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.

Template based parallel checkpointing in a massively parallel computer system

Science.gov (United States)

Archer, Charles Jens [Rochester, MN; Inglett, Todd Alan [Rochester, MN

2009-01-13

A method and apparatus for a template based parallel checkpoint save for a massively parallel super computer system using a parallel variation of the rsync protocol, and network broadcast. In preferred embodiments, the checkpoint data for each node is compared to a template checkpoint file that resides in the storage and that was previously produced. Embodiments herein greatly decrease the amount of data that must be transmitted and stored for faster checkpointing and increased efficiency of the computer system. Embodiments are directed to a parallel computer system with nodes arranged in a cluster with a high speed interconnect that can perform broadcast communication. The checkpoint contains a set of actual small data blocks with their corresponding checksums from all nodes in the system. The data blocks may be compressed using conventional non-lossy data compression algorithms to further reduce the overall checkpoint size.

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

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

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 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.

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.

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

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.

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

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 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

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.

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.

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.

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

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....

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...

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.

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.

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.

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

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%.

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.

A massively-parallel electronic-structure calculations based on real-space density functional theory

International Nuclear Information System (INIS)

Iwata, Jun-Ichi; Takahashi, Daisuke; Oshiyama, Atsushi; Boku, Taisuke; Shiraishi, Kenji; Okada, Susumu; Yabana, Kazuhiro

2010-01-01

Based on the real-space finite-difference method, we have developed a first-principles density functional program that efficiently performs large-scale calculations on massively-parallel computers. In addition to efficient parallel implementation, we also implemented several computational improvements, substantially reducing the computational costs of O(N 3 ) operations such as the Gram-Schmidt procedure and subspace diagonalization. Using the program on a massively-parallel computer cluster with a theoretical peak performance of several TFLOPS, we perform electronic-structure calculations for a system consisting of over 10,000 Si atoms, and obtain a self-consistent electronic-structure in a few hundred hours. We analyze in detail the costs of the program in terms of computation and of inter-node communications to clarify the efficiency, the applicability, and the possibility for further improvements.

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.

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

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.

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.)

Engineering-Based Thermal CFD Simulations on Massive Parallel Systems

KAUST Repository

Frisch, Jérôme

2015-05-22

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 with several thousands to millions of cores. In this paper, we present a hierarchical data structure for massive parallel computations that supports the coupling of a Navier–Stokes-based fluid flow code with the Boussinesq approximation in order to address complex thermal scenarios for energy-related assessments. The newly designed data structure is specifically designed with the idea of interactive data exploration and visualization during runtime of the simulation code; a major shortcoming of traditional high-performance computing (HPC) simulation codes. We further show and discuss speed-up values obtained on one of Germany’s top-ranked supercomputers with up to 140,000 processes and present simulation results for different engineering-based thermal problems.

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.)

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

Design and implementation of an integrated architecture for massive parallel data treatment of analogue signals supplied by silicon detectors of very high spatial resolution

International Nuclear Information System (INIS)

Michel, J.

1993-02-01

This doctorate thesis studies an integrated architecture designed to a parallel massive treatment of analogue signals supplied by silicon detectors of very high spatial resolution. The first chapter is an introduction presenting the general outline and the triggering conditions of the spectrometer. Chapter two describes the operational structure of a microvertex detector made of Si micro-plates associated to the measuring chains. Information preconditioning is related to the pre-amplification stage, to the pile-up effects and to the reduction in the time characteristic due to the high counting rates. The chapter three describes the architecture of the analogue delay buffer, makes an analysis of the intrinsic noise and presents the operational testings and input/output control operations. The fourth chapter is devoted to the description of the analogue pulse shape processor and gives also the testings and the corresponding measurements on the circuit. Finally, the chapter five deals with the simplest modeling of the entire conditioning chain. Also, the testings and measuring procedures are here discussed. In conclusion the author presents some prospects for improving the signal-to-noise ratio by summation of the de-convoluted micro-paths. 78 refs., 78 figs., 1 annexe

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.

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

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.

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

Advanced optical signal processing of broadband parallel data signals

DEFF Research Database (Denmark)

Oxenløwe, Leif Katsuo; Hu, Hao; Kjøller, Niels-Kristian

2016-01-01

Optical signal processing may aid in reducing the number of active components in communication systems with many parallel channels, by e.g. using telescopic time lens arrangements to perform format conversion and allow for WDM regeneration.......Optical signal processing may aid in reducing the number of active components in communication systems with many parallel channels, by e.g. using telescopic time lens arrangements to perform format conversion and allow for WDM regeneration....

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.)

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 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.

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

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.

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.

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.

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)

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.

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

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.

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.

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...

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

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.

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.

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 ...

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.

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 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.

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...

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

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

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)

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.

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.

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.

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.

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

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.

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).

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...

The study of image processing of parallel digital signal processor

International Nuclear Information System (INIS)

Liu Jie

2000-01-01

The author analyzes the basic characteristic of parallel DSP (digital signal processor) TMS320C80 and proposes related optimized image algorithm and the parallel processing method based on parallel DSP. The realtime for many image processing can be achieved in this way

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.

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

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....

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.

Massively Parallel Signal Processing using the Graphics Processing Unit for Real-Time Brain-Computer Interface Feature Extraction.

Science.gov (United States)

Wilson, J Adam; Williams, Justin C

2009-01-01

The clock speeds of modern computer processors have nearly plateaued in the past 5 years. Consequently, neural prosthetic systems that rely on processing large quantities of data in a short period of time face a bottleneck, in that it may not be possible to process all of the data recorded from an electrode array with high channel counts and bandwidth, such as electrocorticographic grids or other implantable systems. Therefore, in this study a method of using the processing capabilities of a graphics card [graphics processing unit (GPU)] was developed for real-time neural signal processing of a brain-computer interface (BCI). The NVIDIA CUDA system was used to offload processing to the GPU, which is capable of running many operations in parallel, potentially greatly increasing the speed of existing algorithms. The BCI system records many channels of data, which are processed and translated into a control signal, such as the movement of a computer cursor. This signal processing chain involves computing a matrix-matrix multiplication (i.e., a spatial filter), followed by calculating the power spectral density on every channel using an auto-regressive method, and finally classifying appropriate features for control. In this study, the first two computationally intensive steps were implemented on the GPU, and the speed was compared to both the current implementation and a central processing unit-based implementation that uses multi-threading. Significant performance gains were obtained with GPU processing: the current implementation processed 1000 channels of 250 ms in 933 ms, while the new GPU method took only 27 ms, an improvement of nearly 35 times.

Massively parallel signal processing using the graphics processing unit for real-time brain-computer interface feature extraction

Directory of Open Access Journals (Sweden)

J. Adam Wilson

2009-07-01

Full Text Available The clock speeds of modern computer processors have nearly plateaued in the past five years. Consequently, neural prosthetic systems that rely on processing large quantities of data in a short period of time face a bottleneck, in that it may not be possible to process all of the data recorded from an electrode array with high channel counts and bandwidth, such as electrocorticographic grids or other implantable systems. Therefore, in this study a method of using the processing capabilities of a graphics card (GPU was developed for real-time neural signal processing of a brain-computer interface (BCI. The NVIDIA CUDA system was used to offload processing to the GPU, which is capable of running many operations in parallel, potentially greatly increasing the speed of existing algorithms. The BCI system records many channels of data, which are processed and translated into a control signal, such as the movement of a computer cursor. This signal processing chain involves computing a matrix-matrix multiplication (i.e., a spatial filter, followed by calculating the power spectral density on every channel using an auto-regressive method, and finally classifying appropriate features for control. In this study, the first two computationally-intensive steps were implemented on the GPU, and the speed was compared to both the current implementation and a CPU-based implementation that uses multi-threading. Significant performance gains were obtained with GPU processing: the current implementation processed 1000 channels in 933 ms, while the new GPU method took only 27 ms, an improvement of nearly 35 times.

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.

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.

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

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

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.

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...

Characterization of Harmonic Signal Acquisition with Parallel Dipole and Multipole Detectors

Science.gov (United States)

Park, Sung-Gun; Anderson, Gordon A.; Bruce, James E.

2018-04-01

Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) is a powerful instrument for the study of complex biological samples due to its high resolution and mass measurement accuracy. However, the relatively long signal acquisition periods needed to achieve high resolution can serve to limit applications of FTICR-MS. The use of multiple pairs of detector electrodes enables detection of harmonic frequencies present at integer multiples of the fundamental cyclotron frequency, and the obtained resolving power for a given acquisition period increases linearly with the order of harmonic signal. However, harmonic signal detection also increases spectral complexity and presents challenges for interpretation. In the present work, ICR cells with independent dipole and harmonic detection electrodes and preamplifiers are demonstrated. A benefit of this approach is the ability to independently acquire fundamental and multiple harmonic signals in parallel using the same ions under identical conditions, enabling direct comparison of achieved performance as parameters are varied. Spectra from harmonic signals showed generally higher resolving power than spectra acquired with fundamental signals and equal signal duration. In addition, the maximum observed signal to noise (S/N) ratio from harmonic signals exceeded that of fundamental signals by 50 to 100%. Finally, parallel detection of fundamental and harmonic signals enables deconvolution of overlapping harmonic signals since observed fundamental frequencies can be used to unambiguously calculate all possible harmonic frequencies. Thus, the present application of parallel fundamental and harmonic signal acquisition offers a general approach to improve utilization of harmonic signals to yield high-resolution spectra with decreased acquisition time. [Figure not available: see fulltext.

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...

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.

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.

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.

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)

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.

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

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.

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.

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.

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.

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)

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...

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

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

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.

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

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.

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.

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

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.

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.

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

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.

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.

Signal-to-noise ratio measurement in parallel MRI with subtraction mapping and consecutive methods

International Nuclear Information System (INIS)

Imai, Hiroshi; Miyati, Tosiaki; Ogura, Akio; Doi, Tsukasa; Tsuchihashi, Toshio; Machida, Yoshio; Kobayashi, Masato; Shimizu, Kouzou; Kitou, Yoshihiro

2008-01-01

When measuring the signal-to-noise ratio (SNR) of an image the used parallel magnetic resonance imaging, it was confirmed that there was a problem in the application of past SNR measurement. With the method of measuring the noise from the background signal, SNR with parallel imaging was higher than that without parallel imaging. In the subtraction method (NEMA standard), which sets a wide region of interest, the white noise was not evaluated correctly although SNR was close to the theoretical value. We proposed two techniques because SNR in parallel imaging was not uniform according to inhomogeneity of the coil sensitivity distribution and geometry factor. Using the first method (subtraction mapping), two images were scanned with identical parameters. The SNR in each pixel divided the running mean (7 by 7 pixels in neighborhood) by standard deviation/√2 in the same region of interest. Using the second (consecutive) method, more than fifty consecutive scans of the uniform phantom were obtained with identical scan parameters. Then the SNR was calculated from the ratio of mean signal intensity to the standard deviation in each pixel on a series of images. Moreover, geometry factors were calculated from SNRs with and without parallel imaging. The SNR and geometry factor using parallel imaging in the subtraction mapping method agreed with those of the consecutive method. Both methods make it possible to obtain a more detailed determination of SNR in parallel imaging and to calculate the geometry factor. (author)

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

Characterization of the Zoarces viviparus liver transcriptome using massively parallel pyrosequencing

Directory of Open Access Journals (Sweden)

Asker Noomi

2009-07-01

Full Text Available Abstract Background The teleost Zoarces viviparus (eelpout lives along the coasts of Northern Europe and has long been an established model organism for marine ecology and environmental monitoring. The scarce information about this species genome has however restrained the use of efficient molecular-level assays, such as gene expression microarrays. Results In the present study we present the first comprehensive characterization of the Zoarces viviparus liver transcriptome. From 400,000 reads generated by massively parallel pyrosequencing, more than 50,000 pieces of putative transcripts were assembled, annotated and functionally classified. The data was estimated to cover roughly 40% of the total transcriptome and homologues for about half of the genes of Gasterosteus aculeatus (stickleback were identified. The sequence data was consequently used to design an oligonucleotide microarray for large-scale gene expression analysis. Conclusion Our results show that one run using a Genome Sequencer FLX from 454 Life Science/Roche generates enough genomic information for adequate de novo assembly of a large number of genes in a higher vertebrate. The generated sequence data, including the validated microarray probes, are publicly available to promote genome-wide research in Zoarces viviparus.

