

GPU-based general-purpose computing is a new branch of modern parallel computing, so the study of parallel algorithms specially designed for GPU hardware architecture is of great significance. In order to solve the problem of high computational complexity and poor real-time performance in blind image restoration, the midfrequency-based algorithm for blind image restoration was analyzed and improved in this paper. Furthermore, a midfrequency-based filtering method is also used to restore the image hardly with any recursion or iteration. Combining the algorithm with data intensiveness, data parallel computing and GPU execution model of single instruction and multiple threads, a new parallel midfrequency-based algorithm for blind image restoration is proposed in this paper, which is suitable for stream computing of GPU. In this algorithm, the GPU is utilized to accelerate the estimation of class-G point spread functions and midfrequency-based filtering. Aiming at better management of the GPU threads, the threads in a grid are scheduled according to the decomposition of the filtering data in frequency domain after the optimization of data access and the communication between the host and the device. The kernel parallelism structure is determined by the decomposition of the filtering data to ensure the transmission rate to get around the memory bandwidth limitation. The results show that, with the new algorithm, the operational speed is significantly increased and the real-time performance of image restoration is effectively improved, especially for high-resolution images.

Multibus-based parallel processor for simulation

Science.gov (United States)

Ogrady, E. P.; Wang, C.-H.

1983-01-01

A Multibus-based parallel processor simulation system is described. The system is intended to serve as a vehicle for gaining hands-on experience, testing system and application software, and evaluating parallel processor performance during development of a larger system based on the horizontal/vertical-bus interprocessor communication mechanism. The prototype system consists of up to seven Intel iSBC 86/12A single-board computers which serve as processing elements, a multiple transmission controller (MTC) designed to support system operation, and an Intel Model 225 Microcomputer Development System which serves as the user interface and input/output processor. All components are interconnected by a Multibus/IEEE 796 bus. An important characteristic of the system is that it provides a mechanism for a processing element to broadcast data to other selected processing elements. This parallel transfer capability is provided through the design of the MTC and a minor modification to the iSBC 86/12A board. The operation of the MTC, the basic hardware-level operation of the system, and pertinent details about the iSBC 86/12A and the Multibus are described.

Optimisation of a parallel ocean general circulation model

Directory of Open Access Journals (Sweden)

M. I. Beare

1997-10-01

Full Text Available This paper presents the development of a general-purpose parallel ocean circulation model, for use on a wide range of computer platforms, from traditional scalar machines to workstation clusters and massively parallel processors. Parallelism is provided, as a modular option, via high-level message-passing routines, thus hiding the technical intricacies from the user. An initial implementation highlights that the parallel efficiency of the model is adversely affected by a number of factors, for which optimisations are discussed and implemented. The resulting ocean code is portable and, in particular, allows science to be achieved on local workstations that could otherwise only be undertaken on state-of-the-art supercomputers.

Optimisation of a parallel ocean general circulation model

Directory of Open Access Journals (Sweden)

M. I. Beare

Full Text Available This paper presents the development of a general-purpose parallel ocean circulation model, for use on a wide range of computer platforms, from traditional scalar machines to workstation clusters and massively parallel processors. Parallelism is provided, as a modular option, via high-level message-passing routines, thus hiding the technical intricacies from the user. An initial implementation highlights that the parallel efficiency of the model is adversely affected by a number of factors, for which optimisations are discussed and implemented. The resulting ocean code is portable and, in particular, allows science to be achieved on local workstations that could otherwise only be undertaken on state-of-the-art supercomputers.

QuASAR-MPRA: accurate allele-specific analysis for massively parallel reporter assays.

Science.gov (United States)

Kalita, Cynthia A; Moyerbrailean, Gregory A; Brown, Christopher; Wen, Xiaoquan; Luca, Francesca; Pique-Regi, Roger

2018-03-01

The majority of the human genome is composed of non-coding regions containing regulatory elements such as enhancers, which are crucial for controlling gene expression. Many variants associated with complex traits are in these regions, and may disrupt gene regulatory sequences. Consequently, it is important to not only identify true enhancers but also to test if a variant within an enhancer affects gene regulation. Recently, allele-specific analysis in high-throughput reporter assays, such as massively parallel reporter assays (MPRAs), have been used to functionally validate non-coding variants. However, we are still missing high-quality and robust data analysis tools for these datasets. We have further developed our method for allele-specific analysis QuASAR (quantitative allele-specific analysis of reads) to analyze allele-specific signals in barcoded read counts data from MPRA. Using this approach, we can take into account the uncertainty on the original plasmid proportions, over-dispersion, and sequencing errors. The provided allelic skew estimate and its standard error also simplifies meta-analysis of replicate experiments. Additionally, we show that a beta-binomial distribution better models the variability present in the allelic imbalance of these synthetic reporters and results in a test that is statistically well calibrated under the null. Applying this approach to the MPRA data, we found 602 SNPs with significant (false discovery rate 10%) allele-specific regulatory function in LCLs. We also show that we can combine MPRA with QuASAR estimates to validate existing experimental and computational annotations of regulatory variants. Our study shows that with appropriate data analysis tools, we can improve the power to detect allelic effects in high-throughput reporter assays. http://github.com/piquelab/QuASAR/tree/master/mpra. fluca@wayne.edu or rpique@wayne.edu. Supplementary data are available online at Bioinformatics. © The Author (2017). Published by

Efficient linear precoding for massive MIMO systems using truncated polynomial expansion

KAUST Repository

Müller, Axel

2014-06-01

Massive multiple-input multiple-output (MIMO) techniques have been proposed as a solution to satisfy many requirements of next generation cellular systems. One downside of massive MIMO is the increased complexity of computing the precoding, especially since the relatively \\'antenna-efficient\\' regularized zero-forcing (RZF) is preferred to simple maximum ratio transmission. We develop in this paper a new class of precoders for single-cell massive MIMO systems. It is based on truncated polynomial expansion (TPE) and mimics the advantages of RZF, while offering reduced and scalable computational complexity that can be implemented in a convenient parallel fashion. Using random matrix theory we provide a closed-form expression of the signal-to-interference-and-noise ratio under TPE precoding and compare it to previous works on RZF. Furthermore, the sum rate maximizing polynomial coefficients in TPE precoding are calculated. By simulation, we find that to maintain a fixed peruser rate loss as compared to RZF, the polynomial degree does not need to scale with the system, but it should be increased with the quality of the channel knowledge and signal-to-noise ratio. © 2014 IEEE.

Parallel Task Processing on a Multicore Platform in a PC-based Control System for Parallel Kinematics

Directory of Open Access Journals (Sweden)

Harald Michalik

2009-02-01

Full Text Available Multicore platforms are such that have one physical processor chip with multiple cores interconnected via a chip level bus. Because they deliver a greater computing power through concurrency, offer greater system density multicore platforms provide best qualifications to address the performance bottleneck encountered in PC-based control systems for parallel kinematic robots with heavy CPU-load. Heavy load control tasks are generated by new control approaches that include features like singularity prediction, structure control algorithms, vision data integration and similar tasks. In this paper we introduce the parallel task scheduling extension of a communication architecture specially tailored for the development of PC-based control of parallel kinematics. The Sche-duling is specially designed for the processing on a multicore platform. It breaks down the serial task processing of the robot control cycle and extends it with parallel task processing paths in order to enhance the overall control performance.

A CFD Heterogeneous Parallel Solver Based on Collaborating CPU and GPU

Science.gov (United States)

Lai, Jianqi; Tian, Zhengyu; Li, Hua; Pan, Sha

2018-03-01

Since Graphic Processing Unit (GPU) has a strong ability of floating-point computation and memory bandwidth for data parallelism, it has been widely used in the areas of common computing such as molecular dynamics (MD), computational fluid dynamics (CFD) and so on. The emergence of compute unified device architecture (CUDA), which reduces the complexity of compiling program, brings the great opportunities to CFD. There are three different modes for parallel solution of NS equations: parallel solver based on CPU, parallel solver based on GPU and heterogeneous parallel solver based on collaborating CPU and GPU. As we can see, GPUs are relatively rich in compute capacity but poor in memory capacity and the CPUs do the opposite. We need to make full use of the GPUs and CPUs, so a CFD heterogeneous parallel solver based on collaborating CPU and GPU has been established. Three cases are presented to analyse the solver’s computational accuracy and heterogeneous parallel efficiency. The numerical results agree well with experiment results, which demonstrate that the heterogeneous parallel solver has high computational precision. The speedup on a single GPU is more than 40 for laminar flow, it decreases for turbulent flow, but it still can reach more than 20. What’s more, the speedup increases as the grid size becomes larger.

Massively parallel implementations of coupled-cluster methods for electron spin resonance spectra. I. Isotropic hyperfine coupling tensors in large radicals

Energy Technology Data Exchange (ETDEWEB)

Verma, Prakash; Morales, Jorge A., E-mail: jorge.morales@ttu.edu [Department of Chemistry and Biochemistry, Texas Tech University, P.O. Box 41061, Lubbock, Texas 79409-1061 (United States); Perera, Ajith [Department of Chemistry and Biochemistry, Texas Tech University, P.O. Box 41061, Lubbock, Texas 79409-1061 (United States); Department of Chemistry, Quantum Theory Project, University of Florida, Gainesville, Florida 32611 (United States)

2013-11-07

Coupled cluster (CC) methods provide highly accurate predictions of molecular properties, but their high computational cost has precluded their routine application to large systems. Fortunately, recent computational developments in the ACES III program by the Bartlett group [the OED/ERD atomic integral package, the super instruction processor, and the super instruction architecture language] permit overcoming that limitation by providing a framework for massively parallel CC implementations. In that scheme, we are further extending those parallel CC efforts to systematically predict the three main electron spin resonance (ESR) tensors (A-, g-, and D-tensors) to be reported in a series of papers. In this paper inaugurating that series, we report our new ACES III parallel capabilities that calculate isotropic hyperfine coupling constants in 38 neutral, cationic, and anionic radicals that include the {sup 11}B, {sup 17}O, {sup 9}Be, {sup 19}F, {sup 1}H, {sup 13}C, {sup 35}Cl, {sup 33}S,{sup 14}N, {sup 31}P, and {sup 67}Zn nuclei. Present parallel calculations are conducted at the Hartree-Fock (HF), second-order many-body perturbation theory [MBPT(2)], CC singles and doubles (CCSD), and CCSD with perturbative triples [CCSD(T)] levels using Roos augmented double- and triple-zeta atomic natural orbitals basis sets. HF results consistently overestimate isotropic hyperfine coupling constants. However, inclusion of electron correlation effects in the simplest way via MBPT(2) provides significant improvements in the predictions, but not without occasional failures. In contrast, CCSD results are consistently in very good agreement with experimental results. Inclusion of perturbative triples to CCSD via CCSD(T) leads to small improvements in the predictions, which might not compensate for the extra computational effort at a non-iterative N{sup 7}-scaling in CCSD(T). The importance of these accurate computations of isotropic hyperfine coupling constants to elucidate

Resolution of the neutron transport equation by massively parallel computer in the Cronos code

International Nuclear Information System (INIS)

Zardini, D.M.

1996-01-01

The feasibility of neutron transport problems parallel resolution by CRONOS code's SN module is here studied. In this report we give the first data about the parallel resolution by angular variable decomposition of the transport equation. Problems about parallel resolution by spatial variable decomposition and memory stage limits are also explained here. (author)

Dynamic file-access characteristics of a production parallel scientific workload

Science.gov (United States)

Kotz, David; Nieuwejaar, Nils

1994-01-01

Multiprocessors have permitted astounding increases in computational performance, but many cannot meet the intense I/O requirements of some scientific applications. An important component of any solution to this I/O bottleneck is a parallel file system that can provide high-bandwidth access to tremendous amounts of data in parallel to hundreds or thousands of processors. Most successful systems are based on a solid understanding of the expected workload, but thus far there have been no comprehensive workload characterizations of multiprocessor file systems. This paper presents the results of a three week tracing study in which all file-related activity on a massively parallel computer was recorded. Our instrumentation differs from previous efforts in that it collects information about every I/O request and about the mix of jobs running in a production environment. We also present the results of a trace-driven caching simulation and recommendations for designers of multiprocessor file systems.

Unified Lambert Tool for Massively Parallel Applications in Space Situational Awareness

Science.gov (United States)

Woollands, Robyn M.; Read, Julie; Hernandez, Kevin; Probe, Austin; Junkins, John L.

2018-03-01

This paper introduces a parallel-compiled tool that combines several of our recently developed methods for solving the perturbed Lambert problem using modified Chebyshev-Picard iteration. This tool (unified Lambert tool) consists of four individual algorithms, each of which is unique and better suited for solving a particular type of orbit transfer. The first is a Keplerian Lambert solver, which is used to provide a good initial guess (warm start) for solving the perturbed problem. It is also used to determine the appropriate algorithm to call for solving the perturbed problem. The arc length or true anomaly angle spanned by the transfer trajectory is the parameter that governs the automated selection of the appropriate perturbed algorithm, and is based on the respective algorithm convergence characteristics. The second algorithm solves the perturbed Lambert problem using the modified Chebyshev-Picard iteration two-point boundary value solver. This algorithm does not require a Newton-like shooting method and is the most efficient of the perturbed solvers presented herein, however the domain of convergence is limited to about a third of an orbit and is dependent on eccentricity. The third algorithm extends the domain of convergence of the modified Chebyshev-Picard iteration two-point boundary value solver to about 90% of an orbit, through regularization with the Kustaanheimo-Stiefel transformation. This is the second most efficient of the perturbed set of algorithms. The fourth algorithm uses the method of particular solutions and the modified Chebyshev-Picard iteration initial value solver for solving multiple revolution perturbed transfers. This method does require "shooting" but differs from Newton-like shooting methods in that it does not require propagation of a state transition matrix. The unified Lambert tool makes use of the General Mission Analysis Tool and we use it to compute thousands of perturbed Lambert trajectories in parallel on the Space Situational

An efficient implementation of a backpropagation learning algorithm on quadrics parallel supercomputer

International Nuclear Information System (INIS)

Taraglio, S.; Massaioli, F.

1995-08-01

A parallel implementation of a library to build and train Multi Layer Perceptrons via the Back Propagation algorithm is presented. The target machine is the SIMD massively parallel supercomputer Quadrics. Performance measures are provided on three different machines with different number of processors, for two network examples. A sample source code is given

Efficient high-precision matrix algebra on parallel architectures for nonlinear combinatorial optimization

KAUST Repository

Gunnels, John; Lee, Jon; Margulies, Susan

2010-01-01

We provide a first demonstration of the idea that matrix-based algorithms for nonlinear combinatorial optimization problems can be efficiently implemented. Such algorithms were mainly conceived by theoretical computer scientists for proving efficiency. We are able to demonstrate the practicality of our approach by developing an implementation on a massively parallel architecture, and exploiting scalable and efficient parallel implementations of algorithms for ultra high-precision linear algebra. Additionally, we have delineated and implemented the necessary algorithmic and coding changes required in order to address problems several orders of magnitude larger, dealing with the limits of scalability from memory footprint, computational efficiency, reliability, and interconnect perspectives. © Springer and Mathematical Programming Society 2010.

Efficient high-precision matrix algebra on parallel architectures for nonlinear combinatorial optimization

KAUST Repository

Gunnels, John

2010-06-01

We provide a first demonstration of the idea that matrix-based algorithms for nonlinear combinatorial optimization problems can be efficiently implemented. Such algorithms were mainly conceived by theoretical computer scientists for proving efficiency. We are able to demonstrate the practicality of our approach by developing an implementation on a massively parallel architecture, and exploiting scalable and efficient parallel implementations of algorithms for ultra high-precision linear algebra. Additionally, we have delineated and implemented the necessary algorithmic and coding changes required in order to address problems several orders of magnitude larger, dealing with the limits of scalability from memory footprint, computational efficiency, reliability, and interconnect perspectives. © Springer and Mathematical Programming Society 2010.

Tuning HDF5 subfiling performance on parallel file systems

Energy Technology Data Exchange (ETDEWEB)

Byna, Suren [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Chaarawi, Mohamad [Intel Corp. (United States); Koziol, Quincey [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Mainzer, John [The HDF Group (United States); Willmore, Frank [The HDF Group (United States)

2017-05-12

Subfiling is a technique used on parallel file systems to reduce locking and contention issues when multiple compute nodes interact with the same storage target node. Subfiling provides a compromise between the single shared file approach that instigates the lock contention problems on parallel file systems and having one file per process, which results in generating a massive and unmanageable number of files. In this paper, we evaluate and tune the performance of recently implemented subfiling feature in HDF5. In specific, we explain the implementation strategy of subfiling feature in HDF5, provide examples of using the feature, and evaluate and tune parallel I/O performance of this feature with parallel file systems of the Cray XC40 system at NERSC (Cori) that include a burst buffer storage and a Lustre disk-based storage. We also evaluate I/O performance on the Cray XC30 system, Edison, at NERSC. Our results show performance benefits of 1.2X to 6X performance advantage with subfiling compared to writing a single shared HDF5 file. We present our exploration of configurations, such as the number of subfiles and the number of Lustre storage targets to storing files, as optimization parameters to obtain superior I/O performance. Based on this exploration, we discuss recommendations for achieving good I/O performance as well as limitations with using the subfiling feature.

Parallel PDE-Based Simulations Using the Common Component Architecture

International Nuclear Information System (INIS)

McInnes, Lois C.; Allan, Benjamin A.; Armstrong, Robert; Benson, Steven J.; Bernholdt, David E.; Dahlgren, Tamara L.; Diachin, Lori; Krishnan, Manoj Kumar; Kohl, James A.; Larson, J. Walter; Lefantzi, Sophia; Nieplocha, Jarek; Norris, Boyana; Parker, Steven G.; Ray, Jaideep; Zhou, Shujia

2006-01-01

The complexity of parallel PDE-based simulations continues to increase as multimodel, multiphysics, and multi-institutional projects become widespread. A goal of component based software engineering in such large-scale simulations is to help manage this complexity by enabling better interoperability among various codes that have been independently developed by different groups. The Common Component Architecture (CCA) Forum is defining a component architecture specification to address the challenges of high-performance scientific computing. In addition, several execution frameworks, supporting infrastructure, and general purpose components are being developed. Furthermore, this group is collaborating with others in the high-performance computing community to design suites of domain-specific component interface specifications and underlying implementations. This chapter discusses recent work on leveraging these CCA efforts in parallel PDE-based simulations involving accelerator design, climate modeling, combustion, and accidental fires and explosions. We explain how component technology helps to address the different challenges posed by each of these applications, and we highlight how component interfaces built on existing parallel toolkits facilitate the reuse of software for parallel mesh manipulation, discretization, linear algebra, integration, optimization, and parallel data redistribution. We also present performance data to demonstrate the suitability of this approach, and we discuss strategies for applying component technologies to both new and existing applications

User's guide of TOUGH2-EGS-MP: A Massively Parallel Simulator with Coupled Geomechanics for Fluid and Heat Flow in Enhanced Geothermal Systems VERSION 1.0

Energy Technology Data Exchange (ETDEWEB)

Xiong, Yi [Colorado School of Mines, Golden, CO (United States); Fakcharoenphol, Perapon [Colorado School of Mines, Golden, CO (United States); Wang, Shihao [Colorado School of Mines, Golden, CO (United States); Winterfeld, Philip H. [Colorado School of Mines, Golden, CO (United States); Zhang, Keni [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Wu, Yu-Shu [Colorado School of Mines, Golden, CO (United States)

2013-12-01

TOUGH2-EGS-MP is a parallel numerical simulation program coupling geomechanics with fluid and heat flow in fractured and porous media, and is applicable for simulation of enhanced geothermal systems (EGS). TOUGH2-EGS-MP is based on the TOUGH2-MP code, the massively parallel version of TOUGH2. In TOUGH2-EGS-MP, the fully-coupled flow-geomechanics model is developed from linear elastic theory for thermo-poro-elastic systems and is formulated in terms of mean normal stress as well as pore pressure and temperature. Reservoir rock properties such as porosity and permeability depend on rock deformation, and the relationships between these two, obtained from poro-elasticity theories and empirical correlations, are incorporated into the simulation. This report provides the user with detailed information on the TOUGH2-EGS-MP mathematical model and instructions for using it for Thermal-Hydrological-Mechanical (THM) simulations. The mathematical model includes the fluid and heat flow equations, geomechanical equation, and discretization of those equations. In addition, the parallel aspects of the code, such as domain partitioning and communication between processors, are also included. Although TOUGH2-EGS-MP has the capability for simulating fluid and heat flows coupled with geomechanical effects, it is up to the user to select the specific coupling process, such as THM or only TH, in a simulation. There are several example problems illustrating applications of this program. These example problems are described in detail and their input data are presented. Their results demonstrate that this program can be used for field-scale geothermal reservoir simulation in porous and fractured media with fluid and heat flow coupled with geomechanical effects.

Rapid Molecular Identification of Human Taeniid Cestodes by Pyrosequencing Approach

Science.gov (United States)

Thanchomnang, Tongjit; Tantrawatpan, Chairat; Intapan, Pewpan M.; Sanpool, Oranuch; Janwan, Penchom; Lulitanond, Viraphong; Tourtip, Somjintana; Yamasaki, Hiroshi; Maleewong, Wanchai

2014-01-01

Taenia saginata, T. solium, and T. asiatica are causative agents of taeniasis in humans. The difficulty of morphological identification of human taeniids can lead to misdiagnosis or confusion. To overcome this problem, several molecular methods have been developed, but use of these tends to be time-consuming. Here, a rapid and high-throughput pyrosequencing approach was developed for the identification of three human taeniids originating from various countries. Primers targeting the mitochondrial cytochrome c oxidase subunit 1 (cox1) gene of the three Taenia species were designed. Variations in a 26-nucleotide target region were used for identification. The reproducibility and accuracy of the pyrosequencing technology was confirmed by Sanger sequencing. This technique will be a valuable tool to distinguish between sympatric human taeniids that occur in Thailand, Asia and Pacific countries. This method could potentially be used for the molecular identification of the taeniid species that might be associated with suspicious cysts and lesions, or cyst residues in humans or livestock at the slaughterhouse. PMID:24945530

A visualization of null geodesics for the bonnor massive dipole

Directory of Open Access Journals (Sweden)

G. Andree Oliva Mercado

2015-08-01

Full Text Available In this work we simulate null geodesics for the Bonnor massive dipole metric by implementing a symbolic-numerical algorithm in Sage and Python. This program is also capable of visualizing in 3D, in principle, the geodesics for any given metric. Geodesics are launched from a common point, collectively forming a cone of light beams, simulating a solid-angle section of a point source in front of a massive object with a magnetic field. Parallel light beams also were considered, and their bending due to the curvature of the space-time was simulated.

On the adequacy of message-passing parallel supercomputers for solving neutron transport problems

International Nuclear Information System (INIS)

Azmy, Y.Y.

1990-01-01

A coarse-grained, static-scheduling parallelization of the standard iterative scheme used for solving the discrete-ordinates approximation of the neutron transport equation is described. The parallel algorithm is based on a decomposition of the angular domain along the discrete ordinates, thus naturally producing a set of completely uncoupled systems of equations in each iteration. Implementation of the parallel code on Intcl's iPSC/2 hypercube, and solutions to test problems are presented as evidence of the high speedup and efficiency of the parallel code. The performance of the parallel code on the iPSC/2 is analyzed, and a model for the CPU time as a function of the problem size (order of angular quadrature) and the number of participating processors is developed and validated against measured CPU times. The performance model is used to speculate on the potential of massively parallel computers for significantly speeding up real-life transport calculations at acceptable efficiencies. We conclude that parallel computers with a few hundred processors are capable of producing large speedups at very high efficiencies in very large three-dimensional problems. 10 refs., 8 figs

A Cyber-ITS Framework for Massive Traffic Data Analysis Using Cyber Infrastructure

Directory of Open Access Journals (Sweden)

Yingjie Xia

2013-01-01

Full Text Available Traffic data is commonly collected from widely deployed sensors in urban areas. This brings up a new research topic, data-driven intelligent transportation systems (ITSs, which means to integrate heterogeneous traffic data from different kinds of sensors and apply it for ITS applications. This research, taking into consideration the significant increase in the amount of traffic data and the complexity of data analysis, focuses mainly on the challenge of solving data-intensive and computation-intensive problems. As a solution to the problems, this paper proposes a Cyber-ITS framework to perform data analysis on Cyber Infrastructure (CI, by nature parallel-computing hardware and software systems, in the context of ITS. The techniques of the framework include data representation, domain decomposition, resource allocation, and parallel processing. All these techniques are based on data-driven and application-oriented models and are organized as a component-and-workflow-based model in order to achieve technical interoperability and data reusability. A case study of the Cyber-ITS framework is presented later based on a traffic state estimation application that uses the fusion of massive Sydney Coordinated Adaptive Traffic System (SCATS data and GPS data. The results prove that the Cyber-ITS-based implementation can achieve a high accuracy rate of traffic state estimation and provide a significant computational speedup for the data fusion by parallel computing.

Pyrosequencing the Midgut Transcriptome of the Banana Weevil Cosmopolites sordidus (Germar (Coleoptera: Curculionidae Reveals Multiple Protease-Like Transcripts.

Directory of Open Access Journals (Sweden)

Arnubio Valencia

Full Text Available The banana weevil Cosmopolites sordidus is an important and serious insect pest in most banana and plantain-growing areas of the world. In spite of the economic importance of this insect pest very little genomic and transcriptomic information exists for this species. In the present study, we characterized the midgut transcriptome of C. sordidus using massive 454-pyrosequencing. We generated over 590,000 sequencing reads that assembled into 30,840 contigs with more than 400 bp, representing a significant expansion of existing sequences available for this insect pest. Among them, 16,427 contigs contained one or more GO terms. In addition, 15,263 contigs were assigned an EC number. In-depth transcriptome analysis identified genes potentially involved in insecticide resistance, peritrophic membrane biosynthesis, immunity-related function and defense against pathogens, and Bacillus thuringiensis toxins binding proteins as well as multiple enzymes involved with protein digestion. This transcriptome will provide a valuable resource for understanding larval physiology and for identifying novel target sites and management approaches for this important insect pest.

Pyrosequencing the Midgut Transcriptome of the Banana Weevil Cosmopolites sordidus (Germar) (Coleoptera: Curculionidae) Reveals Multiple Protease-Like Transcripts.

Science.gov (United States)

Valencia, Arnubio; Wang, Haichuan; Soto, Alberto; Aristizabal, Manuel; Arboleda, Jorge W; Eyun, Seong-Il; Noriega, Daniel D; Siegfried, Blair

2016-01-01

The banana weevil Cosmopolites sordidus is an important and serious insect pest in most banana and plantain-growing areas of the world. In spite of the economic importance of this insect pest very little genomic and transcriptomic information exists for this species. In the present study, we characterized the midgut transcriptome of C. sordidus using massive 454-pyrosequencing. We generated over 590,000 sequencing reads that assembled into 30,840 contigs with more than 400 bp, representing a significant expansion of existing sequences available for this insect pest. Among them, 16,427 contigs contained one or more GO terms. In addition, 15,263 contigs were assigned an EC number. In-depth transcriptome analysis identified genes potentially involved in insecticide resistance, peritrophic membrane biosynthesis, immunity-related function and defense against pathogens, and Bacillus thuringiensis toxins binding proteins as well as multiple enzymes involved with protein digestion. This transcriptome will provide a valuable resource for understanding larval physiology and for identifying novel target sites and management approaches for this important insect pest.

454 pyrosequencing based transcriptome analysis of Zygaena filipendulae with focus on genes involved in biosynthesis of cyanogenic glucosides.

Science.gov (United States)

Zagrobelny, Mika; Scheibye-Alsing, Karsten; Jensen, Niels Bjerg; Møller, Birger Lindberg; Gorodkin, Jan; Bak, Søren

2009-12-02

An essential driving component in the co-evolution of plants and insects is the ability to produce and handle bioactive compounds. Plants produce bioactive natural products for defense, but some insects detoxify and/or sequester the compounds, opening up for new niches with fewer competitors. To study the molecular mechanism behind the co-adaption in plant-insect interactions, we have investigated the interactions between Lotus corniculatus and Zygaena filipendulae. They both contain cyanogenic glucosides which liberate toxic hydrogen cyanide upon breakdown. Moths belonging to the Zygaena family are the only insects known, able to carry out both de novo biosynthesis and sequestration of the same cyanogenic glucosides as those from their feed plants. The biosynthetic pathway for cyanogenic glucoside biosynthesis in Z. filipendulae proceeds using the same intermediates as in the well known pathway from plants, but none of the enzymes responsible have been identified. A genomics strategy founded on 454 pyrosequencing of the Z. filipendulae transcriptome was undertaken to identify some of these enzymes in Z. filipendulae. Comparisons of the Z. filipendulae transcriptome with the sequenced genomes of Bombyx mori, Drosophila melanogaster, Tribolium castaneum, Apis mellifera and Anopheles gambiae indicate a high coverage of the Z. filipendulae transcriptome. 11% of the Z. filipendulae transcriptome sequences were assigned to Gene Ontology categories. Candidate genes for enzymes functioning in the biosynthesis of cyanogenic glucosides (cytochrome P450 and family 1 glycosyltransferases) were identified based on sequence length, number of copies and presence/absence of close homologs in D. melanogaster, B. mori and the cyanogenic butterfly Heliconius. Examination of biased codon usage, GC content and selection on gene candidates support the notion of cyanogenesis as an "old" trait within Ditrysia, as well as its origins being convergent between plants and insects

454 pyrosequencing based transcriptome analysis of Zygaena filipendulae with focus on genes involved in biosynthesis of cyanogenic glucosides

Directory of Open Access Journals (Sweden)

Jensen Niels

2009-12-01

Full Text Available Abstract Background An essential driving component in the co-evolution of plants and insects is the ability to produce and handle bioactive compounds. Plants produce bioactive natural products for defense, but some insects detoxify and/or sequester the compounds, opening up for new niches with fewer competitors. To study the molecular mechanism behind the co-adaption in plant-insect interactions, we have investigated the interactions between Lotus corniculatus and Zygaena filipendulae. They both contain cyanogenic glucosides which liberate toxic hydrogen cyanide upon breakdown. Moths belonging to the Zygaena family are the only insects known, able to carry out both de novo biosynthesis and sequestration of the same cyanogenic glucosides as those from their feed plants. The biosynthetic pathway for cyanogenic glucoside biosynthesis in Z. filipendulae proceeds using the same intermediates as in the well known pathway from plants, but none of the enzymes responsible have been identified. A genomics strategy founded on 454 pyrosequencing of the Z. filipendulae transcriptome was undertaken to identify some of these enzymes in Z. filipendulae. Results Comparisons of the Z. filipendulae transcriptome with the sequenced genomes of Bombyx mori, Drosophila melanogaster, Tribolium castaneum, Apis mellifera and Anopheles gambiae indicate a high coverage of the Z. filipendulae transcriptome. 11% of the Z. filipendulae transcriptome sequences were assigned to Gene Ontology categories. Candidate genes for enzymes functioning in the biosynthesis of cyanogenic glucosides (cytochrome P450 and family 1 glycosyltransferases were identified based on sequence length, number of copies and presence/absence of close homologs in D. melanogaster, B. mori and the cyanogenic butterfly Heliconius. Examination of biased codon usage, GC content and selection on gene candidates support the notion of cyanogenesis as an "old" trait within Ditrysia, as well as its origins being

Pyrosequencing based assessment of bacterial diversity in Turkish Rhipicephalus annulatus and Dermacentor marginatus ticks (Acari: Ixodidae).

Science.gov (United States)

Tekin, Saban; Dowd, Scot E; Davinic, Marko; Bursali, Ahmet; Keskin, Adem

2017-03-01

Ticks continue to be a threat to human and animal health in Turkey, as they are considered important vectors of human and animal diseases. The objectives of this investigation are to characterize the microbial communities of two tick species, Rhipicephalus annulatus and Dermacenter marginatus, analyze patterns of co-occurrence among microbial taxa, identify and compare pathogens contributing human diseases, and determine whether avirulent symbionts could exclude human pathogens from tick communities. Furthermore, this study explores a microbiome of the R. annulatus and D. marginatus via the bacterial 16S tag-encoded FLX-titanium amplicon pyrosequencing (bTEFAP) technique to describe their bacterial diversity. Pyrosequencing was performed on adult males and females isolated from humans from two high-risk Turkish provinces, Sivas and Amasya, during tick outbreaks in 2009. A total of 36,253 sequences were utilized for analyses of the 8 tick samples. Several pathogenic genera such as Francisella, Coxiella, Rickettsia, and Shigella were detected in the ticks tested. The most distinguishable difference between the two species of ticks was the lack of known human pathogen Rickettsia in R. annulatus and in samples 9 and 10 of D. marginatus. These samples had higher relative abundance of Flavobacterium sp., Curvibacter sp., Acidovorax sp., and Bacteroidaceae genera mostly representing symbionts which form a large component of normal tick microbiota. The outcome of this study is consistent with the predictions of the community ecological theory that diversity-rich bacteriomes are more resistant to bacterial invasion (and consequent pathogen dissemination) than diversity-deprived ones.

Detection of polyoma virus in brain tissue of patients with progressive multifocal leukoencephalopathy by real-time PCR and pyrosequencing.

Science.gov (United States)

Beck, Rose C; Kohn, Debra J; Tuohy, Marion J; Prayson, Richard A; Yen-Lieberman, Belinda; Procop, Gary W

2004-03-01

We evaluated 2 methods, a LightCycler PCR assay and pyrosequencing for the detection of the JC polyoma virus (JCV) in fixed brain tissue of 10 patients with and 3 control patients without progressive multifocal leukoencephalopathy (PML). Nucleic acid extraction was performed after deparaffinization and proteinase K digestion. The LightCycler assay differentiates the BK virus (BKV), JCV, and SV40 using melt curve analysis. Conventional PCR was used with the same primers to generate products for pyrosequencing. Two sequencing primers were used that differentiate the polyoma viruses. Seven of 11 biopsies (1 patient had 2 biopsies) with PML were positive for JCV by real-time PCR and/or PCR/pyrosequencing. Three of 4 remaining biopsies were positive by real-time PCR but had melting points between JCV and SV40. The 4 specimens that were negative or atypical by LightCycler PCR were positive by traditional PCR, but 1 had an amplicon of lower molecular weight by gel electrophoresis. These were shown to represent JCV by at least 1 of the 2 pyrosequencing primers. The biopsies from patients without PML were PCR negative. Both the LightCycler and pyrosequencing assays are useful for confirming JCV in brain biopsies from patients with PML, but variant JCVs may require supplementary methods to confirm JCV infection.

A two-level parallel direct search implementation for arbitrarily sized objective functions

Energy Technology Data Exchange (ETDEWEB)

Hutchinson, S.A.; Shadid, N.; Moffat, H.K. [Sandia National Labs., Albuquerque, NM (United States)] [and others

1994-12-31

In the past, many optimization schemes for massively parallel computers have attempted to achieve parallel efficiency using one of two methods. In the case of large and expensive objective function calculations, the optimization itself may be run in serial and the objective function calculations parallelized. In contrast, if the objective function calculations are relatively inexpensive and can be performed on a single processor, then the actual optimization routine itself may be parallelized. In this paper, a scheme based upon the Parallel Direct Search (PDS) technique is presented which allows the objective function calculations to be done on an arbitrarily large number (p{sub 2}) of processors. If, p, the number of processors available, is greater than or equal to 2p{sub 2} then the optimization may be parallelized as well. This allows for efficient use of computational resources since the objective function calculations can be performed on the number of processors that allow for peak parallel efficiency and then further speedup may be achieved by parallelizing the optimization. Results are presented for an optimization problem which involves the solution of a PDE using a finite-element algorithm as part of the objective function calculation. The optimum number of processors for the finite-element calculations is less than p/2. Thus, the PDS method is also parallelized. Performance comparisons are given for a nCUBE 2 implementation.

3D multiphysics modeling of superconducting cavities with a massively parallel simulation suite

Directory of Open Access Journals (Sweden)

Oleksiy Kononenko

2017-10-01

Full Text Available Radiofrequency cavities based on superconducting technology are widely used in particle accelerators for various applications. The cavities usually have high quality factors and hence narrow bandwidths, so the field stability is sensitive to detuning from the Lorentz force and external loads, including vibrations and helium pressure variations. If not properly controlled, the detuning can result in a serious performance degradation of a superconducting accelerator, so an understanding of the underlying detuning mechanisms can be very helpful. Recent advances in the simulation suite ace3p have enabled realistic multiphysics characterization of such complex accelerator systems on supercomputers. In this paper, we present the new capabilities in ace3p for large-scale 3D multiphysics modeling of superconducting cavities, in particular, a parallel eigensolver for determining mechanical resonances, a parallel harmonic response solver to calculate the response of a cavity to external vibrations, and a numerical procedure to decompose mechanical loads, such as from the Lorentz force or piezoactuators, into the corresponding mechanical modes. These capabilities have been used to do an extensive rf-mechanical analysis of dressed TESLA-type superconducting cavities. The simulation results and their implications for the operational stability of the Linac Coherent Light Source-II are discussed.

Multirate-based fast parallel algorithms for 2-D DHT-based real-valued discrete Gabor transform.

Science.gov (United States)

Tao, Liang; Kwan, Hon Keung

2012-07-01

Novel algorithms for the multirate and fast parallel implementation of the 2-D discrete Hartley transform (DHT)-based real-valued discrete Gabor transform (RDGT) and its inverse transform are presented in this paper. A 2-D multirate-based analysis convolver bank is designed for the 2-D RDGT, and a 2-D multirate-based synthesis convolver bank is designed for the 2-D inverse RDGT. The parallel channels in each of the two convolver banks have a unified structure and can apply the 2-D fast DHT algorithm to speed up their computations. The computational complexity of each parallel channel is low and is independent of the Gabor oversampling rate. All the 2-D RDGT coefficients of an image are computed in parallel during the analysis process and can be reconstructed in parallel during the synthesis process. The computational complexity and time of the proposed parallel algorithms are analyzed and compared with those of the existing fastest algorithms for 2-D discrete Gabor transforms. The results indicate that the proposed algorithms are the fastest, which make them attractive for real-time image processing.

Rapid detection and subtyping of human influenza A viruses and reassortants by pyrosequencing.

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Yi-Mo Deng

Full Text Available BACKGROUND: Given the continuing co-circulation of the 2009 H1N1 pandemic influenza A viruses with seasonal H3N2 viruses, rapid and reliable detection of newly emerging influenza reassortant viruses is important to enhance our influenza surveillance. METHODOLOGY/PRINCIPAL FINDINGS: A novel pyrosequencing assay was developed for the rapid identification and subtyping of potential human influenza A virus reassortants based on all eight gene segments of the virus. Except for HA and NA genes, one universal set of primers was used to amplify and subtype each of the six internal genes. With this method, all eight gene segments of 57 laboratory isolates and 17 original specimens of seasonal H1N1, H3N2 and 2009 H1N1 pandemic viruses were correctly matched with their corresponding subtypes. In addition, this method was shown to be capable of detecting reassortant viruses by correctly identifying the source of all 8 gene segments from three vaccine production reassortant viruses and three H1N2 viruses. CONCLUSIONS/SIGNIFICANCE: In summary, this pyrosequencing assay is a sensitive and specific procedure for screening large numbers of viruses for reassortment events amongst the commonly circulating human influenza A viruses, which is more rapid and cheaper than using conventional sequencing approaches.

Rapid detection and subtyping of human influenza A viruses and reassortants by pyrosequencing.

Science.gov (United States)

Deng, Yi-Mo; Caldwell, Natalie; Barr, Ian G

2011-01-01

Given the continuing co-circulation of the 2009 H1N1 pandemic influenza A viruses with seasonal H3N2 viruses, rapid and reliable detection of newly emerging influenza reassortant viruses is important to enhance our influenza surveillance. A novel pyrosequencing assay was developed for the rapid identification and subtyping of potential human influenza A virus reassortants based on all eight gene segments of the virus. Except for HA and NA genes, one universal set of primers was used to amplify and subtype each of the six internal genes. With this method, all eight gene segments of 57 laboratory isolates and 17 original specimens of seasonal H1N1, H3N2 and 2009 H1N1 pandemic viruses were correctly matched with their corresponding subtypes. In addition, this method was shown to be capable of detecting reassortant viruses by correctly identifying the source of all 8 gene segments from three vaccine production reassortant viruses and three H1N2 viruses. In summary, this pyrosequencing assay is a sensitive and specific procedure for screening large numbers of viruses for reassortment events amongst the commonly circulating human influenza A viruses, which is more rapid and cheaper than using conventional sequencing approaches.