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

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.

Real-time Nyquist signaling with dynamic precision and flexible non-integer oversampling.

Science.gov (United States)

Schmogrow, R; Meyer, M; Schindler, P C; Nebendahl, B; Dreschmann, M; Meyer, J; Josten, A; Hillerkuss, D; Ben-Ezra, S; Becker, J; Koos, C; Freude, W; Leuthold, J

2014-01-13

We demonstrate two efficient processing techniques for Nyquist signals, namely computation of signals using dynamic precision as well as arbitrary rational oversampling factors. With these techniques along with massively parallel processing it becomes possible to generate and receive high data rate Nyquist signals with flexible symbol rates and bandwidths, a feature which is highly desirable for novel flexgrid networks. We achieved maximum bit rates of 252 Gbit/s in real-time.

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...

Multichannel microformulators for massively parallel machine learning and automated design of biological experiments

Science.gov (United States)

Wikswo, John; Kolli, Aditya; Shankaran, Harish; Wagoner, Matthew; Mettetal, Jerome; Reiserer, Ronald; Gerken, Gregory; Britt, Clayton; Schaffer, David

Genetic, proteomic, and metabolic networks describing biological signaling can have 102 to 103 nodes. Transcriptomics and mass spectrometry can quantify 104 different dynamical experimental variables recorded from in vitro experiments with a time resolution approaching 1 s. It is difficult to infer metabolic and signaling models from such massive data sets, and it is unlikely that causality can be determined simply from observed temporal correlations. There is a need to design and apply specific system perturbations, which will be difficult to perform manually with 10 to 102 externally controlled variables. Machine learning and optimal experimental design can select an experiment that best discriminates between multiple conflicting models, but a remaining problem is to control in real time multiple variables in the form of concentrations of growth factors, toxins, nutrients and other signaling molecules. With time-division multiplexing, a microfluidic MicroFormulator (μF) can create in real time complex mixtures of reagents in volumes suitable for biological experiments. Initial 96-channel μF implementations control the exposure profile of cells in a 96-well plate to different temporal profiles of drugs; future experiments will include challenge compounds. Funded in part by AstraZeneca, NIH/NCATS HHSN271201600009C and UH3TR000491, and VIIBRE.

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 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

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

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)

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.

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

Porting Gravitational Wave Signal Extraction to Parallel Virtual Machine (PVM)

Science.gov (United States)

Thirumalainambi, Rajkumar; Thompson, David E.; Redmon, Jeffery

2009-01-01

Laser Interferometer Space Antenna (LISA) is a planned NASA-ESA mission to be launched around 2012. The Gravitational Wave detection is fundamentally the determination of frequency, source parameters, and waveform amplitude derived in a specific order from the interferometric time-series of the rotating LISA spacecrafts. The LISA Science Team has developed a Mock LISA Data Challenge intended to promote the testing of complicated nested search algorithms to detect the 100-1 millihertz frequency signals at amplitudes of 10E-21. However, it has become clear that, sequential search of the parameters is very time consuming and ultra-sensitive; hence, a new strategy has been developed. Parallelization of existing sequential search algorithms of Gravitational Wave signal identification consists of decomposing sequential search loops, beginning with outermost loops and working inward. In this process, the main challenge is to detect interdependencies among loops and partitioning the loops so as to preserve concurrency. Existing parallel programs are based upon either shared memory or distributed memory paradigms. In PVM, master and node programs are used to execute parallelization and process spawning. The PVM can handle process management and process addressing schemes using a virtual machine configuration. The task scheduling and the messaging and signaling can be implemented efficiently for the LISA Gravitational Wave search process using a master and 6 nodes. This approach is accomplished using a server that is available at NASA Ames Research Center, and has been dedicated to the LISA Data Challenge Competition. Historically, gravitational wave and source identification parameters have taken around 7 days in this dedicated single thread Linux based server. Using PVM approach, the parameter extraction problem can be reduced to within a day. The low frequency computation and a proxy signal-to-noise ratio are calculated in separate nodes that are controlled by the master

A Parallel Framework with Block Matrices of a Discrete Fourier Transform for Vector-Valued Discrete-Time Signals

Directory of Open Access Journals (Sweden)

Pablo Soto-Quiros

2015-01-01

Full Text Available This paper presents a parallel implementation of a kind of discrete Fourier transform (DFT: the vector-valued DFT. The vector-valued DFT is a novel tool to analyze the spectra of vector-valued discrete-time signals. This parallel implementation is developed in terms of a mathematical framework with a set of block matrix operations. These block matrix operations contribute to analysis, design, and implementation of parallel algorithms in multicore processors. In this work, an implementation and experimental investigation of the mathematical framework are performed using MATLAB with the Parallel Computing Toolbox. We found that there is advantage to use multicore processors and a parallel computing environment to minimize the high execution time. Additionally, speedup increases when the number of logical processors and length of the signal increase.

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

Correlation analysis of respiratory signals by using parallel coordinate plots.

Science.gov (United States)

Saatci, Esra

2018-01-01

The understanding of the bonds and the relationships between the respiratory signals, i.e. the airflow, the mouth pressure, the relative temperature and the relative humidity during breathing may provide the improvement on the measurement methods of respiratory mechanics and sensor designs or the exploration of the several possible applications in the analysis of respiratory disorders. Therefore, the main objective of this study was to propose a new combination of methods in order to determine the relationship between respiratory signals as a multidimensional data. In order to reveal the coupling between the processes two very different methods were used: the well-known statistical correlation analysis (i.e. Pearson's correlation and cross-correlation coefficient) and parallel coordinate plots (PCPs). Curve bundling with the number intersections for the correlation analysis, Least Mean Square Time Delay Estimator (LMS-TDE) for the point delay detection and visual metrics for the recognition of the visual structures were proposed and utilized in PCP. The number of intersections was increased when the correlation coefficient changed from high positive to high negative correlation between the respiratory signals, especially if whole breath was processed. LMS-TDE coefficients plotted in PCP indicated well-matched point delay results to the findings in the correlation analysis. Visual inspection of PCB by visual metrics showed range, dispersions, entropy comparisons and linear and sinusoidal-like relationships between the respiratory signals. It is demonstrated that the basic correlation analysis together with the parallel coordinate plots perceptually motivates the visual metrics in the display and thus can be considered as an aid to the user analysis by providing meaningful views of the data. Copyright © 2017 Elsevier B.V. All rights reserved.

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

OpenAIRE

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.

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. Remedi...

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.

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

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

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

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

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.

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.

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

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).

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...

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.

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.

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.

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.

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.

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.

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

Directory of Open Access Journals (Sweden)

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)

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

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.

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)

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.

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...

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

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.

Practical tools to implement massive parallel pyrosequencing of PCR products in next generation molecular diagnostics.

Directory of Open Access Journals (Sweden)

Kim De Leeneer

Full Text Available Despite improvements in terms of sequence quality and price per basepair, Sanger sequencing remains restricted to screening of individual disease genes. The development of massively parallel sequencing (MPS technologies heralded an era in which molecular diagnostics for multigenic disorders becomes reality. Here, we outline different PCR amplification based strategies for the screening of a multitude of genes in a patient cohort. We performed a thorough evaluation in terms of set-up, coverage and sequencing variants on the data of 10 GS-FLX experiments (over 200 patients. Crucially, we determined the actual coverage that is required for reliable diagnostic results using MPS, and provide a tool to calculate the number of patients that can be screened in a single run. Finally, we provide an overview of factors contributing to false negative or false positive mutation calls and suggest ways to maximize sensitivity and specificity, both important in a routine setting. By describing practical strategies for screening of multigenic disorders in a multitude of samples and providing answers to questions about minimum required coverage, the number of patients that can be screened in a single run and the factors that may affect sensitivity and specificity we hope to facilitate the implementation of MPS technology in molecular diagnostics.

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.

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)

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

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.

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

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.

Apparatus for tomography in which signal profiles gathered from divergent radiation can be reconstructed in signal profiles, each corresponding with a beam of parallel rays

International Nuclear Information System (INIS)

1976-01-01

A tomograph which is capable of gathering divergent radiations and reconstruct them in signal profiles or images each corresponding with a beam of parallel rays is discussed which may eliminate the interfering point dispersion function which normally occurs

My-Forensic-Loci-queries (MyFLq) framework for analysis of forensic STR data generated by massive parallel sequencing.

Science.gov (United States)

Van Neste, Christophe; Vandewoestyne, Mado; Van Criekinge, Wim; Deforce, Dieter; Van Nieuwerburgh, Filip

2014-03-01

Forensic scientists are currently investigating how to transition from capillary electrophoresis (CE) to massive parallel sequencing (MPS) for analysis of forensic DNA profiles. MPS offers several advantages over CE such as virtually unlimited multiplexy of loci, combining both short tandem repeat (STR) and single nucleotide polymorphism (SNP) loci, small amplicons without constraints of size separation, more discrimination power, deep mixture resolution and sample multiplexing. We present our bioinformatic framework My-Forensic-Loci-queries (MyFLq) for analysis of MPS forensic data. For allele calling, the framework uses a MySQL reference allele database with automatically determined regions of interest (ROIs) by a generic maximal flanking algorithm which makes it possible to use any STR or SNP forensic locus. Python scripts were designed to automatically make allele calls starting from raw MPS data. We also present a method to assess the usefulness and overall performance of a forensic locus with respect to MPS, as well as methods to estimate whether an unknown allele, which sequence is not present in the MySQL database, is in fact a new allele or a sequencing error. The MyFLq framework was applied to an Illumina MiSeq dataset of a forensic Illumina amplicon library, generated from multilocus STR polymerase chain reaction (PCR) on both single contributor samples and multiple person DNA mixtures. Although the multilocus PCR was not yet optimized for MPS in terms of amplicon length or locus selection, the results show excellent results for most loci. The results show a high signal-to-noise ratio, correct allele calls, and a low limit of detection for minor DNA contributors in mixed DNA samples. Technically, forensic MPS affords great promise for routine implementation in forensic genomics. The method is also applicable to adjacent disciplines such as molecular autopsy in legal medicine and in mitochondrial DNA research. Copyright © 2013 The Authors. Published by

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 Array Bistable Stochastic Resonance System with Independent Input and Its Signal-to-Noise Ratio Improvement

Directory of Open Access Journals (Sweden)

Wei Li

2014-01-01

with independent components and averaged output; second, we give a deduction of the output signal-to-noise ratio (SNR for this system to show the performance. Our examples show the enhancement of the system and how different parameters influence the performance of the proposed parallel array.

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.

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.

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....

M2M massive wireless access

DEFF Research Database (Denmark)

Zanella, Andrea; Zorzi, Michele; Santos, André F.

2013-01-01

In order to make the Internet of Things a reality, ubiquitous coverage and low-complexity connectivity are required. Cellular networks are hence the most straightforward and realistic solution to enable a massive deployment of always connected Machines around the globe. Nevertheless, a paradigm...... shift in the conception and design of future cellular networks is called for. Massive access attempts, low-complexity and cheap machines, sporadic transmission and correlated signals are among the main properties of this new reality, whose main consequence is the disruption of the development...... Access Reservation, Coded Random Access and the exploitation of multiuser detection in random access. Additionally, we will show how the properties of machine originated signals, such as sparsity and spatial/time correlation can be exploited. The end goal of this paper is to provide motivation...

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.

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

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

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

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.

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.

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

Distributed system for parallel data processing of ECT signals for electromagnetic flaw detection in materials

International Nuclear Information System (INIS)

Guliashki, Vassil; Marinova, Galia

2002-01-01

The paper proposes a distributed system for parallel data processing of ECT signals for flaw detection in materials. The measured data are stored in files on a host computer, where a JAVA server is located. The host computer is connected through Internet to a set of client computers, distributed geographically. The data are distributed from the host computer by means of the JAVA server to the client computers according their requests. The software necessary for the data processing is installed on each client computer in advance. The organization of the data processing on many computers, working simultaneously in parallel, leads to great time reducing, especially in cases when huge amount of data should be processed in very short time. (Author)

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.

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

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.

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)

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

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.

The Application of Paired Parallel Filters for Ultra-Wideband Signal Processing

Directory of Open Access Journals (Sweden)

S. L. Chernyshev

2015-01-01

Full Text Available The paper considers a unit in which the parallel filters on regular lines are pair-attached. This connection allows to reduce a side line impedance at the point of connection. At the same time these lines become narrow, and the possibility to excite higher modes in the joint reduces.Consider the scattering matrix of four identical lines connection. Then find the scattering matrix of connection in which two side lines are connected with filters. Particular cases of the reflection coefficients of different filters are considered. It is shown that only in the case of identical filters there remained a linear relationship between the input filter coefficients of reflection and transmission coefficient of the unit. It facilitates the solution of the problem of synthesis. Restrictions on the transfer coefficient are found. In transition to the time domain impulse response of connection under consideration and the expression for the synthesis were defined. The paper considers an example of implementation of the matched filtering in this connection. In this case, the output signal is a half-sum of the input signal and their autocorrelation function.

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

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

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

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.

Signal enhancement due to high-Z nanofilm electrodes in parallel plate ionization chambers with variable microgaps.

Science.gov (United States)

Brivio, Davide; Sajo, Erno; Zygmanski, Piotr

2017-12-01

We developed a method for measuring signal enhancement produced by high-Z nanofilm electrodes in parallel plate ionization chambers with variable thickness microgaps. We used a laboratory-made variable gap parallel plate ionization chamber with nanofilm electrodes made of aluminum-aluminum (Al-Al) and aluminum-tantalum (Al-Ta). The electrodes were evaporated on 1 mm thick glass substrates. The interelectrode air gap was varied from 3 μm to 1 cm. The gap size was measured using a digital micrometer and it was confirmed by capacitance measurements. The electric field in the chamber was kept between 0.1 kV/cm and 1 kV/cm for all the gap sizes by applying appropriate compensating voltages. The chamber was exposed to 120 kVp X-rays. The current was measured using a commercial data acquisition system with temporal resolution of 600 Hz. In addition, radiation transport simulations were carried out to characterize the dose, D(x), high-energy electron current, J(x), and deposited charge, Q(x), as a function of distance, x, from the electrodes. A deterministic method was selected over Monte Carlo due to its ability to produce results with 10 nm spatial resolution without stochastic uncertainties. Experimental signal enhancement ratio, SER(G) which we defined as the ratio of signal for Al-air-Ta to signal for Al-air-Al for each gap size, was compared to computations. The individual contributions of dose, electron current, and charge deposition to the signal enhancement were determined. Experimental signals matched computed data for all gap sizes after accounting for several contributions to the signal: (a) charge carrier generated via ionization due to the energy deposited in the air gap, D(x); (b) high-energy electron current, J(x), leaking from high-Z electrode (Ta) toward low-Z electrode (Al); (c) deposited charge in the air gap, Q(x); and (d) the decreased collection efficiency for large gaps (>~500 μm). Q(x) accounts for the electrons below 100 eV, which are

Static Mapping of Functional Programs: An Example in Signal Processing

Directory of Open Access Journals (Sweden)

Jack B. Dennis

1996-01-01

Full Text Available Complex signal-processing problems are naturally described by compositions of program modules that process streams of data. In this article we discuss how such compositions may be analyzed and mapped onto multiprocessor computers to effectively exploit the massive parallelism of these applications. The methods are illustrated with an example of signal processing for an optical surveillance problem. Program transformation and analysis are used to construct a program description tree that represents the given computation as an acyclic interconnection of stream-processing modules. Each module may be mapped to a set of threads run on a group of processing elements of a target multiprocessor. Performance is considered for two forms of multiprocessor architecture, one based on conventional DSP technology and the other on a multithreaded-processing element design.

Gaussian Pulse-Based Two-Threshold Parallel Scaling Tone Reservation for PAPR Reduction of OFDM Signals

Directory of Open Access Journals (Sweden)

Lei Guan

2011-01-01

Full Text Available Tone Reservation (TR is a technique proposed to combat the high Peak-to-Average Power Ratio (PAPR problem of Orthogonal Frequency Division Multiplexing (OFDM signals. However conventional TR suffers from high computational cost due to the difficulties in finding an effective cancellation signal in the time domain by using only a few tones in the frequency domain. It also suffers from a high cost of hardware implementation and long handling time delay issues due to the need to conduct multiple iterations to cancel multiple high signal peaks. In this paper, we propose an efficient approach, called two-threshold parallel scaling, for implementing a previously proposed Gaussian pulse-based Tone Reservation algorithm. Compared to conventional approaches, this technique significantly reduces the hardware implementation complexity and cost, while also reducing signal processing time delay by using just two iterations. Experimental results show that the proposed technique can effectively reduce the PAPR of OFDM signals with only a very small number of reserved tones and with limited usage of hardware resources. This technique is suitable for any OFDM-based communication systems, especially for Digital Video Broadcasting (DVB systems employing large IFFT/FFT transforms.

Modeling borehole microseismic and strain signals measured by a distributed fiber optic sensor

Science.gov (United States)

Mellors, R. J.; Sherman, C. S.; Ryerson, F. J.; Morris, J.; Allen, G. S.; Messerly, M. J.; Carr, T.; Kavousi, P.

2017-12-01

The advent of distributed fiber optic sensors installed in boreholes provides a new and data-rich perspective on the subsurface environment. This includes the long-term capability for vertical seismic profiles, monitoring of active borehole processes such as well stimulation, and measuring of microseismic signals. The distributed fiber sensor, which measures strain (or strain-rate), is an active sensor with highest sensitivity parallel to the fiber and subject to varying types of noise, both external and internal. We take a systems approach and include the response of the electronics, fiber/cable, and subsurface to improve interpretation of the signals. This aids in understanding noise sources, assessing error bounds on amplitudes, and developing appropriate algorithms for improving the image. Ultimately, a robust understanding will allow identification of areas for future improvement and possible optimization in fiber and cable design. The subsurface signals are simulated in two ways: 1) a massively parallel multi-physics code that is capable of modeling hydraulic stimulation of heterogeneous reservoir with a pre-existing discrete fracture network, and 2) a parallelized 3D finite difference code for high-frequency seismic signals. Geometry and parameters for the simulations are derived from fiber deployments, including the Marcellus Shale Energy and Environment Laboratory (MSEEL) project in West Virginia. The combination mimics both the low-frequency strain signals generated during the fracture process and high-frequency signals from microseismic and perforation shots. Results are compared with available fiber data and demonstrate that quantitative interpretation of the fiber data provides valuable constraints on the fracture geometry and microseismic activity. These constraints appear difficult, if not impossible, to obtain otherwise.

Comprehensive quantification of signal-to-noise ratio and g-factor for image-based and k-space-based parallel imaging reconstructions.

Science.gov (United States)

Robson, Philip M; Grant, Aaron K; Madhuranthakam, Ananth J; Lattanzi, Riccardo; Sodickson, Daniel K; McKenzie, Charles A

2008-10-01

Parallel imaging reconstructions result in spatially varying noise amplification characterized by the g-factor, precluding conventional measurements of noise from the final image. A simple Monte Carlo based method is proposed for all linear image reconstruction algorithms, which allows measurement of signal-to-noise ratio and g-factor and is demonstrated for SENSE and GRAPPA reconstructions for accelerated acquisitions that have not previously been amenable to such assessment. Only a simple "prescan" measurement of noise amplitude and correlation in the phased-array receiver, and a single accelerated image acquisition are required, allowing robust assessment of signal-to-noise ratio and g-factor. The "pseudo multiple replica" method has been rigorously validated in phantoms and in vivo, showing excellent agreement with true multiple replica and analytical methods. This method is universally applicable to the parallel imaging reconstruction techniques used in clinical applications and will allow pixel-by-pixel image noise measurements for all parallel imaging strategies, allowing quantitative comparison between arbitrary k-space trajectories, image reconstruction, or noise conditioning techniques. (c) 2008 Wiley-Liss, Inc.

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.

Efficient Sphere Detector Algorithm for Massive MIMO using GPU Hardware Accelerator

KAUST Repository

Arfaoui, Mohamed-Amine

2016-06-01

To further enhance the capacity of next generation wireless communication systems, massive MIMO has recently appeared as a necessary enabling technology to achieve high performance signal processing for large-scale multiple antennas. However, massive MIMO systems inevitably generate signal processing overheads, which translate into ever-increasing rate of complexity, and therefore, such system may not maintain the inherent real-time requirement of wireless systems. We redesign the non-linear sphere decoder method to increase the performance of the system, cast most memory-bound computations into compute-bound operations to reduce the overall complexity, and maintain the real-time processing thanks to the GPU computational power. We show a comprehensive complexity and performance analysis on an unprecedented MIMO system scale, which can ease the design phase toward simulating future massive MIMO wireless systems.

Efficient Sphere Detector Algorithm for Massive MIMO using GPU Hardware Accelerator

KAUST Repository

Arfaoui, Mohamed-Amine; Ltaief, Hatem; Rezki, Zouheir; Alouini, Mohamed-Slim; Keyes, David E.

2016-01-01

To further enhance the capacity of next generation wireless communication systems, massive MIMO has recently appeared as a necessary enabling technology to achieve high performance signal processing for large-scale multiple antennas. However, massive MIMO systems inevitably generate signal processing overheads, which translate into ever-increasing rate of complexity, and therefore, such system may not maintain the inherent real-time requirement of wireless systems. We redesign the non-linear sphere decoder method to increase the performance of the system, cast most memory-bound computations into compute-bound operations to reduce the overall complexity, and maintain the real-time processing thanks to the GPU computational power. We show a comprehensive complexity and performance analysis on an unprecedented MIMO system scale, which can ease the design phase toward simulating future massive MIMO wireless systems.

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

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.

Parallels between immune driven-hematopoiesis and T cell activation: 3 signals that relay inflammatory stress to the bone marrow

Energy Technology Data Exchange (ETDEWEB)

Libregts, Sten F.W.M.; Nolte, Martijn A., E-mail: m.nolte@sanquin.nl

2014-12-10

Quiescence, self-renewal, lineage commitment and differentiation of hematopoietic stem cells (HSCs) towards fully mature blood cells are a complex process that involves both intrinsic and extrinsic signals. During steady-state conditions, most hematopoietic signals are provided by various resident cells inside the bone marrow (BM), which establish the HSC micro-environment. However, upon infection, the hematopoietic process is also affected by pathogens and activated immune cells, which illustrates an effective feedback mechanism to hematopoietic stem and progenitor cells (HSPCs) via immune-mediated signals. Here, we review the impact of pathogen-associated molecular patterns (PAMPs), damage-associated molecular patterns (DAMPs), costimulatory molecules and pro-inflammatory cytokines on the quiescence, proliferation and differentiation of HSCs and more committed progenitors. As modulation of HSPC function via these immune-mediated signals holds an interesting parallel with the “three-signal-model” described for the activation and differentiation of naïve T-cells, we propose a novel “three-signal” concept for immune-driven hematopoiesis. In this model, the recognition of PAMPs and DAMPs will activate HSCs and induce proliferation, while costimulatory molecules and pro-inflammatory cytokines confer a second and third signal, respectively, which further regulate expansion, lineage commitment and differentiation of HSPCs. We review the impact of inflammatory stress on hematopoiesis along these three signals and we discuss whether they act independently from each other or that concurrence of these signals is important for an adequate response of HSPCs upon infection. - Highlights: • Inflammation and infection have a direct impact on hematopoiesis in the bone marrow. • We draw a striking parallel between immune-driven hematopoiesis and T cell activation. • We review how PAMPs and DAMPs, costimulation and cytokines influence HSPC function.

Parallels between immune driven-hematopoiesis and T cell activation: 3 signals that relay inflammatory stress to the bone marrow

International Nuclear Information System (INIS)

Libregts, Sten F.W.M.; Nolte, Martijn A.