A Pervasive Parallel Processing Framework for Data Visualization and Analysis at Extreme Scale

Energy Technology Data Exchange (ETDEWEB)

Moreland, Kenneth [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Geveci, Berk [Kitware, Inc., Clifton Park, NY (United States)

2014-11-01

The evolution of the computing world from teraflop to petaflop has been relatively effortless, with several of the existing programming models scaling effectively to the petascale. The migration to exascale, however, poses considerable challenges. All industry trends infer that the exascale machine will be built using processors containing hundreds to thousands of cores per chip. It can be inferred that efficient concurrency on exascale machines requires a massive amount of concurrent threads, each performing many operations on a localized piece of data. Currently, visualization libraries and applications are based off what is known as the visualization pipeline. In the pipeline model, algorithms are encapsulated as filters with inputs and outputs. These filters are connected by setting the output of one component to the input of another. Parallelism in the visualization pipeline is achieved by replicating the pipeline for each processing thread. This works well for today’s distributed memory parallel computers but cannot be sustained when operating on processors with thousands of cores. Our project investigates a new visualization framework designed to exhibit the pervasive parallelism necessary for extreme scale machines. Our framework achieves this by defining algorithms in terms of worklets, which are localized stateless operations. Worklets are atomic operations that execute when invoked unlike filters, which execute when a pipeline request occurs. The worklet design allows execution on a massive amount of lightweight threads with minimal overhead. Only with such fine-grained parallelism can we hope to fill the billions of threads we expect will be necessary for efficient computation on an exascale machine.

Molecular diagnosis of glycogen storage disease and disorders with overlapping clinical symptoms by massive parallel sequencing.

Science.gov (United States)

Vega, Ana I; Medrano, Celia; Navarrete, Rosa; Desviat, Lourdes R; Merinero, Begoña; Rodríguez-Pombo, Pilar; Vitoria, Isidro; Ugarte, Magdalena; Pérez-Cerdá, Celia; Pérez, Belen

2016-10-01

Glycogen storage disease (GSD) is an umbrella term for a group of genetic disorders that involve the abnormal metabolism of glycogen; to date, 23 types of GSD have been identified. The nonspecific clinical presentation of GSD and the lack of specific biomarkers mean that Sanger sequencing is now widely relied on for making a diagnosis. However, this gene-by-gene sequencing technique is both laborious and costly, which is a consequence of the number of genes to be sequenced and the large size of some genes. This work reports the use of massive parallel sequencing to diagnose patients at our laboratory in Spain using either a customized gene panel (targeted exome sequencing) or the Illumina Clinical-Exome TruSight One Gene Panel (clinical exome sequencing (CES)). Sequence variants were matched against biochemical and clinical hallmarks. Pathogenic mutations were detected in 23 patients. Twenty-two mutations were recognized (mostly loss-of-function mutations), including 11 that were novel in GSD-associated genes. In addition, CES detected five patients with mutations in ALDOB, LIPA, NKX2-5, CPT2, or ANO5. Although these genes are not involved in GSD, they are associated with overlapping phenotypic characteristics such as hepatic, muscular, and cardiac dysfunction. These results show that next-generation sequencing, in combination with the detection of biochemical and clinical hallmarks, provides an accurate, high-throughput means of making genetic diagnoses of GSD and related diseases.Genet Med 18 10, 1037-1043.

Comprehensive microRNA profiling in B-cells of human centenarians by massively parallel sequencing

Directory of Open Access Journals (Sweden)

Gombar Saurabh

2012-07-01

Full Text Available Abstract Background MicroRNAs (miRNAs are small, non-coding RNAs that regulate gene expression and play a critical role in development, homeostasis, and disease. Despite their demonstrated roles in age-associated pathologies, little is known about the role of miRNAs in human aging and longevity. Results We employed massively parallel sequencing technology to identify miRNAs expressed in B-cells from Ashkenazi Jewish centenarians, i.e., those living to a hundred and a human model of exceptional longevity, and younger controls without a family history of longevity. With data from 26.7 million reads comprising 9.4 × 108 bp from 3 centenarian and 3 control individuals, we discovered a total of 276 known miRNAs and 8 unknown miRNAs ranging several orders of magnitude in expression levels, a typical characteristics of saturated miRNA-sequencing. A total of 22 miRNAs were found to be significantly upregulated, with only 2 miRNAs downregulated, in centenarians as compared to controls. Gene Ontology analysis of the predicted and validated targets of the 24 differentially expressed miRNAs indicated enrichment of functional pathways involved in cell metabolism, cell cycle, cell signaling, and cell differentiation. A cross sectional expression analysis of the differentially expressed miRNAs in B-cells from Ashkenazi Jewish individuals between the 50th and 100th years of age indicated that expression levels of miR-363* declined significantly with age. Centenarians, however, maintained the youthful expression level. This result suggests that miR-363* may be a candidate longevity-associated miRNA. Conclusion Our comprehensive miRNA data provide a resource for further studies to identify genetic pathways associated with aging and longevity in humans.

A scalable method for parallelizing sampling-based motion planning algorithms

KAUST Repository

Jacobs, Sam Ade; Manavi, Kasra; Burgos, Juan; Denny, Jory; Thomas, Shawna; Amato, Nancy M.

2012-01-01

This paper describes a scalable method for parallelizing sampling-based motion planning algorithms. It subdivides configuration space (C-space) into (possibly overlapping) regions and independently, in parallel, uses standard (sequential) sampling-based planners to construct roadmaps in each region. Next, in parallel, regional roadmaps in adjacent regions are connected to form a global roadmap. By subdividing the space and restricting the locality of connection attempts, we reduce the work and inter-processor communication associated with nearest neighbor calculation, a critical bottleneck for scalability in existing parallel motion planning methods. We show that our method is general enough to handle a variety of planning schemes, including the widely used Probabilistic Roadmap (PRM) and Rapidly-exploring Random Trees (RRT) algorithms. We compare our approach to two other existing parallel algorithms and demonstrate that our approach achieves better and more scalable performance. Our approach achieves almost linear scalability on a 2400 core LINUX cluster and on a 153,216 core Cray XE6 petascale machine. © 2012 IEEE.

A scalable method for parallelizing sampling-based motion planning algorithms

KAUST Repository

Jacobs, Sam Ade

2012-05-01

This paper describes a scalable method for parallelizing sampling-based motion planning algorithms. It subdivides configuration space (C-space) into (possibly overlapping) regions and independently, in parallel, uses standard (sequential) sampling-based planners to construct roadmaps in each region. Next, in parallel, regional roadmaps in adjacent regions are connected to form a global roadmap. By subdividing the space and restricting the locality of connection attempts, we reduce the work and inter-processor communication associated with nearest neighbor calculation, a critical bottleneck for scalability in existing parallel motion planning methods. We show that our method is general enough to handle a variety of planning schemes, including the widely used Probabilistic Roadmap (PRM) and Rapidly-exploring Random Trees (RRT) algorithms. We compare our approach to two other existing parallel algorithms and demonstrate that our approach achieves better and more scalable performance. Our approach achieves almost linear scalability on a 2400 core LINUX cluster and on a 153,216 core Cray XE6 petascale machine. © 2012 IEEE.

Parallelization of the model-based iterative reconstruction algorithm DIRA

International Nuclear Information System (INIS)

Oertenberg, A.; Sandborg, M.; Alm Carlsson, G.; Malusek, A.; Magnusson, M.

2016-01-01

New paradigms for parallel programming have been devised to simplify software development on multi-core processors and many-core graphical processing units (GPU). Despite their obvious benefits, the parallelization of existing computer programs is not an easy task. In this work, the use of the Open Multiprocessing (OpenMP) and Open Computing Language (OpenCL) frameworks is considered for the parallelization of the model-based iterative reconstruction algorithm DIRA with the aim to significantly shorten the code's execution time. Selected routines were parallelized using OpenMP and OpenCL libraries; some routines were converted from MATLAB to C and optimised. Parallelization of the code with the OpenMP was easy and resulted in an overall speedup of 15 on a 16-core computer. Parallelization with OpenCL was more difficult owing to differences between the central processing unit and GPU architectures. The resulting speedup was substantially lower than the theoretical peak performance of the GPU; the cause was explained. (authors)

Towards Interactive Visual Exploration of Parallel Programs using a Domain-Specific Language

KAUST Repository

Klein, Tobias; Bruckner, Stefan; Grö ller, M. Eduard; Hadwiger, Markus; Rautek, Peter

2016-01-01

The use of GPUs and the massively parallel computing paradigm have become wide-spread. We describe a framework for the interactive visualization and visual analysis of the run-time behavior of massively parallel programs, especially OpenCL kernels. This facilitates understanding a program's function and structure, finding the causes of possible slowdowns, locating program bugs, and interactively exploring and visually comparing different code variants in order to improve performance and correctness. Our approach enables very specific, user-centered analysis, both in terms of the recording of the run-time behavior and the visualization itself. Instead of having to manually write instrumented code to record data, simple code annotations tell the source-to-source compiler which code instrumentation to generate automatically. The visualization part of our framework then enables the interactive analysis of kernel run-time behavior in a way that can be very specific to a particular problem or optimization goal, such as analyzing the causes of memory bank conflicts or understanding an entire parallel algorithm.

Towards Interactive Visual Exploration of Parallel Programs using a Domain-Specific Language

KAUST Repository

Klein, Tobias

2016-04-19

The use of GPUs and the massively parallel computing paradigm have become wide-spread. We describe a framework for the interactive visualization and visual analysis of the run-time behavior of massively parallel programs, especially OpenCL kernels. This facilitates understanding a program\\'s function and structure, finding the causes of possible slowdowns, locating program bugs, and interactively exploring and visually comparing different code variants in order to improve performance and correctness. Our approach enables very specific, user-centered analysis, both in terms of the recording of the run-time behavior and the visualization itself. Instead of having to manually write instrumented code to record data, simple code annotations tell the source-to-source compiler which code instrumentation to generate automatically. The visualization part of our framework then enables the interactive analysis of kernel run-time behavior in a way that can be very specific to a particular problem or optimization goal, such as analyzing the causes of memory bank conflicts or understanding an entire parallel algorithm.

Combining flow cytometry and 16S rRNA gene pyrosequencing: A promising approach for drinking water monitoring and characterization

KAUST Repository

Prest, Emmanuelle I E C

2014-10-01

The combination of flow cytometry (FCM) and 16S rRNA gene pyrosequencing data was investigated for the purpose of monitoring and characterizing microbial changes in drinking water distribution systems. High frequency sampling (5min intervals for 1h) was performed at the outlet of a treatment plant and at one location in the full-scale distribution network. In total, 52 bulk water samples were analysed with FCM, pyrosequencing and conventional methods (adenosine-triphosphate, ATP; heterotrophic plate count, HPC). FCM and pyrosequencing results individually showed that changes in the microbial community occurred in the water distribution system, which was not detected with conventional monitoring. FCM data showed an increase in the total bacterial cell concentrations (from 345±15×103 to 425±35×103cellsmL-1) and in the percentage of intact bacterial cells (from 39±3.5% to 53±4.4%) during water distribution. This shift was also observed in the FCM fluorescence fingerprints, which are characteristic of each water sample. A similar shift was detected in the microbial community composition as characterized with pyrosequencing, showing that FCM and genetic fingerprints are congruent. FCM and pyrosequencing data were subsequently combined for the calculation of cell concentration changes for each bacterial phylum. The results revealed an increase in cell concentrations of specific bacterial phyla (e.g., Proteobacteria), along with a decrease in other phyla (e.g., Actinobacteria), which could not be concluded from the two methods individually. The combination of FCM and pyrosequencing methods is a promising approach for future drinking water quality monitoring and for advanced studies on drinking water distribution pipeline ecology. © 2014 Elsevier Ltd.

Pyrosequencing Analysis of Cryogenically Ground Samples from Primary and Secondary/Persistent Endodontic Infections.

Science.gov (United States)

Keskin, Cangül; Demiryürek, Ebru Özsezer; Onuk, Ertan Emek

2017-08-01

This study aimed to characterize the microbial communities of primary and secondary/persistent endodontic infections using high-throughput pyrosequencing from the pulverized samples. The roots of 20 extracted human teeth with primary endodontic infection and 20 teeth with secondary/persistent endodontic infection were collected. The outer surfaces of the roots were disinfected, and whole roots were cryopulverized. 16S amplicon pyrosequencing data from the DNA extracted from the pulverized root powders were obtained, and microorganism abundance and diversity were calculated. Data were analyzed using statistical and bioinformatic methods. Pyrosequencing analysis resulted a total of 2,606,128 sequences from 40 samples. A total of 15 phyla, 160 genera, and 368 species were detected. No significant difference between primary and secondary/persistent endodontic infections was found regarding the diversity and richness of operational taxonomic units at the phyla, genera, and species levels (P > .005). The present study revealed that the microbial diversity of secondary/persistent endodontic infections did not differ than those of primary endodontic infections. A new archaeal species, Candidatus Nitrosoarchaeum limnia, was detected in root canals of 1 patient with primary endodontic infection for the first time. Copyright © 2017 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Multiplex pyrosequencing assay using AdvISER-MH-PYRO algorithm: a case for rapid and cost-effective genotyping analysis of prostate cancer risk-associated SNPs.

Science.gov (United States)

Ambroise, Jérôme; Butoescu, Valentina; Robert, Annie; Tombal, Bertrand; Gala, Jean-Luc

2015-06-25

Single Nucleotide Polymorphisms (SNPs) identified in Genome Wide Association Studies (GWAS) have generally moderate association with related complex diseases. Accordingly, Multilocus Genetic Risk Scores (MGRSs) have been computed in previous studies in order to assess the cumulative association of multiple SNPs. When several SNPs have to be genotyped for each patient, using successive uniplex pyrosequencing reactions increases analytical reagent expenses and Turnaround Time (TAT). While a set of several pyrosequencing primers could theoretically be used to analyze multiplex amplicons, this would generate overlapping primer-specific pyro-signals that are visually uninterpretable. In the current study, two multiplex assays were developed consisting of a quadruplex (n=4) and a quintuplex (n=5) polymerase chain reaction (PCR) each followed by multiplex pyrosequencing analysis. The aim was to reliably but rapidly genotype a set of prostate cancer-related SNPs (n=9). The nucleotide dispensation order was selected using SENATOR software. Multiplex pyro-signals were analyzed using the new AdvISER-MH-PYRO software based on a sparse representation of the signal. Using uniplex assays as gold standard, the concordance between multiplex and uniplex assays was assessed on DNA extracted from patient blood samples (n = 10). All genotypes (n=90) generated with the quadruplex and the quintuplex pyroquencing assays were perfectly (100 %) concordant with uniplex pyrosequencing. Using multiplex genotyping approach for analyzing a set of 90 patients allowed reducing TAT by approximately 75 % (i.e., from 2025 to 470 min) while reducing reagent consumption and cost by approximately 70 % (i.e., from ~229 US$ /patient to ~64 US$ /patient). This combination of quadruplex and quintuplex pyrosequencing and PCR assays enabled to reduce the amount of DNA required for multi-SNP analysis, and to lower the global TAT and costs of SNP genotyping while providing results as reliable as uniplex

Methodes spectrales paralleles et applications aux simulations de couches de melange compressibles

OpenAIRE

Male , Jean-Michel; Fezoui , Loula ,

1993-01-01

La resolution des equations de Navier-Stokes en methodes spectrales pour des ecoulements compressibles peut etre assez gourmande en temps de calcul. On etudie donc ici la parallelisation d'un tel algorithme et son implantation sur une machine massivement parallele, la connection-machine CM-2. La methode spectrale s'adapte bien aux exigences du parallelisme massif, mais l'un des outils de base de cette methode, la transformee de Fourier rapide (lorsqu'elle doit etre appliquee sur les deux dime...

Massively parallel signature sequencing and bioinformatics analysis identifies up-regulation of TGFBI and SOX4 in human glioblastoma.

Directory of Open Access Journals (Sweden)

Biaoyang Lin

Full Text Available BACKGROUND: A comprehensive network-based understanding of molecular pathways abnormally altered in glioblastoma multiforme (GBM is essential for developing effective therapeutic approaches for this deadly disease. METHODOLOGY/PRINCIPAL FINDINGS: Applying a next generation sequencing technology, massively parallel signature sequencing (MPSS, we identified a total of 4535 genes that are differentially expressed between normal brain and GBM tissue. The expression changes of three up-regulated genes, CHI3L1, CHI3L2, and FOXM1, and two down-regulated genes, neurogranin and L1CAM, were confirmed by quantitative PCR. Pathway analysis revealed that TGF- beta pathway related genes were significantly up-regulated in GBM tumor samples. An integrative pathway analysis of the TGF beta signaling network identified two alternative TGF-beta signaling pathways mediated by SOX4 (sex determining region Y-box 4 and TGFBI (Transforming growth factor beta induced. Quantitative RT-PCR and immunohistochemistry staining demonstrated that SOX4 and TGFBI expression is elevated in GBM tissues compared with normal brain tissues at both the RNA and protein levels. In vitro functional studies confirmed that TGFBI and SOX4 expression is increased by TGF-beta stimulation and decreased by a specific inhibitor of TGF-beta receptor 1 kinase. CONCLUSIONS/SIGNIFICANCE: Our MPSS database for GBM and normal brain tissues provides a useful resource for the scientific community. The identification of non-SMAD mediated TGF-beta signaling pathways acting through SOX4 and TGFBI (GENE ID:7045 in GBM indicates that these alternative pathways should be considered, in addition to the canonical SMAD mediated pathway, in the development of new therapeutic strategies targeting TGF-beta signaling in GBM. Finally, the construction of an extended TGF-beta signaling network with overlaid gene expression changes between GBM and normal brain extends our understanding of the biology of GBM.

Neptune: An astrophysical smooth particle hydrodynamics code for massively parallel computer architectures

Science.gov (United States)

Sandalski, Stou

Smooth particle hydrodynamics is an efficient method for modeling the dynamics of fluids. It is commonly used to simulate astrophysical processes such as binary mergers. We present a newly developed GPU accelerated smooth particle hydrodynamics code for astrophysical simulations. The code is named neptune after the Roman god of water. It is written in OpenMP parallelized C++ and OpenCL and includes octree based hydrodynamic and gravitational acceleration. The design relies on object-oriented methodologies in order to provide a flexible and modular framework that can be easily extended and modified by the user. Several pre-built scenarios for simulating collisions of polytropes and black-hole accretion are provided. The code is released under the MIT Open Source license and publicly available at http://code.google.com/p/neptune-sph/.

A Parallel Encryption Algorithm Based on Piecewise Linear Chaotic Map

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Xizhong Wang

2013-01-01

Full Text Available We introduce a parallel chaos-based encryption algorithm for taking advantage of multicore processors. The chaotic cryptosystem is generated by the piecewise linear chaotic map (PWLCM. The parallel algorithm is designed with a master/slave communication model with the Message Passing Interface (MPI. The algorithm is suitable not only for multicore processors but also for the single-processor architecture. The experimental results show that the chaos-based cryptosystem possesses good statistical properties. The parallel algorithm provides much better performance than the serial ones and would be useful to apply in encryption/decryption file with large size or multimedia.

Rapid molecular identification of human taeniid cestodes by pyrosequencing approach.