2014-01-01

Quiescence, self-renewal, lineage commitment and differentiation of hematopoietic stem cells (HSCs) towards fully mature blood cells are a complex process that involves both intrinsic and extrinsic signals. During steady-state conditions, most hematopoietic signals are provided by various resident cells inside the bone marrow (BM), which establish the HSC micro-environment. However, upon infection, the hematopoietic process is also affected by pathogens and activated immune cells, which illustrates an effective feedback mechanism to hematopoietic stem and progenitor cells (HSPCs) via immune-mediated signals. Here, we review the impact of pathogen-associated molecular patterns (PAMPs), damage-associated molecular patterns (DAMPs), costimulatory molecules and pro-inflammatory cytokines on the quiescence, proliferation and differentiation of HSCs and more committed progenitors. As modulation of HSPC function via these immune-mediated signals holds an interesting parallel with the “three-signal-model” described for the activation and differentiation of naïve T-cells, we propose a novel “three-signal” concept for immune-driven hematopoiesis. In this model, the recognition of PAMPs and DAMPs will activate HSCs and induce proliferation, while costimulatory molecules and pro-inflammatory cytokines confer a second and third signal, respectively, which further regulate expansion, lineage commitment and differentiation of HSPCs. We review the impact of inflammatory stress on hematopoiesis along these three signals and we discuss whether they act independently from each other or that concurrence of these signals is important for an adequate response of HSPCs upon infection. - Highlights: • Inflammation and infection have a direct impact on hematopoiesis in the bone marrow. • We draw a striking parallel between immune-driven hematopoiesis and T cell activation. • We review how PAMPs and DAMPs, costimulation and cytokines influence HSPC function

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.

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

Multimodality imaging findings of massive ovarian edema in children

Energy Technology Data Exchange (ETDEWEB)

Dahmoush, Hisham [Stanford University Medical Center, Department of Radiology, Neuroradiology Division, Stanford, CA (United States); Anupindi, Sudha A.; Chauvin, Nancy A. [University of Pennsylvania, The Children' s Hospital of Philadelphia, Department of Radiology, Perelman School of Medicine, Philadelphia, PA (United States); Pawel, Bruce R. [University of Pennsylvania, The Children' s Hospital of Philadelphia, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, Philadelphia, PA (United States)

2017-05-15

Massive ovarian edema is a rare benign condition that predominantly affects childbearing women as well as preadolescent girls. It is thought to result from intermittent or partial torsion of the ovary compromising the venous and lymphatic drainage but with preserved arterial supply. The clinical features of massive ovarian edema are nonspecific and can simulate tumors, leading to unnecessary oophorectomy. To demonstrate imaging features that should alert radiologists to consider the diagnosis of massive ovarian edema preoperatively so that fertility-sparing surgery may be considered. We identified five girls diagnosed with massive ovarian edema at pathology. Presenting symptoms, sidedness, imaging appearance, preoperative diagnosis, and operative and histopathological findings were reviewed. Age range was 9.6-14.3 years (mean age: 12.5 years). Common imaging findings included ovarian enlargement with edema of the stroma, peripherally placed follicles, isointense signal on T1-W MRI and markedly hyperintense signal on T2-W MRI, preservation of color Doppler flow by US, and CT Hounsfield units below 40. The uterus was deviated to the affected side in all patients. Two of the five patients had small to moderate amounts of free pelvic fluid. Mean ovarian volume on imaging was 560 mL (range: 108-1,361 mL). While the clinical presentation of massive ovarian edema is nonspecific, an enlarged ovary with stromal edema, peripherally placed follicles and preservation of blood flow may be suggestive and wedge biopsy should be considered intraoperatively to avoid unnecessary removal of the ovary. (orig.)

Multimodality imaging findings of massive ovarian edema in children

International Nuclear Information System (INIS)

Dahmoush, Hisham; Anupindi, Sudha A.; Chauvin, Nancy A.; Pawel, Bruce R.

2017-01-01

Massive ovarian edema is a rare benign condition that predominantly affects childbearing women as well as preadolescent girls. It is thought to result from intermittent or partial torsion of the ovary compromising the venous and lymphatic drainage but with preserved arterial supply. The clinical features of massive ovarian edema are nonspecific and can simulate tumors, leading to unnecessary oophorectomy. To demonstrate imaging features that should alert radiologists to consider the diagnosis of massive ovarian edema preoperatively so that fertility-sparing surgery may be considered. We identified five girls diagnosed with massive ovarian edema at pathology. Presenting symptoms, sidedness, imaging appearance, preoperative diagnosis, and operative and histopathological findings were reviewed. Age range was 9.6-14.3 years (mean age: 12.5 years). Common imaging findings included ovarian enlargement with edema of the stroma, peripherally placed follicles, isointense signal on T1-W MRI and markedly hyperintense signal on T2-W MRI, preservation of color Doppler flow by US, and CT Hounsfield units below 40. The uterus was deviated to the affected side in all patients. Two of the five patients had small to moderate amounts of free pelvic fluid. Mean ovarian volume on imaging was 560 mL (range: 108-1,361 mL). While the clinical presentation of massive ovarian edema is nonspecific, an enlarged ovary with stromal edema, peripherally placed follicles and preservation of blood flow may be suggestive and wedge biopsy should be considered intraoperatively to avoid unnecessary removal of the ovary. (orig.)

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.

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

Search for strongly interacting massive particles using semiconductor detectors on the ground

International Nuclear Information System (INIS)

Derbin, A.V.; Egorov, A.I.; Bakhlanov, S.V.; Muratova, V.N.

1999-01-01

Using signals from recoil nucleus in semiconductor detectors, search for strongly interacting massive particles, as a possible candidate for dark matter, is continued. Experimental installation and the experimental results are given. New limits on the possible masses and cross sections of strongly interacting massive particles are presented [ru

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.

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.

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

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.

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.

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.

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.

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 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.

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.

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.

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.

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.

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.

A study on the achievable data rate in massive MIMO system

Science.gov (United States)

Salh, Adeeb; Audah, Lukman; Shah, Nor Shahida M.; Hamzah, Shipun A.

2017-09-01

The achievable high data rates depend on the ability of massive multi-input-multi-output (MIMO) for the fifth-generation (5G) cellular networks, where the massive MIMO systems can support very high energy and spectral efficiencies. A major challenge in mobile broadband networks is how to support the throughput in the future 5G, where the highlight of 5G expected to provide high speed internet for every user. The performance massive MIMO system increase with linear minimum mean square error (MMSE), zero forcing (ZF) and maximum ratio transmission (MRT) when the number of antennas increases to infinity, by deriving the closed-form approximation for achievable data rate expressions. Meanwhile, the high signal-to-noise ratio (SNR) can be mitigated by using MMSE, ZF and MRT, which are used to suppress the inter-cell interference signals between neighboring cells. The achievable sum rate for MMSE is improved based on the distributed users inside cell, mitigated the inter-cell interference caused when send the same signal by other cells. By contrast, MMSE is better than ZF in perfect channel state information (CSI) for approximately 20% of the achievable sum rate.

Effect of realistic astrophysical inputs on the phase and shape of the weakly interacting massive particles annual modulation signal

International Nuclear Information System (INIS)

Green, Anne M.

2003-01-01

The orbit of the Earth about the Sun produces an annual modulation in the weakly interacting massive particles (WIMP) direct detection rate. If the local WIMP velocity distribution is isotropic then the modulation is roughly sinusoidal with maximum in June; however, if the velocity distribution is anisotropic the phase and shape of the signal can change. Motivated by conflicting claims about the effect of uncertainties in the local velocity distribution on the interpretation of the DAMA annual modulation signal (and the possibility that the form of the modulation could be used to probe the structure of the Milky Way halo), we study the dependence of the annual modulation on various astrophysical inputs. We first examine the approximations used for the Earth's motion about the Sun and the Sun's velocity with respect to the Galactic rest frame. We find that overly simplistic assumptions lead to errors of up to ten days in the phase and up to tens of percent in the shape of the signal, even if the velocity distribution is isotropic. Crucially, if the components of the Earth's velocity perpendicular to the motion of the Sun are neglected, then the change in the phase which occurs for anisotropic velocity distributions is missed. We then examine how the annual modulation signal varies for physically and observationally well-motivated velocity distributions. We find that the phase of the signal changes by up to 20 days and the mean value and amplitude change by up to tens of percent

Gene discovery using massively parallel pyrosequencing to develop ESTs for the flesh fly Sarcophaga crassipalpis

Directory of Open Access Journals (Sweden)

Hahn Daniel A

2009-05-01

Full Text Available Abstract Background Flesh flies in the genus Sarcophaga are important models for investigating endocrinology, diapause, cold hardiness, reproduction, and immunity. Despite the prominence of Sarcophaga flesh flies as models for insect physiology and biochemistry, and in forensic studies, little genomic or transcriptomic data are available for members of this genus. We used massively parallel pyrosequencing on the Roche 454-FLX platform to produce a substantial EST dataset for the flesh fly Sarcophaga crassipalpis. To maximize sequence diversity, we pooled RNA extracted from whole bodies of all life stages and normalized the cDNA pool after reverse transcription. Results We obtained 207,110 ESTs with an average read length of 241 bp. These reads assembled into 20,995 contigs and 31,056 singletons. Using BLAST searches of the NR and NT databases we were able to identify 11,757 unique gene elements (ES. crassipalpis unigenes among GO Biological Process functional groups with that of the Drosophila melanogaster transcriptome suggests that our ESTs are broadly representative of the flesh fly transcriptome. Insertion and deletion errors in 454 sequencing present a serious hurdle to comparative transcriptome analysis. Aided by a new approach to correcting for these errors, we performed a comparative analysis of genetic divergence across GO categories among S. crassipalpis, D. melanogaster, and Anopheles gambiae. The results suggest that non-synonymous substitutions occur at similar rates across categories, although genes related to response to stimuli may evolve slightly faster. In addition, we identified over 500 potential microsatellite loci and more than 12,000 SNPs among our ESTs. Conclusion Our data provides the first large-scale EST-project for flesh flies, a much-needed resource for exploring this model species. In addition, we identified a large number of potential microsatellite and SNP markers that could be used in population and systematic

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.

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

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.

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.)

Parallel algorithms for online trackfinding at PANDA

Energy Technology Data Exchange (ETDEWEB)

Bianchi, Ludovico; Ritman, James; Stockmanns, Tobias [IKP, Forschungszentrum Juelich GmbH (Germany); Herten, Andreas [JSC, Forschungszentrum Juelich GmbH (Germany); Collaboration: PANDA-Collaboration

2016-07-01

The PANDA experiment, one of the four scientific pillars of the FAIR facility currently in construction in Darmstadt, is a next-generation particle detector that will study collisions of antiprotons with beam momenta of 1.5-15 GeV/c on a fixed proton target. Because of the broad physics scope and the similar signature of signal and background events, PANDA's strategy for data acquisition is to continuously record data from the whole detector and use this global information to perform online event reconstruction and filtering. A real-time rejection factor of up to 1000 must be achieved to match the incoming data rate for offline storage, making all components of the data processing system computationally very challenging. Online particle track identification and reconstruction is an essential step, since track information is used as input in all following phases. Online tracking algorithms must ensure a delicate balance between high tracking efficiency and quality, and minimal computational footprint. For this reason, a massively parallel solution exploiting multiple Graphic Processing Units (GPUs) is under investigation. The talk presents the core concepts of the algorithms being developed for primary trackfinding, along with details of their implementation on GPUs.

Two-Dimensional DOA Estimation Using Arbitrary Arrays for Massive MIMO Systems

Directory of Open Access Journals (Sweden)

Alban Doumtsop Lonkeng

2017-01-01

Full Text Available With the quick advancement of wireless communication networks, the need for massive multiple-input-multiple-output (MIMO to offer adequate network capacity has turned out to be apparent. As a portion of array signal processing, direction-of-arrival (DOA estimation is of indispensable significance to acquire directional data of sources and to empower the 3D beamforming. In this paper, the performance of DOA estimation for massive MIMO systems is analyzed and compared using a low-complexity algorithm. To be exact, the 2D Fourier domain line search (FDLS MUSIC algorithm is studied to mutually estimate elevation and azimuth angle, and arbitrary array geometry is utilized to represent massive MIMO systems. To avoid the computational burden in estimating the data covariance matrix and its eigenvalue decomposition (EVD due to the large-scale sensors involved in massive MIMO systems, the reduced-dimension data matrix is applied on the signals received by the array. The performance is examined and contrasted with the 2D MUSIC algorithm for different types of antenna configuration. Finally, the array resolution is selected to investigate the performance of elevation and azimuth estimation. The effectiveness and advantage of the proposed technique have been proven by detailed simulations for different types of MIMO array configuration.

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.

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...

Use of parallel counters for triggering

International Nuclear Information System (INIS)

Nikityuk, N.M.

1991-01-01

Results of investigation of using parallel counters, majority coincidence schemes, parallel compressors for triggering in multichannel high energy spectrometers are described. Concrete examples of methods of constructing fast and economic new devices used to determine multiplicity hits t>900 registered in a hodoscopic plane and a pixel detector are given. For this purpose the author uses the syndrome coding method and cellular arrays. In addition, an effective coding matrix has been created which can be used for light signal coding. For example, such signals are supplied from scintillators to photomultipliers. 23 refs.; 21 figs

Parallel algorithms for mapping pipelined and parallel computations

Science.gov (United States)

Nicol, David M.

1988-01-01

Many computational problems in image processing, signal processing, and scientific computing are naturally structured for either pipelined or parallel computation. When mapping such problems onto a parallel architecture it is often necessary to aggregate an obvious problem decomposition. Even in this context the general mapping problem is known to be computationally intractable, but recent advances have been made in identifying classes of problems and architectures for which optimal solutions can be found in polynomial time. Among these, the mapping of pipelined or parallel computations onto linear array, shared memory, and host-satellite systems figures prominently. This paper extends that work first by showing how to improve existing serial mapping algorithms. These improvements have significantly lower time and space complexities: in one case a published O(nm sup 3) time algorithm for mapping m modules onto n processors is reduced to an O(nm log m) time complexity, and its space requirements reduced from O(nm sup 2) to O(m). Run time complexity is further reduced with parallel mapping algorithms based on these improvements, which run on the architecture for which they create the mappings.

Global synchronization of parallel processors using clock pulse width modulation

Science.gov (United States)

Chen, Dong; Ellavsky, Matthew R.; Franke, Ross L.; Gara, Alan; Gooding, Thomas M.; Haring, Rudolf A.; Jeanson, Mark J.; Kopcsay, Gerard V.; Liebsch, Thomas A.; Littrell, Daniel; Ohmacht, Martin; Reed, Don D.; Schenck, Brandon E.; Swetz, Richard A.

2013-04-02

A circuit generates a global clock signal with a pulse width modification to synchronize processors in a parallel computing system. The circuit may include a hardware module and a clock splitter. The hardware module may generate a clock signal and performs a pulse width modification on the clock signal. The pulse width modification changes a pulse width within a clock period in the clock signal. The clock splitter may distribute the pulse width modified clock signal to a plurality of processors in the parallel computing system.

12-core x 3-mode Dense Space Division Multiplexed Transmission over 40 km Employing Multi-carrier Signals with Parallel MIMO Equalization

DEFF Research Database (Denmark)

Mizuno, T.; Kobayashi, T.; Takara, H.

2014-01-01

We demonstrate dense SDM transmission of 20-WDM multi-carrier PDM-32QAM signals over a 40-km 12-core x 3-mode fiber with 247.9-b/s/Hz spectral efficiency. Parallel MIMO equalization enables 21-ns DMD compensation with 61 TDE taps per subcarrier....

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)

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

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.

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

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)

'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.)

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.

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.)

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.

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

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.

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.

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

Computation and parallel implementation for early vision

Science.gov (United States)

Gualtieri, J. Anthony

1990-01-01

The problem of early vision is to transform one or more retinal illuminance images-pixel arrays-to image representations built out of such primitive visual features such as edges, regions, disparities, and clusters. These transformed representations form the input to later vision stages that perform higher level vision tasks including matching and recognition. Researchers developed algorithms for: (1) edge finding in the scale space formulation; (2) correlation methods for computing matches between pairs of images; and (3) clustering of data by neural networks. These algorithms are formulated for parallel implementation of SIMD machines, such as the Massively Parallel Processor, a 128 x 128 array processor with 1024 bits of local memory per processor. For some cases, researchers can show speedups of three orders of magnitude over serial implementations.

Fast-Acquisition/Weak-Signal-Tracking GPS Receiver for HEO

Science.gov (United States)

Wintemitz, Luke; Boegner, Greg; Sirotzky, Steve

2004-01-01

A report discusses the technical background and design of the Navigator Global Positioning System (GPS) receiver -- . a radiation-hardened receiver intended for use aboard spacecraft. Navigator is capable of weak signal acquisition and tracking as well as much faster acquisition of strong or weak signals with no a priori knowledge or external aiding. Weak-signal acquisition and tracking enables GPS use in high Earth orbits (HEO), and fast acquisition allows for the receiver to remain without power until needed in any orbit. Signal acquisition and signal tracking are, respectively, the processes of finding and demodulating a signal. Acquisition is the more computationally difficult process. Previous GPS receivers employ the method of sequentially searching the two-dimensional signal parameter space (code phase and Doppler). Navigator exploits properties of the Fourier transform in a massively parallel search for the GPS signal. This method results in far faster acquisition times [in the lab, 12 GPS satellites have been acquired with no a priori knowledge in a Low-Earth-Orbit (LEO) scenario in less than one second]. Modeling has shown that Navigator will be capable of acquiring signals down to 25 dB-Hz, appropriate for HEO missions. Navigator is built using the radiation-hardened ColdFire microprocessor and housing the most computationally intense functions in dedicated field-programmable gate arrays. The high performance of the algorithm and of the receiver as a whole are made possible by optimizing computational efficiency and carefully weighing tradeoffs among the sampling rate, data format, and data-path bit width.

Tryton Supercomputer Capabilities for Analysis of Massive Data Streams

Directory of Open Access Journals (Sweden)

Krawczyk Henryk

2015-09-01

Full Text Available The recently deployed supercomputer Tryton, located in the Academic Computer Center of Gdansk University of Technology, provides great means for massive parallel processing. Moreover, the status of the Center as one of the main network nodes in the PIONIER network enables the fast and reliable transfer of data produced by miscellaneous devices scattered in the area of the whole country. The typical examples of such data are streams containing radio-telescope and satellite observations. Their analysis, especially with real-time constraints, can be challenging and requires the usage of dedicated software components. We propose a solution for such parallel analysis using the supercomputer, supervised by the KASKADA platform, which with the conjunction with immerse 3D visualization techniques can be used to solve problems such as pulsar detection and chronometric or oil-spill simulation on the sea surface.

The Destructive Birth of Massive Stars and Massive Star Clusters

Science.gov (United States)

Rosen, Anna; Krumholz, Mark; McKee, Christopher F.; Klein, Richard I.; Ramirez-Ruiz, Enrico

2017-01-01

Massive stars play an essential role in the Universe. They are rare, yet the energy and momentum they inject into the interstellar medium with their intense radiation fields dwarfs the contribution by their vastly more numerous low-mass cousins. Previous theoretical and observational studies have concluded that the feedback associated with massive stars' radiation fields is the dominant mechanism regulating massive star and massive star cluster (MSC) formation. Therefore detailed simulation of the formation of massive stars and MSCs, which host hundreds to thousands of massive stars, requires an accurate treatment of radiation. For this purpose, we have developed a new, highly accurate hybrid radiation algorithm that properly treats the absorption of the direct radiation field from stars and the re-emission and processing by interstellar dust. We use our new tool to perform a suite of three-dimensional radiation-hydrodynamic simulations of the formation of massive stars and MSCs. For individual massive stellar systems, we simulate the collapse of massive pre-stellar cores with laminar and turbulent initial conditions and properly resolve regions where we expect instabilities to grow. We find that mass is channeled to the massive stellar system via gravitational and Rayleigh-Taylor (RT) instabilities. For laminar initial conditions, proper treatment of the direct radiation field produces later onset of RT instability, but does not suppress it entirely provided the edges of the radiation-dominated bubbles are adequately resolved. RT instabilities arise immediately for turbulent pre-stellar cores because the initial turbulence seeds the instabilities. To model MSC formation, we simulate the collapse of a dense, turbulent, magnetized Mcl = 106 M⊙ molecular cloud. We find that the influence of the magnetic pressure and radiative feedback slows down star formation. Furthermore, we find that star formation is suppressed along dense filaments where the magnetic field is

Application of parallel computing techniques to a large-scale reservoir simulation

International Nuclear Information System (INIS)

Zhang, Keni; Wu, Yu-Shu; Ding, Chris; Pruess, Karsten

2001-01-01

Even with the continual advances made in both computational algorithms and computer hardware used in reservoir modeling studies, large-scale simulation of fluid and heat flow in heterogeneous reservoirs remains a challenge. The problem commonly arises from intensive computational requirement for detailed modeling investigations of real-world reservoirs. This paper presents the application of a massive parallel-computing version of the TOUGH2 code developed for performing large-scale field simulations. As an application example, the parallelized TOUGH2 code is applied to develop a three-dimensional unsaturated-zone numerical model simulating flow of moisture, gas, and heat in the unsaturated zone of Yucca Mountain, Nevada, a potential repository for high-level radioactive waste. The modeling approach employs refined spatial discretization to represent the heterogeneous fractured tuffs of the system, using more than a million 3-D gridblocks. The problem of two-phase flow and heat transfer within the model domain leads to a total of 3,226,566 linear equations to be solved per Newton iteration. The simulation is conducted on a Cray T3E-900, a distributed-memory massively parallel computer. Simulation results indicate that the parallel computing technique, as implemented in the TOUGH2 code, is very efficient. The reliability and accuracy of the model results have been demonstrated by comparing them to those of small-scale (coarse-grid) models. These comparisons show that simulation results obtained with the refined grid provide more detailed predictions of the future flow conditions at the site, aiding in the assessment of proposed repository performance

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

International Nuclear Information System (INIS)

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

2009-01-01

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

High-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.

Massive Gravity

OpenAIRE

de Rham, Claudia

2014-01-01

We review recent progress in massive gravity. We start by showing how different theories of massive gravity emerge from a higher-dimensional theory of general relativity, leading to the Dvali–Gabadadze–Porrati model (DGP), cascading gravity, and ghost-free massive gravity. We then explore their theoretical and phenomenological consistency, proving the absence of Boulware–Deser ghosts and reviewing the Vainshtein mechanism and the cosmological solutions in these models. Finally, we present alt...

MAX-SLNR Precoding Algorithm for Massive MIMO System

Directory of Open Access Journals (Sweden)

Jiang Jing

2016-01-01

Full Text Available Pilot Contamination obviously degrades the system performance of Massive MIMO systems. In this paper, a downlink precoding algorithm based on the Signal-to- Leakage-plus-Noise-Ratio (SLNR criterion is put forward. First, the impact of Pilot Contamination on SLNR is analyzed，then the precoding matrix is calculated with the eigenvalues decomposition of SLNR, which not only maximize the array gains of the target user, but also minimize the impact of Pilot Contamination and the leak to the users of other cells. Further, a simplified solution is derived, in which the impact of Pilot Contamination can be suppressed only with the large-scale fading coefficients. Simulation results reveal that: in the scenario of the serious pilot contamination, the proposed algorithm can avoid the performance loss caused by the pilot contamination compared with the conventional Massive MIMO precoding algorithm. Thus the proposed algorithm can acquire the perfect performance gains of Massive MIMO system and has better practical value since the large-scale fading coefficients are easy to measure and feedback.

High-speed parallel counter

International Nuclear Information System (INIS)

Gus'kov, B.N.; Kalinnikov, V.A.; Krastev, V.R.; Maksimov, A.N.; Nikityuk, N.M.

1985-01-01

This paper describes a high-speed parallel counter that contains 31 inputs and 15 outputs and is implemented by integrated circuits of series 500. The counter is designed for fast sampling of events according to the number of particles that pass simultaneously through the hodoscopic plane of the detector. The minimum delay of the output signals relative to the input is 43 nsec. The duration of the output signals can be varied from 75 to 120 nsec

method for ranging and noise reduction of low coherence interferometry LCI and optical coherence tomography OCT signals by parallel detection of spectral bands

NARCIS (Netherlands)

Boer, JF De; Tearney, G. J.; Bouma, BE

2008-01-01

Apparatus and method for increasing the sensitivity in the detection of optical coherence tomography and loW coher ence interferometry (“LCI”) signals by detecting a parallel set of spectral bands, each band being a unique combination of optical frequencies. The LCI broad bandwidth source is split

Discrete Hadamard transformation algorithm's parallelism analysis and achievement

Science.gov (United States)

Hu, Hui

2009-07-01

With respect to Discrete Hadamard Transformation (DHT) wide application in real-time signal processing while limitation in operation speed of DSP. The article makes DHT parallel research and its parallel performance analysis. Based on multiprocessor platform-TMS320C80 programming structure, the research is carried out to achieve two kinds of parallel DHT algorithms. Several experiments demonstrated the effectiveness of the proposed algorithms.

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.

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.