Directory of Open Access Journals (Sweden)

Tongjit Thanchomnang

Full Text Available Taenia saginata, T. solium, and T. asiatica are causative agents of taeniasis in humans. The difficulty of morphological identification of human taeniids can lead to misdiagnosis or confusion. To overcome this problem, several molecular methods have been developed, but use of these tends to be time-consuming. Here, a rapid and high-throughput pyrosequencing approach was developed for the identification of three human taeniids originating from various countries. Primers targeting the mitochondrial cytochrome c oxidase subunit 1 (cox1 gene of the three Taenia species were designed. Variations in a 26-nucleotide target region were used for identification. The reproducibility and accuracy of the pyrosequencing technology was confirmed by Sanger sequencing. This technique will be a valuable tool to distinguish between sympatric human taeniids that occur in Thailand, Asia and Pacific countries. This method could potentially be used for the molecular identification of the taeniid species that might be associated with suspicious cysts and lesions, or cyst residues in humans or livestock at the slaughterhouse.

Optimization approaches to mpi and area merging-based parallel buffer algorithm

Directory of Open Access Journals (Sweden)

Junfu Fan

Full Text Available On buffer zone construction, the rasterization-based dilation method inevitably introduces errors, and the double-sided parallel line method involves a series of complex operations. In this paper, we proposed a parallel buffer algorithm based on area merging and MPI (Message Passing Interface to improve the performances of buffer analyses on processing large datasets. Experimental results reveal that there are three major performance bottlenecks which significantly impact the serial and parallel buffer construction efficiencies, including the area merging strategy, the task load balance method and the MPI inter-process results merging strategy. Corresponding optimization approaches involving tree-like area merging strategy, the vertex number oriented parallel task partition method and the inter-process results merging strategy were suggested to overcome these bottlenecks. Experiments were carried out to examine the performance efficiency of the optimized parallel algorithm. The estimation results suggested that the optimization approaches could provide high performance and processing ability for buffer construction in a cluster parallel environment. Our method could provide insights into the parallelization of spatial analysis algorithm.

A Generic Mesh Data Structure with Parallel Applications

Science.gov (United States)

Cochran, William Kenneth, Jr.

2009-01-01

High performance, massively-parallel multi-physics simulations are built on efficient mesh data structures. Most data structures are designed from the bottom up, focusing on the implementation of linear algebra routines. In this thesis, we explore a top-down approach to design, evaluating the various needs of many aspects of simulation, not just…

Parallel finite elements with domain decomposition and its pre-processing

International Nuclear Information System (INIS)

Yoshida, A.; Yagawa, G.; Hamada, S.

1993-01-01

This paper describes a parallel finite element analysis using a domain decomposition method, and the pre-processing for the parallel calculation. Computer simulations are about to replace experiments in various fields, and the scale of model to be simulated tends to be extremely large. On the other hand, computational environment has drastically changed in these years. Especially, parallel processing on massively parallel computers or computer networks is considered to be promising techniques. In order to achieve high efficiency on such parallel computation environment, large granularity of tasks, a well-balanced workload distribution are key issues. It is also important to reduce the cost of pre-processing in such parallel FEM. From the point of view, the authors developed the domain decomposition FEM with the automatic and dynamic task-allocation mechanism and the automatic mesh generation/domain subdivision system for it. (author)

Solution of the within-group multidimensional discrete ordinates transport equations on massively parallel architectures

Science.gov (United States)

Zerr, Robert Joseph

2011-12-01

The integral transport matrix method (ITMM) has been used as the kernel of new parallel solution methods for the discrete ordinates approximation of the within-group neutron transport equation. The ITMM abandons the repetitive mesh sweeps of the traditional source iterations (SI) scheme in favor of constructing stored operators that account for the direct coupling factors among all the cells and between the cells and boundary surfaces. The main goals of this work were to develop the algorithms that construct these operators and employ them in the solution process, determine the most suitable way to parallelize the entire procedure, and evaluate the behavior and performance of the developed methods for increasing number of processes. This project compares the effectiveness of the ITMM with the SI scheme parallelized with the Koch-Baker-Alcouffe (KBA) method. The primary parallel solution method involves a decomposition of the domain into smaller spatial sub-domains, each with their own transport matrices, and coupled together via interface boundary angular fluxes. Each sub-domain has its own set of ITMM operators and represents an independent transport problem. Multiple iterative parallel solution methods have investigated, including parallel block Jacobi (PBJ), parallel red/black Gauss-Seidel (PGS), and parallel GMRES (PGMRES). The fastest observed parallel solution method, PGS, was used in a weak scaling comparison with the PARTISN code. Compared to the state-of-the-art SI-KBA with diffusion synthetic acceleration (DSA), this new method without acceleration/preconditioning is not competitive for any problem parameters considered. The best comparisons occur for problems that are difficult for SI DSA, namely highly scattering and optically thick. SI DSA execution time curves are generally steeper than the PGS ones. However, until further testing is performed it cannot be concluded that SI DSA does not outperform the ITMM with PGS even on several thousand or tens of

GROMACS 4.5: A high-throughput and highly parallel open source molecular simulation toolkit

Energy Technology Data Exchange (ETDEWEB)

Pronk, Sander [Science for Life Lab., Stockholm (Sweden); KTH Royal Institute of Technology, Stockholm (Sweden); Pall, Szilard [Science for Life Lab., Stockholm (Sweden); KTH Royal Institute of Technology, Stockholm (Sweden); Schulz, Roland [Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Larsson, Per [Univ. of Virginia, Charlottesville, VA (United States); Bjelkmar, Par [Science for Life Lab., Stockholm (Sweden); Stockholm Univ., Stockholm (Sweden); Apostolov, Rossen [Science for Life Lab., Stockholm (Sweden); KTH Royal Institute of Technology, Stockholm (Sweden); Shirts, Michael R. [Univ. of Virginia, Charlottesville, VA (United States); Smith, Jeremy C. [Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Kasson, Peter M. [Univ. of Virginia, Charlottesville, VA (United States); van der Spoel, David [Science for Life Lab., Stockholm (Sweden); Uppsala Univ., Uppsala (Sweden); Hess, Berk [Science for Life Lab., Stockholm (Sweden); KTH Royal Institute of Technology, Stockholm (Sweden); Lindahl, Erik [Science for Life Lab., Stockholm (Sweden); KTH Royal Institute of Technology, Stockholm (Sweden); Stockholm Univ., Stockholm (Sweden)

2013-02-13

In this study, molecular simulation has historically been a low-throughput technique, but faster computers and increasing amounts of genomic and structural data are changing this by enabling large-scale automated simulation of, for instance, many conformers or mutants of biomolecules with or without a range of ligands. At the same time, advances in performance and scaling now make it possible to model complex biomolecular interaction and function in a manner directly testable by experiment. These applications share a need for fast and efficient software that can be deployed on massive scale in clusters, web servers, distributed computing or cloud resources. As a result, we present a range of new simulation algorithms and features developed during the past 4 years, leading up to the GROMACS 4.5 software package. The software now automatically handles wide classes of biomolecules, such as proteins, nucleic acids and lipids, and comes with all commonly used force fields for these molecules built-in. GROMACS supports several implicit solvent models, as well as new free-energy algorithms, and the software now uses multithreading for efficient parallelization even on low-end systems, including windows-based workstations. Together with hand-tuned assembly kernels and state-of-the-art parallelization, this provides extremely high performance and cost efficiency for high-throughput as well as massively parallel simulations.

An efficient parallel algorithm for matrix-vector multiplication

Energy Technology Data Exchange (ETDEWEB)

Hendrickson, B.; Leland, R.; Plimpton, S.

1993-03-01

The multiplication of a vector by a matrix is the kernel computation of many algorithms in scientific computation. A fast parallel algorithm for this calculation is therefore necessary if one is to make full use of the new generation of parallel supercomputers. This paper presents a high performance, parallel matrix-vector multiplication algorithm that is particularly well suited to hypercube multiprocessors. For an n x n matrix on p processors, the communication cost of this algorithm is O(n/[radical]p + log(p)), independent of the matrix sparsity pattern. The performance of the algorithm is demonstrated by employing it as the kernel in the well-known NAS conjugate gradient benchmark, where a run time of 6.09 seconds was observed. This is the best published performance on this benchmark achieved to date using a massively parallel supercomputer.

A new class of massively parallel direction splitting for the incompressible Navier–Stokes equations

KAUST Repository

Guermond, J.L.

2011-06-01

We introduce in this paper a new direction splitting algorithm for solving the incompressible Navier-Stokes equations. The main originality of the method consists of using the operator (I-∂xx)(I-∂yy)(I-∂zz) for approximating the pressure correction instead of the Poisson operator as done in all the contemporary projection methods. The complexity of the proposed algorithm is significantly lower than that of projection methods, and it is shown the have the same stability properties as the Poisson-based pressure-correction techniques, either in standard or rotational form. The first-order (in time) version of the method is proved to have the same convergence properties as the classical first-order projection techniques. Numerical tests reveal that the second-order version of the method has the same convergence rate as its second-order projection counterpart as well. The method is suitable for parallel implementation and preliminary tests show excellent parallel performance on a distributed memory cluster of up to 1024 processors. The method has been validated on the three-dimensional lid-driven cavity flow using grids composed of up to 2×109 points. © 2011 Elsevier B.V.

Endpoint-based parallel data processing with non-blocking collective instructions in a parallel active messaging interface of a parallel computer

Science.gov (United States)

Archer, Charles J; Blocksome, Michael A; Cernohous, Bob R; Ratterman, Joseph D; Smith, Brian E

2014-11-11

Endpoint-based parallel data processing with non-blocking collective instructions in a PAMI of a parallel computer is disclosed. The PAMI is composed of data communications endpoints, each including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task. The compute nodes are coupled for data communications through the PAMI. The parallel application establishes a data communications geometry specifying a set of endpoints that are used in collective operations of the PAMI by associating with the geometry a list of collective algorithms valid for use with the endpoints of the geometry; registering in each endpoint in the geometry a dispatch callback function for a collective operation; and executing without blocking, through a single one of the endpoints in the geometry, an instruction for the collective operation.

Comparison Study of MS-HRM and Pyrosequencing Techniques for Quantification of APC and CDKN2A Gene Methylation

Science.gov (United States)

Migheli, Francesca; Stoccoro, Andrea; Coppedè, Fabio; Wan Omar, Wan Adnan; Failli, Alessandra; Consolini, Rita; Seccia, Massimo; Spisni, Roberto; Miccoli, Paolo; Mathers, John C.; Migliore, Lucia

2013-01-01

There is increasing interest in the development of cost-effective techniques for the quantification of DNA methylation biomarkers. We analyzed 90 samples of surgically resected colorectal cancer tissues for APC and CDKN2A promoter methylation using methylation sensitive-high resolution melting (MS-HRM) and pyrosequencing. MS-HRM is a less expensive technique compared with pyrosequencing but is usually more limited because it gives a range of methylation estimates rather than a single value. Here, we developed a method for deriving single estimates, rather than a range, of methylation using MS-HRM and compared the values obtained in this way with those obtained using the gold standard quantitative method of pyrosequencing. We derived an interpolation curve using standards of known methylated/unmethylated ratio (0%, 12.5%, 25%, 50%, 75%, and 100% of methylation) to obtain the best estimate of the extent of methylation for each of our samples. We observed similar profiles of methylation and a high correlation coefficient between the two techniques. Overall, our new approach allows MS-HRM to be used as a quantitative assay which provides results which are comparable with those obtained by pyrosequencing. PMID:23326336

Combining flow cytometry and 16S rRNA gene pyrosequencing: a promising approach for drinking water monitoring and characterization.

Science.gov (United States)

Prest, E I; El-Chakhtoura, J; Hammes, F; Saikaly, P E; van Loosdrecht, M C M; Vrouwenvelder, J S

2014-10-15

The combination of flow cytometry (FCM) and 16S rRNA gene pyrosequencing data was investigated for the purpose of monitoring and characterizing microbial changes in drinking water distribution systems. High frequency sampling (5 min intervals for 1 h) was performed at the outlet of a treatment plant and at one location in the full-scale distribution network. In total, 52 bulk water samples were analysed with FCM, pyrosequencing and conventional methods (adenosine-triphosphate, ATP; heterotrophic plate count, HPC). FCM and pyrosequencing results individually showed that changes in the microbial community occurred in the water distribution system, which was not detected with conventional monitoring. FCM data showed an increase in the total bacterial cell concentrations (from 345 ± 15 × 10(3) to 425 ± 35 × 10(3) cells mL(-1)) and in the percentage of intact bacterial cells (from 39 ± 3.5% to 53 ± 4.4%) during water distribution. This shift was also observed in the FCM fluorescence fingerprints, which are characteristic of each water sample. A similar shift was detected in the microbial community composition as characterized with pyrosequencing, showing that FCM and genetic fingerprints are congruent. FCM and pyrosequencing data were subsequently combined for the calculation of cell concentration changes for each bacterial phylum. The results revealed an increase in cell concentrations of specific bacterial phyla (e.g., Proteobacteria), along with a decrease in other phyla (e.g., Actinobacteria), which could not be concluded from the two methods individually. The combination of FCM and pyrosequencing methods is a promising approach for future drinking water quality monitoring and for advanced studies on drinking water distribution pipeline ecology. Copyright © 2014 Elsevier Ltd. All rights reserved.

Using expected sequence features to improve basecalling accuracy of amplicon pyrosequencing data

DEFF Research Database (Denmark)

Rask, Thomas Salhøj; Petersen, Bent; Chen, Donald S.

2016-01-01

. The new basecalling method described here, named Multipass, implements a probabilistic framework for working with the raw flowgrams obtained by pyrosequencing. For each sequence variant Multipass calculates the likelihood and nucleotide sequence of several most likely sequences given the flowgram data....... This probabilistic approach enables integration of basecalling into a larger model where other parameters can be incorporated, such as the likelihood for observing a full-length open reading frame at the targeted region. We apply the method to 454 amplicon pyrosequencing data obtained from a malaria virulence gene...... family, where Multipass generates 20 % more error-free sequences than current state of the art methods, and provides sequence characteristics that allow generation of a set of high confidence error-free sequences. This novel method can be used to increase accuracy of existing and future amplicon...

Parallelized event chain algorithm for dense hard sphere and polymer systems

International Nuclear Information System (INIS)

Kampmann, Tobias A.; Boltz, Horst-Holger; Kierfeld, Jan

2015-01-01

We combine parallelization and cluster Monte Carlo for hard sphere systems and present a parallelized event chain algorithm for the hard disk system in two dimensions. For parallelization we use a spatial partitioning approach into simulation cells. We find that it is crucial for correctness to ensure detailed balance on the level of Monte Carlo sweeps by drawing the starting sphere of event chains within each simulation cell with replacement. We analyze the performance gains for the parallelized event chain and find a criterion for an optimal degree of parallelization. Because of the cluster nature of event chain moves massive parallelization will not be optimal. Finally, we discuss first applications of the event chain algorithm to dense polymer systems, i.e., bundle-forming solutions of attractive semiflexible polymers

Mesh-based parallel code coupling interface

Energy Technology Data Exchange (ETDEWEB)

Wolf, K.; Steckel, B. (eds.) [GMD - Forschungszentrum Informationstechnik GmbH, St. Augustin (DE). Inst. fuer Algorithmen und Wissenschaftliches Rechnen (SCAI)

2001-04-01

MpCCI (mesh-based parallel code coupling interface) is an interface for multidisciplinary simulations. It provides industrial end-users as well as commercial code-owners with the facility to combine different simulation tools in one environment. Thereby new solutions for multidisciplinary problems will be created. This opens new application dimensions for existent simulation tools. This Book of Abstracts gives a short overview about ongoing activities in industry and research - all presented at the 2{sup nd} MpCCI User Forum in February 2001 at GMD Sankt Augustin. (orig.) [German] MpCCI (mesh-based parallel code coupling interface) definiert eine Schnittstelle fuer multidisziplinaere Simulationsanwendungen. Sowohl industriellen Anwender als auch kommerziellen Softwarehersteller wird mit MpCCI die Moeglichkeit gegeben, Simulationswerkzeuge unterschiedlicher Disziplinen miteinander zu koppeln. Dadurch entstehen neue Loesungen fuer multidisziplinaere Problemstellungen und fuer etablierte Simulationswerkzeuge ergeben sich neue Anwendungsfelder. Dieses Book of Abstracts bietet einen Ueberblick ueber zur Zeit laufende Arbeiten in der Industrie und in der Forschung, praesentiert auf dem 2{sup nd} MpCCI User Forum im Februar 2001 an der GMD Sankt Augustin. (orig.)

A sweetpotato gene index established by de novo assembly of pyrosequencing and Sanger sequences and mining for gene-based microsatellite markers

Directory of Open Access Journals (Sweden)

Solis Julio

2010-10-01

Full Text Available Abstract Background Sweetpotato (Ipomoea batatas (L. Lam., a hexaploid outcrossing crop, is an important staple and food security crop in developing countries in Africa and Asia. The availability of genomic resources for sweetpotato is in striking contrast to its importance for human nutrition. Previously existing sequence data were restricted to around 22,000 expressed sequence tag (EST sequences and ~ 1,500 GenBank sequences. We have used 454 pyrosequencing to augment the available gene sequence information to enhance functional genomics and marker design for this plant species. Results Two quarter 454 pyrosequencing runs used two normalized cDNA collections from stems and leaves from drought-stressed sweetpotato clone Tanzania and yielded 524,209 reads, which were assembled together with 22,094 publically available expressed sequence tags into 31,685 sets of overlapping DNA segments and 34,733 unassembled sequences. Blastx comparisons with the UniRef100 database allowed annotation of 23,957 contigs and 15,342 singletons resulting in 24,657 putatively unique genes. Further, 27,119 sequences had no match to protein sequences of UniRef100database. On the basis of this gene index, we have identified 1,661 gene-based microsatellite sequences, of which 223 were selected for testing and 195 were successfully amplified in a test panel of 6 hexaploid (I. batatas and 2 diploid (I. trifida accessions. Conclusions The sweetpotato gene index is a useful source for functionally annotated sweetpotato gene sequences that contains three times more gene sequence information for sweetpotato than previous EST assemblies. A searchable version of the gene index, including a blastn function, is available at http://www.cipotato.org/sweetpotato_gene_index.

A sensitive issue: Pyrosequencing as a valuable forensic SNP typing platform

DEFF Research Database (Denmark)

Harrison, C.; Musgrave-Brown, E.; Bender, K.

2006-01-01

Analysing minute amounts of DNA is a routine challenge in forensics in part due to the poor sensitivity of an instrument and its inability to detect results from forensic samples. In this study, the sensitivity of the Pyrosequencing method is investigated using varying concentrations of DNA and f...

Characterization of bacterial populations in Danish raw milk cheeses made with different starter cultures by denaturating gradient gel electrophoresis and pyrosequencing

DEFF Research Database (Denmark)

Masoud, Wafa Mahmoud Hasan; Takamiya, Monica K Wik; Vogensen, Finn Kvist

2011-01-01

ripening. Other bacteria like Corynebacterium, Halomonas, Pediococcus, Micrococcus and Staphylococcus, which were encountered in some cheese samples at low percentages compared with the total bacterial populations, were only detected by pyrosequencing. 16S rRNA gene pyrosequencing is an efficient method...

Quaternary Morphodynamics of Fluvial Dispersal Systems Revealed: The Fly River, PNG, and the Sunda Shelf, SE Asia, simulated with the Massively Parallel GPU-based Model 'GULLEM'

Science.gov (United States)

Aalto, R. E.; Lauer, J. W.; Darby, S. E.; Best, J.; Dietrich, W. E.