Signatures of massive sgoldstinos at hadron colliders

International Nuclear Information System (INIS)

Perazzi, Elena; Ridolfi, Giovanni; Zwirner, Fabio

2000-01-01

In supersymmetric extensions of the Standard Model with a very light gravitino, the effective theory at the weak scale should contain not only the goldstino G-tilde, but also its supersymmetric partners, the sgoldstinos. In the simplest case, the goldstino is a gauge-singlet and its superpartners are two neutral spin-0 particles, S and P. We study possible signals of massive sgoldstinos at hadron colliders, focusing on those that are most relevant for the Tevatron. We show that inclusive production of sgoldstinos, followed by their decay into two photons, can lead to observable signals or to stringent combined bounds on the gravitino and sgoldstino masses. Sgoldstino decays into two gluon jets may provide a useful complementary signature

Small-Signal Modeling, Analysis and Testing of Parallel Three-Phase-Inverters with A Novel Autonomous Current Sharing Controller

DEFF Research Database (Denmark)

Guan, Yajuan; Quintero, Juan Carlos Vasquez; Guerrero, Josep M.

2015-01-01

A novel simple and effective autonomous currentsharing controller for parallel three-phase inverters is employed in this paper. The novel controller is able to endow to the system high speed response and precision in contrast to the conventional droop control as it does not require calculating any...... active or reactive power, instead it uses a virtual impedance loop and a SFR phase-locked loop. The small-signal model of the system was developed for the autonomous operation of inverter-based microgrid with the proposed controller. The developed model shows large stability margin and fast transient...

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.

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.

I - Template Metaprogramming for Massively Parallel Scientific Computing - Expression Templates

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...

Reconstruction of the 1997/1998 El Nino from TOPEX/POSEIDON and TOGA/TAO Data Using a Massively Parallel Pacific-Ocean Model and Ensemble Kalman Filter

Science.gov (United States)

Keppenne, C. L.; Rienecker, M.; Borovikov, A. Y.

1999-01-01

Two massively parallel data assimilation systems in which the model forecast-error covariances are estimated from the distribution of an ensemble of model integrations are applied to the assimilation of 97-98 TOPEX/POSEIDON altimetry and TOGA/TAO temperature data into a Pacific basin version the NASA Seasonal to Interannual Prediction Project (NSIPP)ls quasi-isopycnal ocean general circulation model. in the first system, ensemble of model runs forced by an ensemble of atmospheric model simulations is used to calculate asymptotic error statistics. The data assimilation then occurs in the reduced phase space spanned by the corresponding leading empirical orthogonal functions. The second system is an ensemble Kalman filter in which new error statistics are computed during each assimilation cycle from the time-dependent ensemble distribution. The data assimilation experiments are conducted on NSIPP's 512-processor CRAY T3E. The two data assimilation systems are validated by withholding part of the data and quantifying the extent to which the withheld information can be inferred from the assimilation of the remaining data. The pros and cons of each system are discussed.

Design of multiple sequence alignment algorithms on parallel, distributed memory supercomputers.

Science.gov (United States)

Church, Philip C; Goscinski, Andrzej; Holt, Kathryn; Inouye, Michael; Ghoting, Amol; Makarychev, Konstantin; Reumann, Matthias

2011-01-01

The challenge of comparing two or more genomes that have undergone recombination and substantial amounts of segmental loss and gain has recently been addressed for small numbers of genomes. However, datasets of hundreds of genomes are now common and their sizes will only increase in the future. Multiple sequence alignment of hundreds of genomes remains an intractable problem due to quadratic increases in compute time and memory footprint. To date, most alignment algorithms are designed for commodity clusters without parallelism. Hence, we propose the design of a multiple sequence alignment algorithm on massively parallel, distributed memory supercomputers to enable research into comparative genomics on large data sets. Following the methodology of the sequential progressiveMauve algorithm, we design data structures including sequences and sorted k-mer lists on the IBM Blue Gene/P supercomputer (BG/P). Preliminary results show that we can reduce the memory footprint so that we can potentially align over 250 bacterial genomes on a single BG/P compute node. We verify our results on a dataset of E.coli, Shigella and S.pneumoniae genomes. Our implementation returns results matching those of the original algorithm but in 1/2 the time and with 1/4 the memory footprint for scaffold building. In this study, we have laid the basis for multiple sequence alignment of large-scale datasets on a massively parallel, distributed memory supercomputer, thus enabling comparison of hundreds instead of a few genome sequences within reasonable time.

Parallel computing techniques for rotorcraft aerodynamics

Science.gov (United States)

Ekici, Kivanc

The modification of unsteady three-dimensional Navier-Stokes codes for application on massively parallel and distributed computing environments is investigated. The Euler/Navier-Stokes code TURNS (Transonic Unsteady Rotor Navier-Stokes) was chosen as a test bed because of its wide use by universities and industry. For the efficient implementation of TURNS on parallel computing systems, two algorithmic changes are developed. First, main modifications to the implicit operator, Lower-Upper Symmetric Gauss Seidel (LU-SGS) originally used in TURNS, is performed. Second, application of an inexact Newton method, coupled with a Krylov subspace iterative method (Newton-Krylov method) is carried out. Both techniques have been tried previously for the Euler equations mode of the code. In this work, we have extended the methods to the Navier-Stokes mode. Several new implicit operators were tried because of convergence problems of traditional operators with the high cell aspect ratio (CAR) grids needed for viscous calculations on structured grids. Promising results for both Euler and Navier-Stokes cases are presented for these operators. For the efficient implementation of Newton-Krylov methods to the Navier-Stokes mode of TURNS, efficient preconditioners must be used. The parallel implicit operators used in the previous step are employed as preconditioners and the results are compared. The Message Passing Interface (MPI) protocol has been used because of its portability to various parallel architectures. It should be noted that the proposed methodology is general and can be applied to several other CFD codes (e.g. OVERFLOW).

GPU: the biggest key processor for AI and parallel processing

Science.gov (United States)

Baji, Toru

2017-07-01

Two types of processors exist in the market. One is the conventional CPU and the other is Graphic Processor Unit (GPU). Typical CPU is composed of 1 to 8 cores while GPU has thousands of cores. CPU is good for sequential processing, while GPU is good to accelerate software with heavy parallel executions. GPU was initially dedicated for 3D graphics. However from 2006, when GPU started to apply general-purpose cores, it was noticed that this architecture can be used as a general purpose massive-parallel processor. NVIDIA developed a software framework Compute Unified Device Architecture (CUDA) that make it possible to easily program the GPU for these application. With CUDA, GPU started to be used in workstations and supercomputers widely. Recently two key technologies are highlighted in the industry. The Artificial Intelligence (AI) and Autonomous Driving Cars. AI requires a massive parallel operation to train many-layers of neural networks. With CPU alone, it was impossible to finish the training in a practical time. The latest multi-GPU system with P100 makes it possible to finish the training in a few hours. For the autonomous driving cars, TOPS class of performance is required to implement perception, localization, path planning processing and again SoC with integrated GPU will play a key role there. In this paper, the evolution of the GPU which is one of the biggest commercial devices requiring state-of-the-art fabrication technology will be introduced. Also overview of the GPU demanding key application like the ones described above will be introduced.

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.

Parallel community climate model: Description and user`s guide

Energy Technology Data Exchange (ETDEWEB)

Drake, J.B.; Flanery, R.E.; Semeraro, B.D.; Worley, P.H. [and others

1996-07-15

This report gives an overview of a parallel version of the NCAR Community Climate Model, CCM2, implemented for MIMD massively parallel computers using a message-passing programming paradigm. The parallel implementation was developed on an Intel iPSC/860 with 128 processors and on the Intel Delta with 512 processors, and the initial target platform for the production version of the code is the Intel Paragon with 2048 processors. Because the implementation uses a standard, portable message-passing libraries, the code has been easily ported to other multiprocessors supporting a message-passing programming paradigm. The parallelization strategy used is to decompose the problem domain into geographical patches and assign each processor the computation associated with a distinct subset of the patches. With this decomposition, the physics calculations involve only grid points and data local to a processor and are performed in parallel. Using parallel algorithms developed for the semi-Lagrangian transport, the fast Fourier transform and the Legendre transform, both physics and dynamics are computed in parallel with minimal data movement and modest change to the original CCM2 source code. Sequential or parallel history tapes are written and input files (in history tape format) are read sequentially by the parallel code to promote compatibility with production use of the model on other computer systems. A validation exercise has been performed with the parallel code and is detailed along with some performance numbers on the Intel Paragon and the IBM SP2. A discussion of reproducibility of results is included. A user`s guide for the PCCM2 version 2.1 on the various parallel machines completes the report. Procedures for compilation, setup and execution are given. A discussion of code internals is included for those who may wish to modify and use the program in their own research.

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.

Massless and massive quanta resulting from a mediumlike metric tensor

International Nuclear Information System (INIS)

Soln, J.

1985-01-01

A simple model of the ''primordial'' scalar field theory is presented in which the metric tensor is a generalization of the metric tensor from electrodynamics in a medium. The radiation signal corresponding to the scalar field propagates with a velocity that is generally less than c. This signal can be associated simultaneously with imaginary and real effective (momentum-dependent) masses. The requirement that the imaginary effective mass vanishes, which we take to be the prerequisite for the vacuumlike signal propagation, leads to the ''spontaneous'' splitting of the metric tensor into two distinct metric tensors: one metric tensor gives rise to masslesslike radiation and the other to a massive particle. (author)

The effect of plasma fluctuations on parallel transport parameters in the SOL

DEFF Research Database (Denmark)

Havlíčková, E.; Fundamenski, W.; Naulin, Volker

2011-01-01

The effect of plasma fluctuations due to turbulence at the outboard midplane on parallel transport properties is investigated. Time-dependent fluctuating signals at different radial locations are used to study the effect of signal statistics. Further, a computational analysis of parallel transport...... to a comparison of steady-state and time-dependent modelling....

Method of optical coherence tomography with parallel depth-resolved signal reception and fibre-optic phase modulators

Energy Technology Data Exchange (ETDEWEB)

Morozov, A N; Turchin, I V [Institute of Applied Physics, Russian Academy of Sciences, Nizhnii Novgorod (Russian Federation)

2013-12-31

The method of optical coherence tomography with the scheme of parallel reception of the interference signal (P-OCT) is developed on the basis of spatial paralleling of the reference wave by means of a phase diffraction grating producing the appropriate time delay in the Mach–Zehnder interferometer. The absence of mechanical variation of the optical path difference in the interferometer essentially reduces the time required for 2D imaging of the object internal structure, as compared to the classical OCT that uses the time-domain method of the image construction, the sensitivity and the dynamic range being comparable in both approaches. For the resulting field of the interfering object and reference waves an analytical expression is derived that allows the calculation of the autocorrelation function in the plane of photodetectors. For the first time a method of linear phase modulation by 2π is proposed for P-OCT systems, which allows the use of compact high-frequency (a few hundred kHz) piezoelectric cell-based modulators. For the demonstration of the P-OCT method an experimental setup was created, using which the images of the inner structure of biological objects at the depth up to 1 mm with the axial spatial resolution of 12 μm were obtained. (optical coherence tomography)

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

International Nuclear Information System (INIS)

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

2006-01-01

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

Accelerating Monte Carlo Molecular Simulations Using Novel Extrapolation Schemes Combined with Fast Database Generation on Massively Parallel Machines

KAUST Repository

Amir, Sahar Z.

2013-05-01

We introduce an efficient thermodynamically consistent technique to extrapolate and interpolate normalized Canonical NVT ensemble averages like pressure and energy for Lennard-Jones (L-J) fluids. Preliminary results show promising applicability in oil and gas modeling, where accurate determination of thermodynamic properties in reservoirs is challenging. The thermodynamic interpolation and thermodynamic extrapolation schemes predict ensemble averages at different thermodynamic conditions from expensively simulated data points. The methods reweight and reconstruct previously generated database values of Markov chains at neighboring temperature and density conditions. To investigate the efficiency of these methods, two databases corresponding to different combinations of normalized density and temperature are generated. One contains 175 Markov chains with 10,000,000 MC cycles each and the other contains 3000 Markov chains with 61,000,000 MC cycles each. For such massive database creation, two algorithms to parallelize the computations have been investigated. The accuracy of the thermodynamic extrapolation scheme is investigated with respect to classical interpolation and extrapolation. Finally, thermodynamic interpolation benefiting from four neighboring Markov chains points is implemented and compared with previous schemes. The thermodynamic interpolation scheme using knowledge from the four neighboring points proves to be more accurate than the thermodynamic extrapolation from the closest point only, while both thermodynamic extrapolation and thermodynamic interpolation are more accurate than the classical interpolation and extrapolation. The investigated extrapolation scheme has great potential in oil and gas reservoir modeling.That is, such a scheme has the potential to speed up the MCMC thermodynamic computation to be comparable with conventional Equation of State approaches in efficiency. In particular, this makes it applicable to large-scale optimization of L

Application of affymetrix array and massively parallel signature sequencing for identification of genes involved in prostate cancer progression

International Nuclear Information System (INIS)

Oudes, Asa J; Roach, Jared C; Walashek, Laura S; Eichner, Lillian J; True, Lawrence D; Vessella, Robert L; Liu, Alvin Y

2005-01-01

Affymetrix GeneChip Array and Massively Parallel Signature Sequencing (MPSS) are two high throughput methodologies used to profile transcriptomes. Each method has certain strengths and weaknesses; however, no comparison has been made between the data derived from Affymetrix arrays and MPSS. In this study, two lineage-related prostate cancer cell lines, LNCaP and C4-2, were used for transcriptome analysis with the aim of identifying genes associated with prostate cancer progression. Affymetrix GeneChip array and MPSS analyses were performed. Data was analyzed with GeneSpring 6.2 and in-house perl scripts. Expression array results were verified with RT-PCR. Comparison of the data revealed that both technologies detected genes the other did not. In LNCaP, 3,180 genes were only detected by Affymetrix and 1,169 genes were only detected by MPSS. Similarly, in C4-2, 4,121 genes were only detected by Affymetrix and 1,014 genes were only detected by MPSS. Analysis of the combined transcriptomes identified 66 genes unique to LNCaP cells and 33 genes unique to C4-2 cells. Expression analysis of these genes in prostate cancer specimens showed CA1 to be highly expressed in bone metastasis but not expressed in primary tumor and EPHA7 to be expressed in normal prostate and primary tumor but not bone metastasis. Our data indicates that transcriptome profiling with a single methodology will not fully assess the expression of all genes in a cell line. A combination of transcription profiling technologies such as DNA array and MPSS provides a more robust means to assess the expression profile of an RNA sample. Finally, genes that were differentially expressed in cell lines were also differentially expressed in primary prostate cancer and its metastases

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.

Neurite, a finite difference large scale parallel program for the simulation of electrical signal propagation in neurites under mechanical loading.

Directory of Open Access Journals (Sweden)

Julián A García-Grajales

Full Text Available With the growing body of research on traumatic brain injury and spinal cord injury, computational neuroscience has recently focused its modeling efforts on neuronal functional deficits following mechanical loading. However, in most of these efforts, cell damage is generally only characterized by purely mechanistic criteria, functions of quantities such as stress, strain or their corresponding rates. The modeling of functional deficits in neurites as a consequence of macroscopic mechanical insults has been rarely explored. In particular, a quantitative mechanically based model of electrophysiological impairment in neuronal cells, Neurite, has only very recently been proposed. In this paper, we present the implementation details of this model: a finite difference parallel program for simulating electrical signal propagation along neurites under mechanical loading. Following the application of a macroscopic strain at a given strain rate produced by a mechanical insult, Neurite is able to simulate the resulting neuronal electrical signal propagation, and thus the corresponding functional deficits. The simulation of the coupled mechanical and electrophysiological behaviors requires computational expensive calculations that increase in complexity as the network of the simulated cells grows. The solvers implemented in Neurite--explicit and implicit--were therefore parallelized using graphics processing units in order to reduce the burden of the simulation costs of large scale scenarios. Cable Theory and Hodgkin-Huxley models were implemented to account for the electrophysiological passive and active regions of a neurite, respectively, whereas a coupled mechanical model accounting for the neurite mechanical behavior within its surrounding medium was adopted as a link between electrophysiology and mechanics. This paper provides the details of the parallel implementation of Neurite, along with three different application examples: a long myelinated axon

Domain-Specific Acceleration and Auto-Parallelization of Legacy Scientific Code in FORTRAN 77 using Source-to-Source Compilation

OpenAIRE

Vanderbauwhede, Wim; Davidson, Gavin

2017-01-01

Massively parallel accelerators such as GPGPUs, manycores and FPGAs represent a powerful and affordable tool for scientists who look to speed up simulations of complex systems. However, porting code to such devices requires a detailed understanding of heterogeneous programming tools and effective strategies for parallelization. In this paper we present a source to source compilation approach with whole-program analysis to automatically transform single-threaded FORTRAN 77 legacy code into Ope...

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.

Monte Carlo simulations of quantum systems on massively parallel supercomputers

International Nuclear Information System (INIS)

Ding, H.Q.

1993-01-01

A large class of quantum physics applications uses operator representations that are discrete integers by nature. This class includes magnetic properties of solids, interacting bosons modeling superfluids and Cooper pairs in superconductors, and Hubbard models for strongly correlated electrons systems. This kind of application typically uses integer data representations and the resulting algorithms are dominated entirely by integer operations. The authors implemented an efficient algorithm for one such application on the Intel Touchstone Delta and iPSC/860. The algorithm uses a multispin coding technique which allows significant data compactification and efficient vectorization of Monte Carlo updates. The algorithm regularly switches between two data decompositions, corresponding naturally to different Monte Carlo updating processes and observable measurements such that only nearest-neighbor communications are needed within a given decomposition. On 128 nodes of Intel Delta, this algorithm updates 183 million spins per second (compared to 21 million on CM-2 and 6.2 million on a Cray Y-MP). A systematic performance analysis shows a better than 90% efficiency in the parallel implementation

ParaBTM: A Parallel Processing Framework for Biomedical Text Mining on Supercomputers.

Science.gov (United States)

Xing, Yuting; Wu, Chengkun; Yang, Xi; Wang, Wei; Zhu, En; Yin, Jianping

2018-04-27

A prevailing way of extracting valuable information from biomedical literature is to apply text mining methods on unstructured texts. However, the massive amount of literature that needs to be analyzed poses a big data challenge to the processing efficiency of text mining. In this paper, we address this challenge by introducing parallel processing on a supercomputer. We developed paraBTM, a runnable framework that enables parallel text mining on the Tianhe-2 supercomputer. It employs a low-cost yet effective load balancing strategy to maximize the efficiency of parallel processing. We evaluated the performance of paraBTM on several datasets, utilizing three types of named entity recognition tasks as demonstration. Results show that, in most cases, the processing efficiency can be greatly improved with parallel processing, and the proposed load balancing strategy is simple and effective. In addition, our framework can be readily applied to other tasks of biomedical text mining besides NER.

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.

Second International Workshop on Software Engineering and Code Design in Parallel Meteorological and Oceanographic Applications

Science.gov (United States)

OKeefe, Matthew (Editor); Kerr, Christopher L. (Editor)

1998-01-01

This report contains the abstracts and technical papers from the Second International Workshop on Software Engineering and Code Design in Parallel Meteorological and Oceanographic Applications, held June 15-18, 1998, in Scottsdale, Arizona. The purpose of the workshop is to bring together software developers in meteorology and oceanography to discuss software engineering and code design issues for parallel architectures, including Massively Parallel Processors (MPP's), Parallel Vector Processors (PVP's), Symmetric Multi-Processors (SMP's), Distributed Shared Memory (DSM) multi-processors, and clusters. Issues to be discussed include: (1) code architectures for current parallel models, including basic data structures, storage allocation, variable naming conventions, coding rules and styles, i/o and pre/post-processing of data; (2) designing modular code; (3) load balancing and domain decomposition; (4) techniques that exploit parallelism efficiently yet hide the machine-related details from the programmer; (5) tools for making the programmer more productive; and (6) the proliferation of programming models (F--, OpenMP, MPI, and HPF).

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

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.

Parallel Evolutionary Optimization for Neuromorphic Network Training

Energy Technology Data Exchange (ETDEWEB)

Schuman, Catherine D [ORNL; Disney, Adam [University of Tennessee (UT); Singh, Susheela [North Carolina State University (NCSU), Raleigh; Bruer, Grant [University of Tennessee (UT); Mitchell, John Parker [University of Tennessee (UT); Klibisz, Aleksander [University of Tennessee (UT); Plank, James [University of Tennessee (UT)

2016-01-01

One of the key impediments to the success of current neuromorphic computing architectures is the issue of how best to program them. Evolutionary optimization (EO) is one promising programming technique; in particular, its wide applicability makes it especially attractive for neuromorphic architectures, which can have many different characteristics. In this paper, we explore different facets of EO on a spiking neuromorphic computing model called DANNA. We focus on the performance of EO in the design of our DANNA simulator, and on how to structure EO on both multicore and massively parallel computing systems. We evaluate how our parallel methods impact the performance of EO on Titan, the U.S.'s largest open science supercomputer, and BOB, a Beowulf-style cluster of Raspberry Pi's. We also focus on how to improve the EO by evaluating commonality in higher performing neural networks, and present the result of a study that evaluates the EO performed by Titan.

Galaxy bispectrum from massive spinning particles

Science.gov (United States)

Moradinezhad Dizgah, Azadeh; Lee, Hayden; Muñoz, Julian B.; Dvorkin, Cora

2018-05-01

Massive spinning particles, if present during inflation, lead to a distinctive bispectrum of primordial perturbations, the shape and amplitude of which depend on the masses and spins of the extra particles. This signal, in turn, leaves an imprint in the statistical distribution of galaxies; in particular, as a non-vanishing galaxy bispectrum, which can be used to probe the masses and spins of these particles. In this paper, we present for the first time a new theoretical template for the bispectrum generated by massive spinning particles, valid for a general triangle configuration. We then proceed to perform a Fisher-matrix forecast to assess the potential of two next-generation spectroscopic galaxy surveys, EUCLID and DESI, to constrain the primordial non-Gaussianity sourced by these extra particles. We model the galaxy bispectrum using tree-level perturbation theory, accounting for redshift-space distortions and the Alcock-Paczynski effect, and forecast constraints on the primordial non-Gaussianity parameters marginalizing over all relevant biases and cosmological parameters. Our results suggest that these surveys would potentially be sensitive to any primordial non-Gaussianity with an amplitude larger than fNL≈ 1, for massive particles with spins 2, 3, and 4. Interestingly, if non-Gaussianities are present at that level, these surveys will be able to infer the masses of these spinning particles to within tens of percent. If detected, this would provide a very clear window into the particle content of our Universe during inflation.

Implementation of parallel processing in the basf2 framework for Belle II

International Nuclear Information System (INIS)

Itoh, Ryosuke; Lee, Soohyung; Katayama, N; Mineo, S; Moll, A; Kuhr, T; Heck, M

2012-01-01

Recent PC servers are equipped with multi-core CPUs and it is desired to utilize the full processing power of them for the data analysis in large scale HEP experiments. A software framework basf2 is being developed for the use in the Belle II experiment, a new generation B-factory experiment at KEK, and the parallel event processing to utilize the multi-core CPUs is in its design for the use in the massive data production. The details of the implementation of event parallel processing in the basf2 framework are discussed with the report of preliminary performance study in the realistic use on a 32 core PC server.

Evaluation of Circulating Current Suppression Methods for Parallel Interleaved Inverters

DEFF Research Database (Denmark)

Gohil, Ghanshyamsinh Vijaysinh; Bede, Lorand; Teodorescu, Remus

2016-01-01

Two-level Voltage Source Converters (VSCs) are often connected in parallel to achieve desired current rating in multi-megawatt Wind Energy Conversion System (WECS). A multi-level converter can be realized by interleaving the carrier signals of the parallel VSCs. As a result, the harmonic perfor......-mance of the WECS can be significantly improved. However, the interleaving of the carrier signals may lead to the flow of circulating current between parallel VSCs and it is highly desirable to avoid/suppress this unwanted circulating current. A comparative evaluation of the different methods to avoid....../suppress the circulating current between the parallel interleaved VSCs is presented in this paper. The losses and the volume of the inductive components and the semiconductor losses are evaluated for the WECS with different circulating current suppression methods. Multi-objective optimizations of the inductive components...

A massive cryogenic particle detector with good energy resolution

International Nuclear Information System (INIS)

Ferger, P.; Colling, P.; Cooper, S.; Dummer, D.; Frank, M.; Nagel, U.; Nucciotti, A.; Proebst, F.; Seidel, W.