2015-12-01

During glacial-marine transgressions vast volumes of sediment are deposited due to the infilling of lowland fluvial systems and shallow shelves, material that is removed during ensuing regressions. Modelling these processes would illuminate system morphodynamics, fluxes, and 'complexity' in response to base level change, yet such problems are computationally formidable. Environmental systems are characterized by strong interconnectivity, yet traditional supercomputers have slow inter-node communication -- whereas rapidly advancing Graphics Processing Unit (GPU) technology offers vastly higher (>100x) bandwidths. GULLEM (GpU-accelerated Lowland Landscape Evolution Model) employs massively parallel code to simulate coupled fluvial-landscape evolution for complex lowland river systems over large temporal and spatial scales. GULLEM models the accommodation space carved/infilled by representing a range of geomorphic processes, including: river & tributary incision within a multi-directional flow regime, non-linear diffusion, glacial-isostatic flexure, hydraulic geometry, tectonic deformation, sediment production, transport & deposition, and full 3D tracking of all resulting stratigraphy. Model results concur with the Holocene dynamics of the Fly River, PNG -- as documented with dated cores, sonar imaging of floodbasin stratigraphy, and the observations of topographic remnants from LGM conditions. Other supporting research was conducted along the Mekong River, the largest fluvial system of the Sunda Shelf. These and other field data provide tantalizing empirical glimpses into the lowland landscapes of large rivers during glacial-interglacial transitions, observations that can be explored with this powerful numerical model. GULLEM affords estimates for the timing and flux budgets within the Fly and Sunda Systems, illustrating complex internal system responses to the external forcing of sea level and climate. Furthermore, GULLEM can be applied to most ANY fluvial system to

Parallel preconditioning techniques for sparse CG solvers

Energy Technology Data Exchange (ETDEWEB)

Basermann, A.; Reichel, B.; Schelthoff, C. [Central Institute for Applied Mathematics, Juelich (Germany)

1996-12-31

Conjugate gradient (CG) methods to solve sparse systems of linear equations play an important role in numerical methods for solving discretized partial differential equations. The large size and the condition of many technical or physical applications in this area result in the need for efficient parallelization and preconditioning techniques of the CG method. In particular for very ill-conditioned matrices, sophisticated preconditioner are necessary to obtain both acceptable convergence and accuracy of CG. Here, we investigate variants of polynomial and incomplete Cholesky preconditioners that markedly reduce the iterations of the simply diagonally scaled CG and are shown to be well suited for massively parallel machines.

Genomic Characterization of Non–Small-Cell Lung Cancer in African Americans by Targeted Massively Parallel Sequencing

Science.gov (United States)

Araujo, Luiz H.; Timmers, Cynthia; Bell, Erica Hlavin; Shilo, Konstantin; Lammers, Philip E.; Zhao, Weiqiang; Natarajan, Thanemozhi G.; Miller, Clinton J.; Zhang, Jianying; Yilmaz, Ayse S.; Liu, Tom; Coombes, Kevin; Amann, Joseph; Carbone, David P.

2015-01-01

Purpose Technologic advances have enabled the comprehensive analysis of genetic perturbations in non–small-cell lung cancer (NSCLC); however, African Americans have often been underrepresented in these studies. This ethnic group has higher lung cancer incidence and mortality rates, and some studies have suggested a lower incidence of epidermal growth factor receptor mutations. Herein, we report the most in-depth molecular profile of NSCLC in African Americans to date. Methods A custom panel was designed to cover the coding regions of 81 NSCLC-related genes and 40 ancestry-informative markers. Clinical samples were sequenced on a massively parallel sequencing instrument, and anaplastic lymphoma kinase translocation was evaluated by fluorescent in situ hybridization. Results The study cohort included 99 patients (61% males, 94% smokers) comprising 31 squamous and 68 nonsquamous cell carcinomas. We detected 227 nonsilent variants in the coding sequence, including 24 samples with nonoverlapping, classic driver alterations. The frequency of driver mutations was not significantly different from that of whites, and no association was found between genetic ancestry and the presence of somatic mutations. Copy number alteration analysis disclosed distinguishable amplifications in the 3q chromosome arm in squamous cell carcinomas and pointed toward a handful of targetable alterations. We also found frequent SMARCA4 mutations and protein loss, mostly in driver-negative tumors. Conclusion Our data suggest that African American ancestry may not be significantly different from European/white background for the presence of somatic driver mutations in NSCLC. Furthermore, we demonstrated that using a comprehensive genotyping approach could identify numerous targetable alterations, with potential impact on therapeutic decisions. PMID:25918285

A dynamic bead-based microarray for parallel DNA detection

International Nuclear Information System (INIS)

Sochol, R D; Lin, L; Casavant, B P; Dueck, M E; Lee, L P

2011-01-01

A microfluidic system has been designed and constructed by means of micromachining processes to integrate both microfluidic mixing of mobile microbeads and hydrodynamic microbead arraying capabilities on a single chip to simultaneously detect multiple bio-molecules. The prototype system has four parallel reaction chambers, which include microchannels of 18 × 50 µm 2 cross-sectional area and a microfluidic mixing section of 22 cm length. Parallel detection of multiple DNA oligonucleotide sequences was achieved via molecular beacon probes immobilized on polystyrene microbeads of 16 µm diameter. Experimental results show quantitative detection of three distinct DNA oligonucleotide sequences from the Hepatitis C viral (HCV) genome with single base-pair mismatch specificity. Our dynamic bead-based microarray offers an effective microfluidic platform to increase parallelization of reactions and improve microbead handling for various biological applications, including bio-molecule detection, medical diagnostics and drug screening

Research on Parallel Three Phase PWM Converters base on RTDS

Science.gov (United States)

Xia, Yan; Zou, Jianxiao; Li, Kai; Liu, Jingbo; Tian, Jun

2018-01-01

Converters parallel operation can increase capacity of the system, but it may lead to potential zero-sequence circulating current, so the control of circulating current was an important goal in the design of parallel inverters. In this paper, the Real Time Digital Simulator (RTDS) is used to model the converters parallel system in real time and study the circulating current restraining. The equivalent model of two parallel converters and zero-sequence circulating current(ZSCC) were established and analyzed, then a strategy using variable zero vector control was proposed to suppress the circulating current. For two parallel modular converters, hardware-in-the-loop(HIL) study based on RTDS and practical experiment were implemented, results prove that the proposed control strategy is feasible and effective.

On the Minimum Cable Tensions for the Cable-Based Parallel Robots

Directory of Open Access Journals (Sweden)

Peng Liu

2014-01-01

Full Text Available This paper investigates the minimum cable tension distributions in the workspace for cable-based parallel robots to find out more information on the stability. First, the kinematic model of a cable-based parallel robot is derived based on the wrench matrix. Then, a noniterative polynomial-based optimization algorithm with the proper optimal objective function is presented based on the convex optimization theory, in which the minimum cable tension at any pose is determined. Additionally, three performance indices are proposed to show the distributions of the minimum cable tensions in a specified region of the workspace. An important thing is that the three performance indices can be used to evaluate the stability of the cable-based parallel robots. Furthermore, a new workspace, the Specified Minimum Cable Tension Workspace (SMCTW, is introduced, within which all the minimum tensions exceed a specified value, therefore meeting the specified stability requirement. Finally, a camera robot parallel driven by four cables for aerial panoramic photographing is selected to illustrate the distributions of the minimum cable tensions in the workspace and the relationship between the three performance indices and the stability.

A Novel Algorithm for Solving the Multidimensional Neutron Transport Equation on Massively Parallel Architectures

Energy Technology Data Exchange (ETDEWEB)

Azmy, Yousry

2014-06-10

We employ the Integral Transport Matrix Method (ITMM) as the kernel of new parallel solution methods for the discrete ordinates approximation of the within-group neutron transport equation. The ITMM abandons the repetitive mesh sweeps of the traditional source iterations (SI) scheme in favor of constructing stored operators that account for the direct coupling factors among all the cells' fluxes and between the cells' and boundary surfaces' fluxes. The main goals of this work are to develop the algorithms that construct these operators and employ them in the solution process, determine the most suitable way to parallelize the entire procedure, and evaluate the behavior and parallel performance of the developed methods with increasing number of processes, P. The fastest observed parallel solution method, Parallel Gauss-Seidel (PGS), was used in a weak scaling comparison with the PARTISN transport code, which uses the source iteration (SI) scheme parallelized with the Koch-baker-Alcouffe (KBA) method. Compared to the state-of-the-art SI-KBA with diffusion synthetic acceleration (DSA), this new method- even without acceleration/preconditioning-is completitive for optically thick problems as P is increased to the tens of thousands range. For the most optically thick cells tested, PGS reduced execution time by an approximate factor of three for problems with more than 130 million computational cells on P = 32,768. Moreover, the SI-DSA execution times's trend rises generally more steeply with increasing P than the PGS trend. Furthermore, the PGS method outperforms SI for the periodic heterogeneous layers (PHL) configuration problems. The PGS method outperforms SI and SI-DSA on as few as P = 16 for PHL problems and reduces execution time by a factor of ten or more for all problems considered with more than 2 million computational cells on P = 4.096.

Flexbar 3.0 - SIMD and multicore parallelization.

Science.gov (United States)

Roehr, Johannes T; Dieterich, Christoph; Reinert, Knut

2017-09-15

High-throughput sequencing machines can process many samples in a single run. For Illumina systems, sequencing reads are barcoded with an additional DNA tag that is contained in the respective sequencing adapters. The recognition of barcode and adapter sequences is hence commonly needed for the analysis of next-generation sequencing data. Flexbar performs demultiplexing based on barcodes and adapter trimming for such data. The massive amounts of data generated on modern sequencing machines demand that this preprocessing is done as efficiently as possible. We present Flexbar 3.0, the successor of the popular program Flexbar. It employs now twofold parallelism: multi-threading and additionally SIMD vectorization. Both types of parallelism are used to speed-up the computation of pair-wise sequence alignments, which are used for the detection of barcodes and adapters. Furthermore, new features were included to cover a wide range of applications. We evaluated the performance of Flexbar based on a simulated sequencing dataset. Our program outcompetes other tools in terms of speed and is among the best tools in the presented quality benchmark. https://github.com/seqan/flexbar. johannes.roehr@fu-berlin.de or knut.reinert@fu-berlin.de. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Tiling as a Durable Abstraction for Parallelism and Data Locality

Energy Technology Data Exchange (ETDEWEB)

Unat, Didem [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Chan, Cy P. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Zhang, Weiqun [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bell, John [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Shalf, John [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2013-11-18

Tiling is a useful loop transformation for expressing parallelism and data locality. Automated tiling transformations that preserve data-locality are increasingly important due to hardware trends towards massive parallelism and the increasing costs of data movement relative to the cost of computing. We propose TiDA as a durable tiling abstraction that centralizes parameterized tiling information within array data types with minimal changes to the source code. The data layout information can be used by the compiler and runtime to automatically manage parallelism, optimize data locality, and schedule tasks intelligently. In this study, we present the design features and early interface of TiDA along with some preliminary results.

A molecular gram stain using broad range PCR and pyrosequencing technology: a potentially useful tool for diagnosing orthopaedic infections.

Science.gov (United States)

Kobayashi, Naomi; Bauer, Thomas W; Togawa, Daisuke; Lieberman, Isador H; Sakai, Hiroshige; Fujishiro, Takaaki; Tuohy, Marion J; Procop, Gary W

2005-06-01

The bacteria associated with orthopaedic infections are usually common gram-positive and gram-negative bacteria. This fundamental grouping of bacteria is a necessary first step in the selection of appropriate antibiotics. Since polymerase chain reaction (PCR) is more rapid and may be more sensitive than culture, we developed a postamplification pyrosequencing method to subcategorize bacteria based on a few nucleotide polymorphisms in the 16S rRNA gene. We validated this method using well-characterized strains of bacteria and applied it to specimens from spinal surgery cases with suspected infections. Lysates of 114 bacteria including 75 species were created following standard cultivation to obtain DNA. The DNA was amplified by a broad-range real-time PCR. The amplicons were evaluated by pyrosequencing and were classified as gram-positive, gram-negative, or acid-fast bacilli based on the first three to five nucleotides sequenced. In addition, clinical cases of suspected infection were obtained from spinal surgery. The results of the "molecular Gram stain" were compared with the results of traditional Gram stain and culture. The lysates of 107 (93.9%) of the bacteria extracts tested were appropriately categorized as gram-positive and gram-negative or as acid-fast bacilli on the basis of this assay. The sensitivity and specificity of this assay were 100% and 97.4% for gram-positive and 88.3% and 100% for gram-negative isolates. All of the five clinical samples were appropriately categorized as containing gram-positive or gram-negative bacteria with this assay. This study demonstrates that high sensitivity and specificity of a molecular gram stain may be achieved using broad-range real-time PCR and pyrosequencing.

Rumen bacterial community evaluated by 454 pyrosequencing and terminal restriction fragment length polymorphism analyses in dairy sheep fed marine algae.

Science.gov (United States)

Castro-Carrera, T; Toral, P G; Frutos, P; McEwan, N R; Hervás, G; Abecia, L; Pinloche, E; Girdwood, S E; Belenguer, A

2014-03-01

Developing novel strategies to increase the content of bioactive unsaturated fatty acids (FA) in ruminant-derived products requires a deeper understanding of rumen biohydrogenation and bacteria involved in this process. Although high-throughput pyrosequencing may allow for a great coverage of bacterial diversity, it has hardly been used to investigate the microbiology of ruminal FA metabolism. In this experiment, 454 pyrosequencing and a molecular fingerprinting technique (terminal restriction fragment length polymorphism; T-RFLP) were used concurrently to assess the effect of diet supplementation with marine algae (MA) on the rumen bacterial community of dairy sheep. Eleven lactating ewes were divided in 2 lots and offered a total mixed ration based on alfalfa hay and concentrate (40:60), supplemented with 0 (control) or 8 (MA) g of MA/kg of dry matter. After 54 d on treatments, animals were slaughtered and samples of rumen content and fluid were collected separately for microbial analysis. Pyrosequencing yielded a greater coverage of bacterial diversity than T-RFLP and allowed the identification of low abundant populations. Conversely, both molecular approaches pointed to similar conclusions and showed that relevant changes due to MA addition were observed within the major ruminal phyla, namely Bacteroidetes, Firmicutes, and Proteobacteria. Decreases in the abundance of unclassified Bacteroidales, Porphyromonadaceae, and Ruminococcaceae and increases in as-yet uncultured species of the family Succinivibrionaceae, might be related to a potential role of these groups in different pathways of rumen FA metabolism. Diet supplementation with MA, however, had no effect on the relative abundance of Butyrivibrio and Pseudobutyrivibrio genera. In addition, results from both 454 pyrosequencing and T-RFLP indicate that the effect of MA was rather consistent in rumen content or fluid samples, despite inherent differences between these fractions in their bacterial composition

An optimization of a GPU-based parallel wind field module

International Nuclear Information System (INIS)

Pinheiro, André L.S.; Shirru, Roberto

2017-01-01

Atmospheric radionuclide dispersion systems (ARDS) are important tools to predict the impact of radioactive releases from Nuclear Power Plants and guide people evacuation from affected areas. Four modules comprise ARDS: Source Term, Wind Field, Plume Dispersion and Doses Calculations. The slowest is the Wind Field Module that was previously parallelized using the CUDA C language. The statement purpose of this work is to show the speedup gain with the optimization of the already parallel code of the GPU-based Wind Field module, based in WEST model (Extrapolated from Stability and Terrain). Due to the parallelization done in the wind field module, it was observed that some CUDA processors became idle, thus contributing to a reduction in speedup. It was proposed in this work a way of allocating these idle CUDA processors in order to increase the speedup. An acceleration of about 4 times can be seen in the comparative case study between the regular CUDA code and the optimized CUDA code. These results are quite motivating and point out that even after a parallelization of code, a parallel code optimization should be taken into account. (author)

An optimization of a GPU-based parallel wind field module

Energy Technology Data Exchange (ETDEWEB)

Pinheiro, André L.S.; Shirru, Roberto [Coordenacao de Pos-Graduacao e Pesquisa de Engenharia (PEN/COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Programa de Engenharia Nuclear; Pereira, Cláudio M.N.A., E-mail: apinheiro99@gmail.com, E-mail: schirru@lmp.ufrj.br, E-mail: cmnap@ien.gov.br [Instituto de Engenharia Nuclear (IEN/CNEN-RJ), Rio de Janeiro, RJ (Brazil)

2017-07-01

Atmospheric radionuclide dispersion systems (ARDS) are important tools to predict the impact of radioactive releases from Nuclear Power Plants and guide people evacuation from affected areas. Four modules comprise ARDS: Source Term, Wind Field, Plume Dispersion and Doses Calculations. The slowest is the Wind Field Module that was previously parallelized using the CUDA C language. The statement purpose of this work is to show the speedup gain with the optimization of the already parallel code of the GPU-based Wind Field module, based in WEST model (Extrapolated from Stability and Terrain). Due to the parallelization done in the wind field module, it was observed that some CUDA processors became idle, thus contributing to a reduction in speedup. It was proposed in this work a way of allocating these idle CUDA processors in order to increase the speedup. An acceleration of about 4 times can be seen in the comparative case study between the regular CUDA code and the optimized CUDA code. These results are quite motivating and point out that even after a parallelization of code, a parallel code optimization should be taken into account. (author)

Parallel data grabbing card based on PCI bus RS422

International Nuclear Information System (INIS)

Zhang Zhenghui; Shen Ji; Wei Dongshan; Chen Ziyu

2005-01-01

This article briefly introduces the developments of the parallel data grabbing card based on RS422 and PCI bus. It could be applied for grabbing the 14 bits parallel data in high speed, coming from the devices with RS422 interface. The methods of data acquisition which bases on the PCI protocol, the functions and their usages of the chips employed, the ideas and principles of the hardware and software designing are presented. (authors)

Genome-wide massively parallel sequencing of formaldehyde fixed-paraffin embedded (FFPE tumor tissues for copy-number- and mutation-analysis.

Directory of Open Access Journals (Sweden)

Michal R Schweiger

Full Text Available BACKGROUND: Cancer re-sequencing programs rely on DNA isolated from fresh snap frozen tissues, the preparation of which is combined with additional preservation efforts. Tissue samples at pathology departments are routinely stored as formalin-fixed and paraffin-embedded (FFPE samples and their use would open up access to a variety of clinical trials. However, FFPE preparation is incompatible with many down-stream molecular biology techniques such as PCR based amplification methods and gene expression studies. METHODOLOGY/PRINCIPAL FINDINGS: Here we investigated the sample quality requirements of FFPE tissues for massively parallel short-read sequencing approaches. We evaluated key variables of pre-fixation, fixation related and post-fixation processes that occur in routine medical service (e.g. degree of autolysis, duration of fixation and of storage. We also investigated the influence of tissue storage time on sequencing quality by using material that was up to 18 years old. Finally, we analyzed normal and tumor breast tissues using the Sequencing by Synthesis technique (Illumina Genome Analyzer, Solexa to simultaneously localize genome-wide copy number alterations and to detect genomic variations such as substitutions and point-deletions and/or insertions in FFPE tissue samples. CONCLUSIONS/SIGNIFICANCE: The application of second generation sequencing techniques on small amounts of FFPE material opens up the possibility to analyze tissue samples which have been collected during routine clinical work as well as in the context of clinical trials. This is in particular important since FFPE samples are amply available from surgical tumor resections and histopathological diagnosis, and comprise tissue from precursor lesions, primary tumors, lymphogenic and/or hematogenic metastases. Large-scale studies using this tissue material will result in a better prediction of the prognosis of cancer patients and the early identification of patients which

Spatial Segregation and Aggregation of Ectomycorrhizal and Root-Endophytic Fungi in the Seedlings of Two Quercus Species

Science.gov (United States)

Yamamoto, Satoshi; Sato, Hirotoshi; Tanabe, Akifumi S.; Hidaka, Amane; Kadowaki, Kohmei; Toju, Hirokazu

2014-01-01

Diverse clades of mycorrhizal and endophytic fungi are potentially involved in competitive or facilitative interactions within host-plant roots. We investigated the potential consequences of these ecological interactions on the assembly process of root-associated fungi by examining the co-occurrence of pairs of fungi in host-plant individuals. Based on massively-parallel pyrosequencing, we analyzed the root-associated fungal community composition for each of the 249 Quercus serrata and 188 Quercus glauca seedlings sampled in a warm-temperate secondary forest in Japan. Pairs of fungi that co-occurred more or less often than expected by chance were identified based on randomization tests. The pyrosequencing analysis revealed that not only ectomycorrhizal fungi but also endophytic fungi were common in the root-associated fungal community. Intriguingly, specific pairs of these ectomycorrhizal and endophytic fungi showed spatially aggregated patterns, suggesting the existence of facilitative interactions between fungi in different functional groups. Due to the large number of fungal pairs examined, many of the observed aggregated/segregated patterns with very low P values (e.g., fungi could influence each other through interspecific competitive/facilitative interactions in root. To test the potential of host-plants' control of fungus–fungus ecological interactions in roots, we further examined whether the aggregated/segregated patterns could vary depending on the identity of host plant species. Potentially due to the physiological properties shared between the congeneric host plant species, the sign of hosts' control was not detected in the present study. The pyrosequencing-based randomization analyses shown in this study provide a platform of the high-throughput investigation of fungus–fungus interactions in plant root systems. PMID:24801150

Sampling the Denatured State of Polypeptides in Water, Urea, and Guanidine Chloride to Strict Equilibrium Conditions with the Help of Massively Parallel Computers.

Science.gov (United States)

Meloni, Roberto; Camilloni, Carlo; Tiana, Guido

2014-02-11

The denatured state of polypeptides and proteins, stabilized by chemical denaturants like urea and guanidine chloride, displays residual secondary structure when studied by nuclear-magnetic-resonance spectroscopy. However, these experimental techniques are weakly sensitive, and thus molecular-dynamics simulations can be useful to complement the experimental findings. To sample the denatured state, we made use of massively-parallel computers and of a variant of the replica exchange algorithm, in which the different branches, connected with unbiased replicas, favor the formation and disruption of local secondary structure. The algorithm is applied to the second hairpin of GB1 in water, in urea, and in guanidine chloride. We show with the help of different criteria that the simulations converge to equilibrium. It results that urea and guanidine chloride, besides inducing some polyproline-II structure, have different effect on the hairpin. Urea disrupts completely the native region and stabilizes a state which resembles a random coil, while guanidine chloride has a milder effect.

Clinical Neuropathology practice news 1-2014: Pyrosequencing meets clinical and analytical performance criteria for routine testing of MGMT promoter methylation status in glioblastoma

Science.gov (United States)

Preusser, Matthias; Berghoff, Anna S.; Manzl, Claudia; Filipits, Martin; Weinhäusel, Andreas; Pulverer, Walter; Dieckmann, Karin; Widhalm, Georg; Wöhrer, Adelheid; Knosp, Engelbert; Marosi, Christine; Hainfellner, Johannes A.

2014-01-01

Testing of the MGMT promoter methylation status in glioblastoma is relevant for clinical decision making and research applications. Two recent and independent phase III therapy trials confirmed a prognostic and predictive value of the MGMT promoter methylation status in elderly glioblastoma patients. Several methods for MGMT promoter methylation testing have been proposed, but seem to be of limited test reliability. Therefore, and also due to feasibility reasons, translation of MGMT methylation testing into routine use has been protracted so far. Pyrosequencing after prior DNA bisulfite modification has emerged as a reliable, accurate, fast and easy-to-use method for MGMT promoter methylation testing in tumor tissues (including formalin-fixed and paraffin-embedded samples). We performed an intra- and inter-laboratory ring trial which demonstrates a high analytical performance of this technique. Thus, pyrosequencing-based assessment of MGMT promoter methylation status in glioblastoma meets the criteria of high analytical test performance and can be recommended for clinical application, provided that strict quality control is performed. Our article summarizes clinical indications, practical instructions and open issues for MGMT promoter methylation testing in glioblastoma using pyrosequencing. PMID:24359605

Performances of two biotrickling filters in treating H₂S-containing waste gases and analysis of corresponding bacterial communities by pyrosequencing.

Science.gov (United States)

Li, Jianjun; Ye, Guangyun; Sun, Duanfang; Sun, Guoping; Zeng, Xiaowei; Xu, Jian; Liang, Shizhong

2012-09-01

Two identical biotrickling filters named BTFa and BTFb were run in parallel to examine their performances in removing hydrogen sulfide. BTFa was filled with ceramic granules, and BTFb was filled with volcanic rocks. The results showed that BTFb was more robust than BTFa under acidic conditions. At empty bed residence times (EBRTs) of 20 and 15 s, the removal efficiency of BTFa was close to 100%. At EBRTs of 10 and 5 s, the removal efficiency of BTFa slightly decreased. The removal efficiencies of BTFa decreased by different degrees at the end of each stage, dropping to 94%, 81%, 60%, and 71%, respectively. However, the H(2)S removal efficiency in BTFb consistently reached 99% throughout the experiment. Pyrosequencing analyses indicated that members of Thiomonas dominated in both BTFs, but the relative abundance of Acidithiobacillus was higher in BTFb than in BTFa.

GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit.

Science.gov (United States)

Pronk, Sander; Páll, Szilárd; Schulz, Roland; Larsson, Per; Bjelkmar, Pär; Apostolov, Rossen; Shirts, Michael R; Smith, Jeremy C; Kasson, Peter M; van der Spoel, David; Hess, Berk; Lindahl, Erik

2013-04-01

Molecular simulation has historically been a low-throughput technique, but faster computers and increasing amounts of genomic and structural data are changing this by enabling large-scale automated simulation of, for instance, many conformers or mutants of biomolecules with or without a range of ligands. At the same time, advances in performance and scaling now make it possible to model complex biomolecular interaction and function in a manner directly testable by experiment. These applications share a need for fast and efficient software that can be deployed on massive scale in clusters, web servers, distributed computing or cloud resources. Here, we present a range of new simulation algorithms and features developed during the past 4 years, leading up to the GROMACS 4.5 software package. The software now automatically handles wide classes of biomolecules, such as proteins, nucleic acids and lipids, and comes with all commonly used force fields for these molecules built-in. GROMACS supports several implicit solvent models, as well as new free-energy algorithms, and the software now uses multithreading for efficient parallelization even on low-end systems, including windows-based workstations. Together with hand-tuned assembly kernels and state-of-the-art parallelization, this provides extremely high performance and cost efficiency for high-throughput as well as massively parallel simulations. GROMACS is an open source and free software available from http://www.gromacs.org. Supplementary data are available at Bioinformatics online.

MEDUSA - An overset grid flow solver for network-based parallel computer systems

Science.gov (United States)

Smith, Merritt H.; Pallis, Jani M.

1993-01-01

Continuing improvement in processing speed has made it feasible to solve the Reynolds-Averaged Navier-Stokes equations for simple three-dimensional flows on advanced workstations. Combining multiple workstations into a network-based heterogeneous parallel computer allows the application of programming principles learned on MIMD (Multiple Instruction Multiple Data) distributed memory parallel computers to the solution of larger problems. An overset-grid flow solution code has been developed which uses a cluster of workstations as a network-based parallel computer. Inter-process communication is provided by the Parallel Virtual Machine (PVM) software. Solution speed equivalent to one-third of a Cray-YMP processor has been achieved from a cluster of nine commonly used engineering workstation processors. Load imbalance and communication overhead are the principal impediments to parallel efficiency in this application.

GPU Parallel Bundle Block Adjustment

Directory of Open Access Journals (Sweden)

ZHENG Maoteng

2017-09-01

Full Text Available To deal with massive data in photogrammetry, we introduce the GPU parallel computing technology. The preconditioned conjugate gradient and inexact Newton method are also applied to decrease the iteration times while solving the normal equation. A brand new workflow of bundle adjustment is developed to utilize GPU parallel computing technology. Our method can avoid the storage and inversion of the big normal matrix, and compute the normal matrix in real time. The proposed method can not only largely decrease the memory requirement of normal matrix, but also largely improve the efficiency of bundle adjustment. It also achieves the same accuracy as the conventional method. Preliminary experiment results show that the bundle adjustment of a dataset with about 4500 images and 9 million image points can be done in only 1.5 minutes while achieving sub-pixel accuracy.

Performance Analysis of 3D Massive MIMO Cellular Systems with Collaborative Base Station

Directory of Open Access Journals (Sweden)

Xingwang Li

2014-01-01

Full Text Available Massive MIMO have drawn considerable attention as they enable significant capacity and coverage improvement in wireless cellular network. However, pilot contamination is a great challenge in massive MIMO systems. Under this circumstance, cooperation and three-dimensional (3D MIMO are emerging technologies to eliminate the pilot contamination and to enhance the performance relative to the traditional interference-limited implementations. Motivated by this, we investigate the achievable sum rate performance of MIMO systems in the uplink employing cooperative base station (BS and 3D MIMO systems. In our model, we consider the effects of both large-scale and small-scale fading, as well as the spatial correlation and indoor-to-outdoor high-rise propagation environment. In particular, we investigate the cooperative communication model based on 3D MIMO and propose a closed-form lower bound on the sum rate. Utilizing this bound, we pursue a “large-system” analysis and provide the asymptotic expression when the number of antennas at the BS grows large, and when the numbers of antennas at transceiver grow large with a fixed ratio. We demonstrate that the lower bound is very tight and becomes exact in the massive MIMO system limits. Finally, under the sum rate maximization condition, we derive the optimal number of UTs to be served.

A parallel orbital-updating based plane-wave basis method for electronic structure calculations

International Nuclear Information System (INIS)

Pan, Yan; Dai, Xiaoying; Gironcoli, Stefano de; Gong, Xin-Gao; Rignanese, Gian-Marco; Zhou, Aihui

2017-01-01

Highlights: • Propose three parallel orbital-updating based plane-wave basis methods for electronic structure calculations. • These new methods can avoid the generating of large scale eigenvalue problems and then reduce the computational cost. • These new methods allow for two-level parallelization which is particularly interesting for large scale parallelization. • Numerical experiments show that these new methods are reliable and efficient for large scale calculations on modern supercomputers. - Abstract: Motivated by the recently proposed parallel orbital-updating approach in real space method , we propose a parallel orbital-updating based plane-wave basis method for electronic structure calculations, for solving the corresponding eigenvalue problems. In addition, we propose two new modified parallel orbital-updating methods. Compared to the traditional plane-wave methods, our methods allow for two-level parallelization, which is particularly interesting for large scale parallelization. Numerical experiments show that these new methods are more reliable and efficient for large scale calculations on modern supercomputers.

Big Data GPU-Driven Parallel Processing Spatial and Spatio-Temporal Clustering Algorithms

Science.gov (United States)

Konstantaras, Antonios; Skounakis, Emmanouil; Kilty, James-Alexander; Frantzeskakis, Theofanis; Maravelakis, Emmanuel

2016-04-01

Advances in graphics processing units' technology towards encompassing parallel architectures [1], comprised of thousands of cores and multiples of parallel threads, provide the foundation in terms of hardware for the rapid processing of various parallel applications regarding seismic big data analysis. Seismic data are normally stored as collections of vectors in massive matrices, growing rapidly in size as wider areas are covered, denser recording networks are being established and decades of data are being compiled together [2]. Yet, many processes regarding seismic data analysis are performed on each seismic event independently or as distinct tiles [3] of specific grouped seismic events within a much larger data set. Such processes, independent of one another can be performed in parallel narrowing down processing times drastically [1,3]. This research work presents the development and implementation of three parallel processing algorithms using Cuda C [4] for the investigation of potentially distinct seismic regions [5,6] present in the vicinity of the southern Hellenic seismic arc. The algorithms, programmed and executed in parallel comparatively, are the: fuzzy k-means clustering with expert knowledge [7] in assigning overall clusters' number; density-based clustering [8]; and a selves-developed spatio-temporal clustering algorithm encompassing expert [9] and empirical knowledge [10] for the specific area under investigation. Indexing terms: GPU parallel programming, Cuda C, heterogeneous processing, distinct seismic regions, parallel clustering algorithms, spatio-temporal clustering References [1] Kirk, D. and Hwu, W.: 'Programming massively parallel processors - A hands-on approach', 2nd Edition, Morgan Kaufman Publisher, 2013 [2] Konstantaras, A., Valianatos, F., Varley, M.R. and Makris, J.P.: 'Soft-Computing Modelling of Seismicity in the Southern Hellenic Arc', Geoscience and Remote Sensing Letters, vol. 5 (3), pp. 323-327, 2008 [3] Papadakis, S. and

Parallel computers and three-dimensional computational electromagnetics

International Nuclear Information System (INIS)

Madsen, N.K.

1994-01-01

The authors have continued to enhance their ability to use new massively parallel processing computers to solve time-domain electromagnetic problems. New vectorization techniques have improved the performance of their code DSI3D by factors of 5 to 15, depending on the computer used. New radiation boundary conditions and far-field transformations now allow the computation of radar cross-section values for complex objects. A new parallel-data extraction code has been developed that allows the extraction of data subsets from large problems, which have been run on parallel computers, for subsequent post-processing on workstations with enhanced graphics capabilities. A new charged-particle-pushing version of DSI3D is under development. Finally, DSI3D has become a focal point for several new Cooperative Research and Development Agreement activities with industrial companies such as Lockheed Advanced Development Company, Varian, Hughes Electron Dynamics Division, General Atomic, and Cray

Application of massively parallel sequencing to genetic diagnosis in multiplex families with idiopathic sensorineural hearing impairment.

Directory of Open Access Journals (Sweden)

Chen-Chi Wu

Full Text Available Despite the clinical utility of genetic diagnosis to address idiopathic sensorineural hearing impairment (SNHI, the current strategy for screening mutations via Sanger sequencing suffers from the limitation that only a limited number of DNA fragments associated with common deafness mutations can be genotyped. Consequently, a definitive genetic diagnosis cannot be achieved in many families with discernible family history. To investigate the diagnostic utility of massively parallel sequencing (MPS, we applied the MPS technique to 12 multiplex families with idiopathic SNHI in which common deafness mutations had previously been ruled out. NimbleGen sequence capture array was designed to target all protein coding sequences (CDSs and 100 bp of the flanking sequence of 80 common deafness genes. We performed MPS on the Illumina HiSeq2000, and applied BWA, SAMtools, Picard, GATK, Variant Tools, ANNOVAR, and IGV for bioinformatics analyses. Initial data filtering with allele frequencies (0.95 prioritized 5 indels (insertions/deletions and 36 missense variants in the 12 multiplex families. After further validation by Sanger sequencing, segregation pattern, and evolutionary conservation of amino acid residues, we identified 4 variants in 4 different genes, which might lead to SNHI in 4 families compatible with autosomal dominant inheritance. These included GJB2 p.R75Q, MYO7A p.T381M, KCNQ4 p.S680F, and MYH9 p.E1256K. Among them, KCNQ4 p.S680F and MYH9 p.E1256K were novel. In conclusion, MPS allows genetic diagnosis in multiplex families with idiopathic SNHI by detecting mutations in relatively uncommon deafness genes.

Parallel k-means++ for Multiple Shared-Memory Architectures

Energy Technology Data Exchange (ETDEWEB)

Mackey, Patrick S.; Lewis, Robert R.

2016-09-22

In recent years k-means++ has become a popular initialization technique for improved k-means clustering. To date, most of the work done to improve its performance has involved parallelizing algorithms that are only approximations of k-means++. In this paper we present a parallelization of the exact k-means++ algorithm, with a proof of its correctness. We develop implementations for three distinct shared-memory architectures: multicore CPU, high performance GPU, and the massively multithreaded Cray XMT platform. We demonstrate the scalability of the algorithm on each platform. In addition we present a visual approach for showing which platform performed k-means++ the fastest for varying data sizes.

Parallel processing is good for your scientific codes...But massively parallel processing is so much better

International Nuclear Information System (INIS)

Thomas, B.; Domain, Ch.; Souffez, Y.; Eon-Duval, P.

1998-01-01

Harnessing the power of many computers, to solve concurrently difficult scientific problems, is one of the most innovative trend in High Performance Computing. At EDF, we have invested in parallel computing and have achieved significant results. First we improved the processing speed of strategic codes, in order to extend their scope. Then we turned to numerical simulations at the atomic scale. These computations, we never dreamt of before, provided us with a better understanding of metallurgic phenomena. More precisely we were able to trace defects in alloys that are used in nuclear power plants. (author)

Thermal Casimir effect in Kerr spacetime with quintessence and massive gravitons

Energy Technology Data Exchange (ETDEWEB)

Bezerra, V.B. [Universidade Federal da Paraiba, Departamento de Fisica, Joao Pessoa, PB (Brazil); Christiansen, H.R. [Ciencia e Tecnologia do Ceara (IFCE), Departamento de Fisica, Instituto Federal de Educacao, Sobral, CE (Brazil); Cunha, M.S. [Universidade Estadual do Ceara, Grupo de Fisica Teorica (GFT), Fortaleza, CE (Brazil); Muniz, C.R.; Tahim, M.O. [Universidade Estadual do Ceara, Faculdade de Educacao, Ciencias e Letras do Sertao Central, Quixada, CE (Brazil)

2017-11-15

Starting from an analytical expression for the Helmholtz free energy we calculate the thermal corrections to the Casimir energy density and entropy within nearby ideal parallel plates in the vacuum of a massless scalar field. Our framework is the Kerr spacetime in the presence of quintessence and massive gravitons. The high and low temperature regimes are especially analyzed in order to distinguish the main contributions. For instance, in the high temperature regime, we show that the force between the plates is repulsive and grows with both the quintessence and the massive gravitons. Regarding the Casimir entropy, our results are in agreement with the Nernst heat theorem and therefore confirm the third law of thermodynamics in the present scenario. (orig.)

Base drive for paralleled inverter systems

Science.gov (United States)

Nagano, S. (Inventor)

1980-01-01

In a paralleled inverter system, a positive feedback current derived from the total current from all of the modules of the inverter system is applied to the base drive of each of the power transistors of all modules, thereby to provide all modules protection against open or short circuit faults occurring in any of the modules, and force equal current sharing among the modules during turn on of the power transistors.

COLA with massive neutrinos

Energy Technology Data Exchange (ETDEWEB)

Wright, Bill S.; Winther, Hans A.; Koyama, Kazuya, E-mail: bill.wright@port.ac.uk, E-mail: hans.winther@port.ac.uk, E-mail: kazuya.koyama@port.ac.uk [Institute of Cosmology and Gravitation, University of Portsmouth, Dennis Sciama Building, Burnaby Road, Portsmouth, Hampshire, PO1 3FX (United Kingdom)

2017-10-01

The effect of massive neutrinos on the growth of cold dark matter perturbations acts as a scale-dependent Newton's constant and leads to scale-dependent growth factors just as we often find in models of gravity beyond General Relativity. We show how to compute growth factors for ΛCDM and general modified gravity cosmologies combined with massive neutrinos in Lagrangian perturbation theory for use in COLA and extensions thereof. We implement this together with the grid-based massive neutrino method of Brandbyge and Hannestad in MG-PICOLA and compare COLA simulations to full N -body simulations of ΛCDM and f ( R ) gravity with massive neutrinos. Our implementation is computationally cheap if the underlying cosmology already has scale-dependent growth factors and it is shown to be able to produce results that match N -body to percent level accuracy for both the total and CDM matter power-spectra up to k ∼< 1 h /Mpc.

Web based parallel/distributed medical data mining using software agents

Energy Technology Data Exchange (ETDEWEB)

Kargupta, H.; Stafford, B.; Hamzaoglu, I.

1997-12-31

This paper describes an experimental parallel/distributed data mining system PADMA (PArallel Data Mining Agents) that uses software agents for local data accessing and analysis and a web based interface for interactive data visualization. It also presents the results of applying PADMA for detecting patterns in unstructured texts of postmortem reports and laboratory test data for Hepatitis C patients.

Investigation and experimental validation of the contribution of optical interconnects in the SYMPHONIE massively parallel computer

International Nuclear Information System (INIS)

Scheer, Patrick

1998-01-01

Progress in microelectronics lead to electronic circuits which are increasingly integrated, with an operating frequency and an inputs/outputs count larger than the ones supported by printed circuit board and back-plane technologies. As a result, distributed systems with several boards cannot fully exploit the performance of integrated circuits. In synchronous parallel computers, the situation is worsen since the overall system performances rely on the efficiency of electrical interconnects between the integrated circuits which include the processing elements (PE). The study of a real parallel computer named SYMPHONIE shows for instance that the system operating frequency is far smaller than the capabilities of the microelectronics technology used for the PE implementation. Optical interconnections may cancel these limitations by providing more efficient connections between the PE. Especially, free-space optical interconnections based on vertical-cavity surface-emitting lasers (VCSEL), micro-lens and PIN photodiodes are compatible with the required features of the PE communications. Zero bias modulation of VCSEL with CMOS-compatible digital signals is studied and experimentally demonstrated. A model of the propagation of truncated gaussian beams through micro-lenses is developed. It is then used to optimise the geometry of the detection areas. A dedicated mechanical system is also proposed and implemented for integrating free-space optical interconnects in a standard electronic environment, representative of the one of parallel computer systems. A specially designed demonstrator provides the experimental validation of the above physical concepts. (author) [fr

Fast parallel DNA-based algorithms for molecular computation: the set-partition problem.

Science.gov (United States)

Chang, Weng-Long

2007-12-01

This paper demonstrates that basic biological operations can be used to solve the set-partition problem. In order to achieve this, we propose three DNA-based algorithms, a signed parallel adder, a signed parallel subtractor and a signed parallel comparator, that formally verify our designed molecular solutions for solving the set-partition problem.

QR-decomposition based SENSE reconstruction using parallel architecture.

Science.gov (United States)

Ullah, Irfan; Nisar, Habab; Raza, Haseeb; Qasim, Malik; Inam, Omair; Omer, Hammad

2018-04-01

Magnetic Resonance Imaging (MRI) is a powerful medical imaging technique that provides essential clinical information about the human body. One major limitation of MRI is its long scan time. Implementation of advance MRI algorithms on a parallel architecture (to exploit inherent parallelism) has a great potential to reduce the scan time. Sensitivity Encoding (SENSE) is a Parallel Magnetic Resonance Imaging (pMRI) algorithm that utilizes receiver coil sensitivities to reconstruct MR images from the acquired under-sampled k-space data. At the heart of SENSE lies inversion of a rectangular encoding matrix. This work presents a novel implementation of GPU based SENSE algorithm, which employs QR decomposition for the inversion of the rectangular encoding matrix. For a fair comparison, the performance of the proposed GPU based SENSE reconstruction is evaluated against single and multicore CPU using openMP. Several experiments against various acceleration factors (AFs) are performed using multichannel (8, 12 and 30) phantom and in-vivo human head and cardiac datasets. Experimental results show that GPU significantly reduces the computation time of SENSE reconstruction as compared to multi-core CPU (approximately 12x speedup) and single-core CPU (approximately 53x speedup) without any degradation in the quality of the reconstructed images. Copyright © 2018 Elsevier Ltd. All rights reserved.

Fast parallel molecular algorithms for DNA-based computation: factoring integers.

Science.gov (United States)

Chang, Weng-Long; Guo, Minyi; Ho, Michael Shan-Hui

2005-06-01

The RSA public-key cryptosystem is an algorithm that converts input data to an unrecognizable encryption and converts the unrecognizable data back into its original decryption form. The security of the RSA public-key cryptosystem is based on the difficulty of factoring the product of two large prime numbers. This paper demonstrates to factor the product of two large prime numbers, and is a breakthrough in basic biological operations using a molecular computer. In order to achieve this, we propose three DNA-based algorithms for parallel subtractor, parallel comparator, and parallel modular arithmetic that formally verify our designed molecular solutions for factoring the product of two large prime numbers. Furthermore, this work indicates that the cryptosystems using public-key are perhaps insecure and also presents clear evidence of the ability of molecular computing to perform complicated mathematical operations.

III - Template Metaprogramming for massively parallel scientific computing - Templates for Iteration; Thread-level Parallelism

CERN Multimedia

CERN. Geneva

2016-01-01

Large scale scientific computing raises questions on different levels ranging from the fomulation of the problems to the choice of the best algorithms and their implementation for a specific platform. There are similarities in these different topics that can be exploited by modern-style C++ template metaprogramming techniques to produce readable, maintainable and generic code. Traditional low-level code tend to be fast but platform-dependent, and it obfuscates the meaning of the algorithm. On the other hand, object-oriented approach is nice to read, but may come with an inherent performance penalty. These lectures aim to present he basics of the Expression Template (ET) idiom which allows us to keep the object-oriented approach without sacrificing performance. We will in particular show to to enhance ET to include SIMD vectorization. We will then introduce techniques for abstracting iteration, and introduce thread-level parallelism for use in heavy data-centric loads. We will show to to apply these methods i...

Potential human pathogenic bacteria in a mixed urban watershed as revealed by pyrosequencing.

Directory of Open Access Journals (Sweden)

A Mark Ibekwe

Full Text Available Current microbial source tracking (MST methods for water depend on testing for fecal indicator bacterial counts or specific marker gene sequences to identify fecal contamination where potential human pathogenic bacteria could be present. In this study, we applied 454 high-throughput pyrosequencing to identify bacterial pathogen DNA sequences, including those not traditionally monitored by MST and correlated their abundances to specific sources of contamination such as urban runoff and agricultural runoff from concentrated animal feeding operations (CAFOs, recreation park area, waste-water treatment plants, and natural sites with little or no human activities. Samples for pyrosequencing were surface water, and sediment collected from 19 sites. A total of 12,959 16S rRNA gene sequences with average length of ≤400 bp were obtained, and were assigned to corresponding taxonomic ranks using ribosomal database project (RDP, Classifier and Greengenes databases. The percent of total potential pathogens were highest in urban runoff water (7.94%, agricultural runoff sediment (6.52%, and Prado Park sediment (6.00%, respectively. Although the numbers of DNA sequence tags from pyrosequencing were very high for the natural site, corresponding percent potential pathogens were very low (3.78-4.08%. Most of the potential pathogenic bacterial sequences identified were from three major phyla, namely, Proteobacteria, Bacteroidetes, and Firmicutes. The use of deep sequencing may provide improved and faster methods for the identification of pathogen sources in most watersheds so that better risk assessment methods may be developed to enhance public health.

Use of pyrosequencing and DNA barcodes to monitor variations in Firmicutes and Bacteroidetes communities in the gut microbiota of obese humans

Directory of Open Access Journals (Sweden)

Raoult Didier

2008-12-01

Full Text Available Abstract Background Recent studies of 16S rRNA genes in the mammalian gut microbiota distinguished a higher Firmicutes/Bacteroidetes ratio in obese individuals compared to lean individuals. This ratio was estimated using a clonal Sanger sequencing approach which is time-consuming and requires laborious data analysis. In contrast, new high-throughput pyrosequencing technology offers an inexpensive alternative to clonal Sanger sequencing and would significantly advance our understanding of obesity via the development of a clinical diagnostic method. Here we present a cost-effective method that combines 16S rRNA pyrosequencing and DNA barcodes of the Firmicutes and Bacteroidetes 16S rRNA genes to determine the Firmicutes/Bacteroidetes ratio in the gut microbiota of obese humans. Results The main result was the identification of DNA barcodes targeting the Firmicutes and Bacteroidetes phyla. These barcodes were validated using previously published 16S rRNA gut microbiota clone libraries. In addition, an accurate F/B ratio was found when the DNA barcodes were applied to short pyrosequencing reads of published gut metagenomes. Finally, the barcodes were utilized to define the F/B ratio of 16S rRNA pyrosequencing data generated from brain abscess pus and cystic fibrosis sputum. Conclusion Using DNA barcodes of Bacteroidetes and Firmicutes 16S rRNA genes combined with pyrosequencing is a cost-effective method for monitoring relevant changes in the relative abundance of Firmicutes and Bacteroidetes bacterial communities in microbial ecosystems.

A Parallel Modular Biomimetic Cilia Sorting Platform

Directory of Open Access Journals (Sweden)

James G. H. Whiting

2018-03-01

Full Text Available The aquatic unicellular organism Paramecium caudatum uses cilia to swim around its environment and to graze on food particles and bacteria. Paramecia use waves of ciliary beating for locomotion, intake of food particles and sensing. There is some evidence that Paramecia pre-sort food particles by discarding larger particles, but intake the particles matching their mouth cavity. Most prior attempts to mimic cilia-based manipulation merely mimicked the overall action rather than the beating of cilia. The majority of massive-parallel actuators are controlled by a central computer; however, a distributed control would be far more true-to-life. We propose and test a distributed parallel cilia platform where each actuating unit is autonomous, yet exchanging information with its closest neighboring units. The units are arranged in a hexagonal array. Each unit is a tileable circuit board, with a microprocessor, color-based object sensor and servo-actuated biomimetic cilia actuator. Localized synchronous communication between cilia allowed for the emergence of coordinated action, moving different colored objects together. The coordinated beating action was capable of moving objects up to 4 cm/s at its highest beating frequency; however, objects were moved at a speed proportional to the beat frequency. Using the local communication, we were able to detect the shape of objects and rotating an object using edge detection was performed; however, lateral manipulation using shape information was unsuccessful.

Parallelization and checkpointing of GPU applications through program transformation

Energy Technology Data Exchange (ETDEWEB)

Solano-Quinde, Lizandro Damian [Iowa State Univ., Ames, IA (United States)

2012-01-01

GPUs have emerged as a powerful tool for accelerating general-purpose applications. The availability of programming languages that makes writing general-purpose applications for running on GPUs tractable have consolidated GPUs as an alternative for accelerating general purpose applications. Among the areas that have benefited from GPU acceleration are: signal and image processing, computational fluid dynamics, quantum chemistry, and, in general, the High Performance Computing (HPC) Industry. In order to continue to exploit higher levels of parallelism with GPUs, multi-GPU systems are gaining popularity. In this context, single-GPU applications are parallelized for running in multi-GPU systems. Furthermore, multi-GPU systems help to solve the GPU memory limitation for applications with large application memory footprint. Parallelizing single-GPU applications has been approached by libraries that distribute the workload at runtime, however, they impose execution overhead and are not portable. On the other hand, on traditional CPU systems, parallelization has been approached through application transformation at pre-compile time, which enhances the application to distribute the workload at application level and does not have the issues of library-based approaches. Hence, a parallelization scheme for GPU systems based on application transformation is needed. Like any computing engine of today, reliability is also a concern in GPUs. GPUs are vulnerable to transient and permanent failures. Current checkpoint/restart techniques are not suitable for systems with GPUs. Checkpointing for GPU systems present new and interesting challenges, primarily due to the natural differences imposed by the hardware design, the memory subsystem architecture, the massive number of threads, and the limited amount of synchronization among threads. Therefore, a checkpoint/restart technique suitable for GPU systems is needed. The goal of this work is to exploit higher levels of parallelism and

Sensitivity Analysis of the Proximal-Based Parallel Decomposition Methods

Directory of Open Access Journals (Sweden)

Feng Ma

2014-01-01

Full Text Available The proximal-based parallel decomposition methods were recently proposed to solve structured convex optimization problems. These algorithms are eligible for parallel computation and can be used efficiently for solving large-scale separable problems. In this paper, compared with the previous theoretical results, we show that the range of the involved parameters can be enlarged while the convergence can be still established. Preliminary numerical tests on stable principal component pursuit problem testify to the advantages of the enlargement.

Algorithms and data structures for massively parallel generic adaptive finite element codes

KAUST Repository

Bangerth, Wolfgang

2011-12-01

Today\\'s largest supercomputers have 100,000s of processor cores and offer the potential to solve partial differential equations discretized by billions of unknowns. However, the complexity of scaling to such large machines and problem sizes has so far prevented the emergence of generic software libraries that support such computations, although these would lower the threshold of entry and enable many more applications to benefit from large-scale computing. We are concerned with providing this functionality for mesh-adaptive finite element computations. We assume the existence of an "oracle" that implements the generation and modification of an adaptive mesh distributed across many processors, and that responds to queries about its structure. Based on querying the oracle, we develop scalable algorithms and data structures for generic finite element methods. Specifically, we consider the parallel distribution of mesh data, global enumeration of degrees of freedom, constraints, and postprocessing. Our algorithms remove the bottlenecks that typically limit large-scale adaptive finite element analyses. We demonstrate scalability of complete finite element workflows on up to 16,384 processors. An implementation of the proposed algorithms, based on the open source software p4est as mesh oracle, is provided under an open source license through the widely used deal.II finite element software library. © 2011 ACM 0098-3500/2011/12-ART10 $10.00.

Pyrosequencing analysis of the microbial diversity of airag, khoormog and tarag, traditional fermented dairy products of mongolia.

Science.gov (United States)

Oki, Kaihei; Dugersuren, Jamyan; Demberel, Shirchin; Watanabe, Koichi

2014-01-01

Here, we used pyrosequencing to obtain a detailed analysis of the microbial diversities of traditional fermented dairy products of Mongolia. From 22 Airag (fermented mare's milk), 5 Khoormog (fermented camel's milk) and 26 Tarag (fermented milk of cows, goats and yaks) samples collected in the Mongolian provinces of Arhangai, Bulgan, Dundgobi, Tov, Uburhangai and Umnugobi, we obtained a total of 81 operational taxonomic units, which were assigned to 15 families, 21 genera and 41 species in 3 phyla. The genus Lactobacillus is a core bacterial component of Mongolian fermented milks, and Lactobacillus helveticus, Lactobacillus kefiranofaciens and Lactobacillus delbrueckii were the predominant species of lactic acid bacteria (LAB) in the Airag, Khoormog and Tarag samples, respectively. By using this pyrosequencing approach, we successfully detected most LAB species that have been isolated as well as seven LAB species that have not been found in our previous culture-based study. A subsequent analysis of the principal components of the samples revealed that L. delbrueckii, L. helveticus, L. kefiranofaciens and Streptococcus thermophilus were the main factors influencing the microbial diversity of these Mongolian traditional fermented dairy products and that this diversity correlated with the animal species from which the milk was sourced.

Parallel Harmony Search Based Distributed Energy Resource Optimization

Energy Technology Data Exchange (ETDEWEB)

Ceylan, Oguzhan [ORNL; Liu, Guodong [ORNL; Tomsovic, Kevin [University of Tennessee, Knoxville (UTK)

2015-01-01

This paper presents a harmony search based parallel optimization algorithm to minimize voltage deviations in three phase unbalanced electrical distribution systems and to maximize active power outputs of distributed energy resources (DR). The main contribution is to reduce the adverse impacts on voltage profile during a day as photovoltaics (PVs) output or electrical vehicles (EVs) charging changes throughout a day. The IEEE 123- bus distribution test system is modified by adding DRs and EVs under different load profiles. The simulation results show that by using parallel computing techniques, heuristic methods may be used as an alternative optimization tool in electrical power distribution systems operation.

Shotgun pyrosequencing metagenomic analyses of dusts from swine confinement and grain facilities.

Science.gov (United States)

Boissy, Robert J; Romberger, Debra J; Roughead, William A; Weissenburger-Moser, Lisa; Poole, Jill A; LeVan, Tricia D

2014-01-01

Inhalation of agricultural dusts causes inflammatory reactions and symptoms such as headache, fever, and malaise, which can progress to chronic airway inflammation and associated diseases, e.g. asthma, chronic bronchitis, chronic obstructive pulmonary disease, and hypersensitivity pneumonitis. Although in many agricultural environments feed particles are the major constituent of these dusts, the inflammatory responses that they provoke are likely attributable to particle-associated bacteria, archaebacteria, fungi, and viruses. In this study, we performed shotgun pyrosequencing metagenomic analyses of DNA from dusts from swine confinement facilities or grain elevators, with comparisons to dusts from pet-free households. DNA sequence alignment showed that 19% or 62% of shotgun pyrosequencing metagenomic DNA sequence reads from swine facility or household dusts, respectively, were of swine or human origin, respectively. In contrast only 2% of such reads from grain elevator dust were of mammalian origin. These metagenomic shotgun reads of mammalian origin were excluded from our analyses of agricultural dust microbiota. The ten most prevalent bacterial taxa identified in swine facility compared to grain elevator or household dust were comprised of 75%, 16%, and 42% gram-positive organisms, respectively. Four of the top five swine facility dust genera were assignable (Clostridium, Lactobacillus, Ruminococcus, and Eubacterium, ranging from 4% to 19% relative abundance). The relative abundances of these four genera were lower in dust from grain elevators or pet-free households. These analyses also highlighted the predominance in swine facility dust of Firmicutes (70%) at the phylum level, Clostridia (44%) at the Class level, and Clostridiales at the Order level (41%). In summary, shotgun pyrosequencing metagenomic analyses of agricultural dusts show that they differ qualitatively and quantitatively at the level of microbial taxa present, and that the bioinformatic analyses

Shotgun pyrosequencing metagenomic analyses of dusts from swine confinement and grain facilities.

Directory of Open Access Journals (Sweden)

Robert J Boissy

Full Text Available Inhalation of agricultural dusts causes inflammatory reactions and symptoms such as headache, fever, and malaise, which can progress to chronic airway inflammation and associated diseases, e.g. asthma, chronic bronchitis, chronic obstructive pulmonary disease, and hypersensitivity pneumonitis. Although in many agricultural environments feed particles are the major constituent of these dusts, the inflammatory responses that they provoke are likely attributable to particle-associated bacteria, archaebacteria, fungi, and viruses. In this study, we performed shotgun pyrosequencing metagenomic analyses of DNA from dusts from swine confinement facilities or grain elevators, with comparisons to dusts from pet-free households. DNA sequence alignment showed that 19% or 62% of shotgun pyrosequencing metagenomic DNA sequence reads from swine facility or household dusts, respectively, were of swine or human origin, respectively. In contrast only 2% of such reads from grain elevator dust were of mammalian origin. These metagenomic shotgun reads of mammalian origin were excluded from our analyses of agricultural dust microbiota. The ten most prevalent bacterial taxa identified in swine facility compared to grain elevator or household dust were comprised of 75%, 16%, and 42% gram-positive organisms, respectively. Four of the top five swine facility dust genera were assignable (Clostridium, Lactobacillus, Ruminococcus, and Eubacterium, ranging from 4% to 19% relative abundance. The relative abundances of these four genera were lower in dust from grain elevators or pet-free households. These analyses also highlighted the predominance in swine facility dust of Firmicutes (70% at the phylum level, Clostridia (44% at the Class level, and Clostridiales at the Order level (41%. In summary, shotgun pyrosequencing metagenomic analyses of agricultural dusts show that they differ qualitatively and quantitatively at the level of microbial taxa present, and that the

Parallel dispatch: a new paradigm of electrical power system dispatch

Energy Technology Data Exchange (ETDEWEB)

Zhang, Jun Jason; Wang, Fei-Yue; Wang, Qiang; Hao, Dazhi; Yang, Xiaojing; Gao, David Wenzhong; Zhao, Xiangyang; Zhang, Yingchen

2018-01-01

Modern power systems are evolving into sociotechnical systems with massive complexity, whose real-time operation and dispatch go beyond human capability. Thus, the need for developing and applying new intelligent power system dispatch tools are of great practical significance. In this paper, we introduce the overall business model of power system dispatch, the top level design approach of an intelligent dispatch system, and the parallel intelligent technology with its dispatch applications. We expect that a new dispatch paradigm, namely the parallel dispatch, can be established by incorporating various intelligent technologies, especially the parallel intelligent technology, to enable secure operation of complex power grids, extend system operators U+02BC capabilities, suggest optimal dispatch strategies, and to provide decision-making recommendations according to power system operational goals.

Beam dynamics simulations using a parallel version of PARMILA

International Nuclear Information System (INIS)

Ryne, R.D.

1996-01-01

The computer code PARMILA has been the primary tool for the design of proton and ion linacs in the United States for nearly three decades. Previously it was sufficient to perform simulations with of order 10000 particles, but recently the need to perform high resolution halo studies for next-generation, high intensity linacs has made it necessary to perform simulations with of order 100 million particles. With the advent of massively parallel computers such simulations are now within reach. Parallel computers already make it possible, for example, to perform beam dynamics calculations with tens of millions of particles, requiring over 10 GByte of core memory, in just a few hours. Also, parallel computers are becoming easier to use thanks to the availability of mature, Fortran-like languages such as Connection Machine Fortran and High Performance Fortran. We will describe our experience developing a parallel version of PARMILA and the performance of the new code

Beam dynamics simulations using a parallel version of PARMILA

International Nuclear Information System (INIS)

Ryne, Robert

1996-01-01

The computer code PARMILA has been the primary tool for the design of proton and ion linacs in the United States for nearly three decades. Previously it was sufficient to perform simulations with of order 10000 particles, but recently the need to perform high resolution halo studies for next-generation, high intensity linacs has made it necessary to perform simulations with of order 100 million particles. With the advent of massively parallel computers such simulations are now within reach. Parallel computers already make it possible, for example, to perform beam dynamics calculations with tens of millions of particles, requiring over 10 GByte of core memory, in just a few hours. Also, parallel computers are becoming easier to use thanks to the availability of mature, Fortran-like languages such as Connection Machine Fortran and High Performance Fortran. We will describe our experience developing a parallel version of PARMILA and the performance of the new code. (author)

Algorithm comparison and benchmarking using a parallel spectra transform shallow water model

Energy Technology Data Exchange (ETDEWEB)

Worley, P.H. [Oak Ridge National Lab., TN (United States); Foster, I.T.; Toonen, B. [Argonne National Lab., IL (United States)

1995-04-01

In recent years, a number of computer vendors have produced supercomputers based on a massively parallel processing (MPP) architecture. These computers have been shown to be competitive in performance with conventional vector supercomputers for some applications. As spectral weather and climate models are heavy users of vector supercomputers, it is interesting to determine how these models perform on MPPS, and which MPPs are best suited to the execution of spectral models. The benchmarking of MPPs is complicated by the fact that different algorithms may be more efficient on different architectures. Hence, a comprehensive benchmarking effort must answer two related questions: which algorithm is most efficient on each computer and how do the most efficient algorithms compare on different computers. In general, these are difficult questions to answer because of the high cost associated with implementing and evaluating a range of different parallel algorithms on each MPP platform.

MASSIVELY PARALLEL LATENT SEMANTIC ANALYSES USING A GRAPHICS PROCESSING UNIT

Energy Technology Data Exchange (ETDEWEB)

Cavanagh, J.; Cui, S.

2009-01-01

Latent Semantic Analysis (LSA) aims to reduce the dimensions of large term-document datasets using Singular Value Decomposition. However, with the ever-expanding size of datasets, current implementations are not fast enough to quickly and easily compute the results on a standard PC. A graphics processing unit (GPU) can solve some highly parallel problems much faster than a traditional sequential processor or central processing unit (CPU). Thus, a deployable system using a GPU to speed up large-scale LSA processes would be a much more effective choice (in terms of cost/performance ratio) than using a PC cluster. Due to the GPU’s application-specifi c architecture, harnessing the GPU’s computational prowess for LSA is a great challenge. We presented a parallel LSA implementation on the GPU, using NVIDIA® Compute Unifi ed Device Architecture and Compute Unifi ed Basic Linear Algebra Subprograms software. The performance of this implementation is compared to traditional LSA implementation on a CPU using an optimized Basic Linear Algebra Subprograms library. After implementation, we discovered that the GPU version of the algorithm was twice as fast for large matrices (1 000x1 000 and above) that had dimensions not divisible by 16. For large matrices that did have dimensions divisible by 16, the GPU algorithm ran fi ve to six times faster than the CPU version. The large variation is due to architectural benefi ts of the GPU for matrices divisible by 16. It should be noted that the overall speeds for the CPU version did not vary from relative normal when the matrix dimensions were divisible by 16. Further research is needed in order to produce a fully implementable version of LSA. With that in mind, the research we presented shows that the GPU is a viable option for increasing the speed of LSA, in terms of cost/performance ratio.

Comparative analysis of pyrosequencing and a phylogenetic microarray for exploring microbial community structures in the human distal intestine.

Directory of Open Access Journals (Sweden)

Marcus J Claesson

Full Text Available BACKGROUND: Variations in the composition of the human intestinal microbiota are linked to diverse health conditions. High-throughput molecular technologies have recently elucidated microbial community structure at much higher resolution than was previously possible. Here we compare two such methods, pyrosequencing and a phylogenetic array, and evaluate classifications based on two variable 16S rRNA gene regions. METHODS AND FINDINGS: Over 1.75 million amplicon sequences were generated from the V4 and V6 regions of 16S rRNA genes in bacterial DNA extracted from four fecal samples of elderly individuals. The phylotype richness, for individual samples, was 1,400-1,800 for V4 reads and 12,500 for V6 reads, and 5,200 unique phylotypes when combining V4 reads from all samples. The RDP-classifier was more efficient for the V4 than for the far less conserved and shorter V6 region, but differences in community structure also affected efficiency. Even when analyzing only 20% of the reads, the majority of the microbial diversity was captured in two samples tested. DNA from the four samples was hybridized against the Human Intestinal Tract (HIT Chip, a phylogenetic microarray for community profiling. Comparison of clustering of genus counts from pyrosequencing and HITChip data revealed highly similar profiles. Furthermore, correlations of sequence abundance and hybridization signal intensities were very high for lower-order ranks, but lower at family-level, which was probably due to ambiguous taxonomic groupings. CONCLUSIONS: The RDP-classifier consistently assigned most V4 sequences from human intestinal samples down to genus-level with good accuracy and speed. This is the deepest sequencing of single gastrointestinal samples reported to date, but microbial richness levels have still not leveled out. A majority of these diversities can also be captured with five times lower sampling-depth. HITChip hybridizations and resulting community profiles correlate

Performance Testing of Massive MIMO Base Station with Multi-Probe Anechoic Chamber Setups

DEFF Research Database (Denmark)

Zhang, Fengchun; Fan, Wei; Ji, Yilin

2018-01-01

The utilization of massive multiple-input multipleoutput (MIMO) antenna arrays at the base station (BS) side has been identified as an enabling technique for 5G communication systems. To evaluate the true end-to-end performance of BS's, an over-the-air (OTA) radiated method is required...

Massive branes

International Nuclear Information System (INIS)

Bergshoeff, E.; Ortin, T.

1998-01-01

We investigate the effective world-volume theories of branes in a background given by (the bosonic sector of) 10-dimensional massive IIA supergravity (''''massive branes'''') and their M-theoretic origin. In the case of the solitonic 5-brane of type IIA superstring theory the construction of the Wess-Zumino term in the world-volume action requires a dualization of the massive Neveu-Schwarz/Neveu-Schwarz target space 2-form field. We find that, in general, the effective world-volume theory of massive branes contains new world-volume fields that are absent in the massless case, i.e. when the mass parameter m of massive IIA supergravity is set to zero. We show how these new world-volume fields can be introduced in a systematic way. (orig.)

The diversity and structure of marine protists in the coastal waters of China revealed by morphological observation and 454 pyrosequencing

Science.gov (United States)

Liu, Yun; Song, Shuqun; Chen, Tiantian; Li, Caiwen

2017-04-01

Pyrosequencing of the 18S rRNA gene has been widely adopted to study the eukaryotic diversity in various types of environments, and has an advantage over traditional morphology methods in exploring unknown microbial communities. To comprehensively assess the diversity and community composition of marine protists in the coastal waters of China, we applied both morphological observations and high-throughput sequencing of the V2 and V3 regions of 18S rDNA simultaneously to analyze samples collected from the surface layer of the Yellow and East China Seas. Dinoflagellates, diatoms and ciliates were the three dominant protistan groups as revealed by the two methods. Diatoms were the first dominant protistan group in the microscopic observations, with Skeletonema mainly distributed in the nearshore eutrophic waters and Chaetoceros in higher temperature and higher pH waters. The mixotrophic dinoflagellates, Gymnodinium and Gyrodinium, were more competitive in the oligotrophic waters. The pyrosequencing method revealed an extensive diversity of dinoflagellates. Chaetoceros was the only dominant diatom group in the pyrosequencing dataset. Gyrodinium represented the most abundant reads and dominated the offshore oligotrophic protistan community as they were in the microscopic observations. The dominance of parasitic dinoflagellates in the pyrosequencing dataset, which were overlooked in the morphological observations, indicates more attention should be paid to explore the potential role of this group. Both methods provide coherent clustering of samples. Nutrient levels, salinity and pH were the main factors influencing the distribution of protists. This study demonstrates that different primer pairs used in the pyrosequencing will indicate different protistan community structures. A suitable marker may reveal more comprehensive composition of protists and provide valuable information on environmental drivers.

A mirror for lab-based quasi-monochromatic parallel x-rays.

Science.gov (United States)

Nguyen, Thanhhai; Lu, Xun; Lee, Chang Jun; Jung, Jin-Ho; Jin, Gye-Hwan; Kim, Sung Youb; Jeon, Insu

2014-09-01

A multilayered parabolic mirror with six W/Al bilayers was designed and fabricated to generate monochromatic parallel x-rays using a lab-based x-ray source. Using this mirror, curved bright bands were obtained in x-ray images as reflected x-rays. The parallelism of the reflected x-rays was investigated using the shape of the bands. The intensity and monochromatic characteristics of the reflected x-rays were evaluated through measurements of the x-ray spectra in the band. High intensity, nearly monochromatic, and parallel x-rays, which can be used for high resolution x-ray microscopes and local radiation therapy systems, were obtained.

Mn-silicide nanostructures aligned on massively parallel silicon nano-ribbons

International Nuclear Information System (INIS)

De Padova, Paola; Ottaviani, Carlo; Ronci, Fabio; Colonna, Stefano; Quaresima, Claudio; Cricenti, Antonio; Olivieri, Bruno; Dávila, Maria E; Hennies, Franz; Pietzsch, Annette; Shariati, Nina; Le Lay, Guy

2013-01-01

The growth of Mn nanostructures on a 1D grating of silicon nano-ribbons is investigated at atomic scale by means of scanning tunneling microscopy, low energy electron diffraction and core level photoelectron spectroscopy. The grating of silicon nano-ribbons represents an atomic scale template that can be used in a surface-driven route to control the combination of Si with Mn in the development of novel materials for spintronics devices. The Mn atoms show a preferential adsorption site on silicon atoms, forming one-dimensional nanostructures. They are parallel oriented with respect to the surface Si array, which probably predetermines the diffusion pathways of the Mn atoms during the process of nanostructure formation.

Flexure mechanism-based parallelism measurements for chip-on-glass bonding

International Nuclear Information System (INIS)

Jung, Seung Won; Yun, Won Soo; Jin, Songwan; Jeong, Young Hun; Kim, Bo Sun

2011-01-01

Recently, liquid crystal displays (LCDs) have played vital roles in a variety of electronic devices such as televisions, cellular phones, and desktop/laptop monitors because of their enhanced volume, performance, and functionality. However, there is still a need for thinner LCD panels due to the trend of miniaturization in electronic applications. Thus, chip-on-glass (COG) bonding has become one of the most important aspects in the LCD panel manufacturing process. In this study, a novel sensor was developed to measure the parallelism between the tooltip planes of the bonding head and the backup of the COG main bonder, which has previously been estimated by prescale pressure films in industry. The sensor developed in this study is based on a flexure mechanism, and it can measure the total pressing force and the inclination angles in two directions that satisfy the quantitative definition of parallelism. To improve the measurement accuracy, the sensor was calibrated based on the estimation of the total pressing force and the inclination angles using the least-squares method. To verify the accuracy of the sensor, the estimation results for parallelism were compared with those from prescale pressure film measurements. In addition, the influence of parallelism on the bonding quality was experimentally demonstrated. The sensor was successfully applied to the measurement of parallelism in the COG-bonding process with an accuracy of more than three times that of the conventional method using prescale pressure films

Parallel Algorithms for Switching Edges in Heterogeneous Graphs.

Science.gov (United States)

Bhuiyan, Hasanuzzaman; Khan, Maleq; Chen, Jiangzhuo; Marathe, Madhav

2017-06-01

An edge switch is an operation on a graph (or network) where two edges are selected randomly and one of their end vertices are swapped with each other. Edge switch operations have important applications in graph theory and network analysis, such as in generating random networks with a given degree sequence, modeling and analyzing dynamic networks, and in studying various dynamic phenomena over a network. The recent growth of real-world networks motivates the need for efficient parallel algorithms. The dependencies among successive edge switch operations and the requirement to keep the graph simple (i.e., no self-loops or parallel edges) as the edges are switched lead to significant challenges in designing a parallel algorithm. Addressing these challenges requires complex synchronization and communication among the processors leading to difficulties in achieving a good speedup by parallelization. In this paper, we present distributed memory parallel algorithms for switching edges in massive networks. These algorithms provide good speedup and scale well to a large number of processors. A harmonic mean speedup of 73.25 is achieved on eight different networks with 1024 processors. One of the steps in our edge switch algorithms requires the computation of multinomial random variables in parallel. This paper presents the first non-trivial parallel algorithm for the problem, achieving a speedup of 925 using 1024 processors.

A massively parallel method of characteristic neutral particle transport code for GPUs

International Nuclear Information System (INIS)

Boyd, W. R.; Smith, K.; Forget, B.

2013-01-01

Over the past 20 years, parallel computing has enabled computers to grow ever larger and more powerful while scientific applications have advanced in sophistication and resolution. This trend is being challenged, however, as the power consumption for conventional parallel computing architectures has risen to unsustainable levels and memory limitations have come to dominate compute performance. Heterogeneous computing platforms, such as Graphics Processing Units (GPUs), are an increasingly popular paradigm for solving these issues. This paper explores the applicability of GPUs for deterministic neutron transport. A 2D method of characteristics (MOC) code - OpenMOC - has been developed with solvers for both shared memory multi-core platforms as well as GPUs. The multi-threading and memory locality methodologies for the GPU solver are presented. Performance results for the 2D C5G7 benchmark demonstrate 25-35 x speedup for MOC on the GPU. The lessons learned from this case study will provide the basis for further exploration of MOC on GPUs as well as design decisions for hardware vendors exploring technologies for the next generation of machines for scientific computing. (authors)

Global transcriptional profiling of the toxic dinoflagellate Alexandrium fundyense using Massively Parallel Signature Sequencing

Directory of Open Access Journals (Sweden)

Anderson Donald M

2006-04-01

Full Text Available Abstract Background Dinoflagellates are one of the most important classes of marine and freshwater algae, notable both for their functional diversity and ecological significance. They occur naturally as free-living cells, as endosymbionts of marine invertebrates and are well known for their involvement in "red tides". Dinoflagellates are also notable for their unusual genome content and structure, which suggests that the organization and regulation of dinoflagellate genes may be very different from that of most eukaryotes. To investigate the content and regulation of the dinoflagellate genome, we performed a global analysis of the transcriptome of the toxic dinoflagellate Alexandrium fundyense under nitrate- and phosphate-limited conditions using Massively Parallel Signature Sequencing (MPSS. Results Data from the two MPSS libraries showed that the number of unique signatures found in A. fundyense cells is similar to that of humans and Arabidopsis thaliana, two eukaryotes that have been extensively analyzed using this method. The general distribution, abundance and expression patterns of the A. fundyense signatures were also quite similar to other eukaryotes, and at least 10% of the A. fundyense signatures were differentially expressed between the two conditions. RACE amplification and sequencing of a subset of signatures showed that multiple signatures arose from sequence variants of a single gene. Single signatures also mapped to different sequence variants of the same gene. Conclusion The MPSS data presented here provide a quantitative view of the transcriptome and its regulation in these unusual single-celled eukaryotes. The observed signature abundance and distribution in Alexandrium is similar to that of other eukaryotes that have been analyzed using MPSS. Results of signature mapping via RACE indicate that many signatures result from sequence variants of individual genes. These data add to the growing body of evidence for widespread gene

Epidemiology of massive transfusion

DEFF Research Database (Denmark)

Halmin, M A; Chiesa, F; Vasan, S K

2015-01-01

and to describe characteristics and mortality of massively transfused patients. Methods: We performed a retrospective cohort study based on the Scandinavian Donations and Transfusions (SCANDAT2) database, linking data on blood donation, blood components and transfused patients with inpatient- and population.......4% among women transfused for obstetrical bleeding. Mortality increased gradually with age and among all patients massively transfused at age 80 years, only 26% were alive [TABLE PRESENTED] after 5 years. The relative mortality, early after transfusion, was high and decreased with time since transfusion...

Pyrosequencing of prey DNA in reptile faeces: analysis of earthworm consumption by slow worms.

Science.gov (United States)

Brown, David S; Jarman, Simon N; Symondson, William O C

2012-03-01

Little quantitative ecological information exists on the diets of most invertebrate feeding reptiles, particularly nocturnal or elusive species that are difficult to observe. In the UK and elsewhere, reptiles are legally required to be relocated before land development can proceed, but without knowledge of their dietary requirements, the suitability of receptor sites cannot be known. Here, we tested the ability of non-invasive DNA-based molecular diagnostics (454 pyrosequencing) to analyse reptile diets, with the specific aims of determining which earthworm species are exploited by slow worms (the legless lizard Anguis fragilis) and whether they feed on the deeper-living earthworm species that only come to the surface at night. Slow worm faecal samples from four different habitats were analysed using earthworm-specific PCR primers. We found that 86% of slow worms (N=80) had eaten earthworms. In lowland heath and marshy/acid grassland, Lumbricus rubellus, a surface-dwelling epigeic species, dominated slow worm diet. In two other habitats, riverside pasture and calciferous coarse grassland, diet was dominated by deeper-living anecic and endogeic species. We conclude that all species of earthworm are exploited by these reptiles and lack of specialization allows slow worms to thrive in a wide variety of habitats. Pyrosequencing of prey DNA in faeces showed promise as a practical, rapid and relatively inexpensive means of obtaining detailed and valuable ecological information on the diets of reptiles. © 2011 Blackwell Publishing Ltd.

Parallel algorithms and cluster computing

CERN Document Server

Hoffmann, Karl Heinz

2007-01-01

This book presents major advances in high performance computing as well as major advances due to high performance computing. It contains a collection of papers in which results achieved in the collaboration of scientists from computer science, mathematics, physics, and mechanical engineering are presented. From the science problems to the mathematical algorithms and on to the effective implementation of these algorithms on massively parallel and cluster computers we present state-of-the-art methods and technology as well as exemplary results in these fields. This book shows that problems which seem superficially distinct become intimately connected on a computational level.

Spatial segregation and aggregation of ectomycorrhizal and root-endophytic fungi in the seedlings of two Quercus species.

Directory of Open Access Journals (Sweden)

Satoshi Yamamoto

Full Text Available Diverse clades of mycorrhizal and endophytic fungi are potentially involved in competitive or facilitative interactions within host-plant roots. We investigated the potential consequences of these ecological interactions on the assembly process of root-associated fungi by examining the co-occurrence of pairs of fungi in host-plant individuals. Based on massively-parallel pyrosequencing, we analyzed the root-associated fungal community composition for each of the 249 Quercus serrata and 188 Quercus glauca seedlings sampled in a warm-temperate secondary forest in Japan. Pairs of fungi that co-occurred more or less often than expected by chance were identified based on randomization tests. The pyrosequencing analysis revealed that not only ectomycorrhizal fungi but also endophytic fungi were common in the root-associated fungal community. Intriguingly, specific pairs of these ectomycorrhizal and endophytic fungi showed spatially aggregated patterns, suggesting the existence of facilitative interactions between fungi in different functional groups. Due to the large number of fungal pairs examined, many of the observed aggregated/segregated patterns with very low P values (e.g., < 0.005 turned non-significant after the application of a multiple comparison method. However, our overall results imply that the community structures of ectomycorrhizal and endophytic fungi could influence each other through interspecific competitive/facilitative interactions in root. To test the potential of host-plants' control of fungus-fungus ecological interactions in roots, we further examined whether the aggregated/segregated patterns could vary depending on the identity of host plant species. Potentially due to the physiological properties shared between the congeneric host plant species, the sign of hosts' control was not detected in the present study. The pyrosequencing-based randomization analyses shown in this study provide a platform of the high

Parallel keyed hash function construction based on chaotic maps

International Nuclear Information System (INIS)

Xiao Di; Liao Xiaofeng; Deng Shaojiang

2008-01-01

Recently, a variety of chaos-based hash functions have been proposed. Nevertheless, none of them works efficiently in parallel computing environment. In this Letter, an algorithm for parallel keyed hash function construction is proposed, whose structure can ensure the uniform sensitivity of hash value to the message. By means of the mechanism of both changeable-parameter and self-synchronization, the keystream establishes a close relation with the algorithm key, the content and the order of each message block. The entire message is modulated into the chaotic iteration orbit, and the coarse-graining trajectory is extracted as the hash value. Theoretical analysis and computer simulation indicate that the proposed algorithm can satisfy the performance requirements of hash function. It is simple, efficient, practicable, and reliable. These properties make it a good choice for hash on parallel computing platform

Using Load Balancing to Scalably Parallelize Sampling-Based Motion Planning Algorithms

KAUST Repository

Fidel, Adam; Jacobs, Sam Ade; Sharma, Shishir; Amato, Nancy M.; Rauchwerger, Lawrence