1993-12-01

Massive cryogenic particle detectors are being developed for use in a search for dark matter particles. Results with a 31 g sapphire crystal and a superconducting phase transition thermometer operated at 44 mK are presented. The observed signal includes a fast component which is significantly larger than the expected thermal pulse. The energy resolution is 210 eV (FWHM) for 6 keV X-rays. (orig.)

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.

Touch imprint cytology with massively parallel sequencing (TIC-seq): a simple and rapid method to snapshot genetic alterations in tumors.

Science.gov (United States)

Amemiya, Kenji; Hirotsu, Yosuke; Goto, Taichiro; Nakagomi, Hiroshi; Mochizuki, Hitoshi; Oyama, Toshio; Omata, Masao

2016-12-01

Identifying genetic alterations in tumors is critical for molecular targeting of therapy. In the clinical setting, formalin-fixed paraffin-embedded (FFPE) tissue is usually employed for genetic analysis. However, DNA extracted from FFPE tissue is often not suitable for analysis because of its low levels and poor quality. Additionally, FFPE sample preparation is time-consuming. To provide early treatment for cancer patients, a more rapid and robust method is required for precision medicine. We present a simple method for genetic analysis, called touch imprint cytology combined with massively paralleled sequencing (touch imprint cytology [TIC]-seq), to detect somatic mutations in tumors. We prepared FFPE tissues and TIC specimens from tumors in nine lung cancer patients and one patient with breast cancer. We found that the quality and quantity of TIC DNA was higher than that of FFPE DNA, which requires microdissection to enrich DNA from target tissues. Targeted sequencing using a next-generation sequencer obtained sufficient sequence data using TIC DNA. Most (92%) somatic mutations in lung primary tumors were found to be consistent between TIC and FFPE DNA. We also applied TIC DNA to primary and metastatic tumor tissues to analyze tumor heterogeneity in a breast cancer patient, and showed that common and distinct mutations among primary and metastatic sites could be classified into two distinct histological subtypes. TIC-seq is an alternative and feasible method to analyze genomic alterations in tumors by simply touching the cut surface of specimens to slides. © 2016 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Load-balancing techniques for a parallel electromagnetic particle-in-cell code

Energy Technology Data Exchange (ETDEWEB)

PLIMPTON,STEVEN J.; SEIDEL,DAVID B.; PASIK,MICHAEL F.; COATS,REBECCA S.

2000-01-01

QUICKSILVER is a 3-d electromagnetic particle-in-cell simulation code developed and used at Sandia to model relativistic charged particle transport. It models the time-response of electromagnetic fields and low-density-plasmas in a self-consistent manner: the fields push the plasma particles and the plasma current modifies the fields. Through an LDRD project a new parallel version of QUICKSILVER was created to enable large-scale plasma simulations to be run on massively-parallel distributed-memory supercomputers with thousands of processors, such as the Intel Tflops and DEC CPlant machines at Sandia. The new parallel code implements nearly all the features of the original serial QUICKSILVER and can be run on any platform which supports the message-passing interface (MPI) standard as well as on single-processor workstations. This report describes basic strategies useful for parallelizing and load-balancing particle-in-cell codes, outlines the parallel algorithms used in this implementation, and provides a summary of the modifications made to QUICKSILVER. It also highlights a series of benchmark simulations which have been run with the new code that illustrate its performance and parallel efficiency. These calculations have up to a billion grid cells and particles and were run on thousands of processors. This report also serves as a user manual for people wishing to run parallel QUICKSILVER.

Load-balancing techniques for a parallel electromagnetic particle-in-cell code

International Nuclear Information System (INIS)

Plimpton, Steven J.; Seidel, David B.; Pasik, Michael F.; Coats, Rebecca S.

2000-01-01

QUICKSILVER is a 3-d electromagnetic particle-in-cell simulation code developed and used at Sandia to model relativistic charged particle transport. It models the time-response of electromagnetic fields and low-density-plasmas in a self-consistent manner: the fields push the plasma particles and the plasma current modifies the fields. Through an LDRD project a new parallel version of QUICKSILVER was created to enable large-scale plasma simulations to be run on massively-parallel distributed-memory supercomputers with thousands of processors, such as the Intel Tflops and DEC CPlant machines at Sandia. The new parallel code implements nearly all the features of the original serial QUICKSILVER and can be run on any platform which supports the message-passing interface (MPI) standard as well as on single-processor workstations. This report describes basic strategies useful for parallelizing and load-balancing particle-in-cell codes, outlines the parallel algorithms used in this implementation, and provides a summary of the modifications made to QUICKSILVER. It also highlights a series of benchmark simulations which have been run with the new code that illustrate its performance and parallel efficiency. These calculations have up to a billion grid cells and particles and were run on thousands of processors. This report also serves as a user manual for people wishing to run parallel QUICKSILVER

The massive transformation in Ti-Al alloys: mechanistic observations

International Nuclear Information System (INIS)

Zhang, X.D.; Godfrey, S.; Weaver, M.; Strangwood, M.; Kaufman, M.J.; Loretto, M.H.

1996-01-01

The massive α→γ m transformation, as observed using analytical transmission electron microscopy, in Ti-49Al, Ti-48Al-2Nb-2Mn, Ti-55Al-25Ta and Ti-50Al-20Ta alloys is described. Conventional solution heating and quenching experiments have been combined with the more rapid quenching possible using electron beam melting in order to provide further insight into the early stages of the transformation of these alloys. It is shown that the γ develops first at grain boundaries as lamellae in one of the grains and that these lamellae intersect and spread into the adjacent grain in a massive manner. Consequently, there is no orientation relationship between the massive gamma (γ m ) and the grain being consumed whereas there is the expected relation between the γ m and the first grain which is inherited from the lamellae. It is further shown that the γ m grows as an f.c.c. phase after initially growing with the L1 0 structure. Furthermore, it is shown that the massive f.c.c. phase then orders to the L1 0 structure producing APDB-like defects which are actually thin 90 degree domains separating adjacent domains that have the same orientation yet are out of phase. The advancing γ m interface tends to facet parallel either to one of its four {111} planes or to the basal plane in the grain being consumed by impinging on existing γ lamellae. Thin microtwins and α 2 platelets then form in the γ m presumably due, respectively, to transformation stresses and supersaturation of the γ m with titanium for alloys containing ∼48% Al; indeed, there is a local depletion in aluminium across the α 2 platelets as determined using fine probe microanalysis

Radiation-magnetohydrodynamics of fusion plasmas on parallel supercomputers

International Nuclear Information System (INIS)

Yasar, O.; Moses, G.A.; Tautges, T.J.

1993-01-01

A parallel computational model to simulate fusion plasmas in the radiation-magnetohydrodynamics (R-MHD) framework is presented. Plasmas are often treated in a fluid dynamics context (magnetohydrodynamics, MHD), but when the flow field is coupled with the radiation field it falls into a more complex category, radiation magnetohydrodynamics (R-MHD), where the interaction between the flow field and the radiation field is nonlinear. The solution for the radiation field usually dominates the R-MHD computation. To solve for the radiation field, one usually chooses the S N discrete ordinates method (a deterministic method) rather than the Monte Carlo method if the geometry is not complex. The discrete ordinates method on a massively parallel processor (Intel iPSC/860) is implemented. The speedup is 14 for a run on 16 processors and the performance is 3.7 times better than a single CRAY YMP processor implementation. (orig./DG)

Linear precoding based on polynomial expansion: reducing complexity in massive MIMO

KAUST Repository

Mueller, Axel; Kammoun, Abla; Bjö rnson, Emil; Debbah, Mé rouane

2016-01-01

By deriving new random matrix results, we obtain a deterministic expression for the asymptotic signal-to-interference-and-noise ratio (SINR) achieved by TPE precoding in massive MIMO systems. Furthermore, we provide a closed-form expression for the polynomial coefficients that maximizes this SINR. To maintain a fixed per-user 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 the signal-to-noise ratio.

Dynamo: A Runtime Codesign Environment

National Research Council Canada - National Science Library

Quinn, Heather; Leeser, Miriam; Smith-King, L. A

2004-01-01

.... Signal and image processing applications are especially attractive for implementation on FPGAs as their computationally intensive and massively parallel algorithms can effectively take advantage...

Massive Submucosal Ganglia in Colonic Inertia.

Science.gov (United States)

Naemi, Kaveh; Stamos, Michael J; Wu, Mark Li-Cheng

2018-02-01

- Colonic inertia is a debilitating form of primary chronic constipation with unknown etiology and diagnostic criteria, often requiring pancolectomy. We have occasionally observed massively enlarged submucosal ganglia containing at least 20 perikarya, in addition to previously described giant ganglia with greater than 8 perikarya, in cases of colonic inertia. These massively enlarged ganglia have yet to be formally recognized. - To determine whether such "massive submucosal ganglia," defined as ganglia harboring at least 20 perikarya, characterize colonic inertia. - We retrospectively reviewed specimens from colectomies of patients with colonic inertia and compared the prevalence of massive submucosal ganglia occurring in this setting to the prevalence of massive submucosal ganglia occurring in a set of control specimens from patients lacking chronic constipation. - Seven of 8 specimens affected by colonic inertia harbored 1 to 4 massive ganglia, for a total of 11 massive ganglia. One specimen lacked massive ganglia but had limited sampling and nearly massive ganglia. Massive ganglia occupied both superficial and deep submucosal plexus. The patient with 4 massive ganglia also had 1 mitotically active giant ganglion. Only 1 massive ganglion occupied the entire set of 10 specimens from patients lacking chronic constipation. - We performed the first, albeit distinctly small, study of massive submucosal ganglia and showed that massive ganglia may be linked to colonic inertia. Further, larger studies are necessary to determine whether massive ganglia are pathogenetic or secondary phenomena, and whether massive ganglia or mitotically active ganglia distinguish colonic inertia from other types of chronic constipation.

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.

Ultrafast Nonlinear Signal Processing in Silicon Waveguides

DEFF Research Database (Denmark)

Oxenløwe, Leif Katsuo; Mulvad, Hans Christian Hansen; Hu, Hao

2012-01-01

We describe recent demonstrations of exploiting highly nonlinear silicon waveguides for ultrafast optical signal processing. We describe wavelength conversion and serial-to-parallel conversion of 640 Gbit/s data signals and 1.28 Tbit/s demultiplexing and all-optical sampling.......We describe recent demonstrations of exploiting highly nonlinear silicon waveguides for ultrafast optical signal processing. We describe wavelength conversion and serial-to-parallel conversion of 640 Gbit/s data signals and 1.28 Tbit/s demultiplexing and all-optical sampling....

High Performance Parallel Processing Project: Industrial computing initiative. Progress reports for fiscal year 1995

Energy Technology Data Exchange (ETDEWEB)

Koniges, A.

1996-02-09

This project is a package of 11 individual CRADA`s plus hardware. This innovative project established a three-year multi-party collaboration that is significantly accelerating the availability of commercial massively parallel processing computing software technology to U.S. government, academic, and industrial end-users. This report contains individual presentations from nine principal investigators along with overall program information.

Rubus: A compiler for seamless and extensible parallelism

Science.gov (United States)

Adnan, Muhammad; Aslam, Faisal; Sarwar, Syed Mansoor

2017-01-01

Nowadays, a typical processor may have multiple processing cores on a single chip. Furthermore, a special purpose processing unit called Graphic Processing Unit (GPU), originally designed for 2D/3D games, is now available for general purpose use in computers and mobile devices. However, the traditional programming languages which were designed to work with machines having single core CPUs, cannot utilize the parallelism available on multi-core processors efficiently. Therefore, to exploit the extraordinary processing power of multi-core processors, researchers are working on new tools and techniques to facilitate parallel programming. To this end, languages like CUDA and OpenCL have been introduced, which can be used to write code with parallelism. The main shortcoming of these languages is that programmer needs to specify all the complex details manually in order to parallelize the code across multiple cores. Therefore, the code written in these languages is difficult to understand, debug and maintain. Furthermore, to parallelize legacy code can require rewriting a significant portion of code in CUDA or OpenCL, which can consume significant time and resources. Thus, the amount of parallelism achieved is proportional to the skills of the programmer and the time spent in code optimizations. This paper proposes a new open source compiler, Rubus, to achieve seamless parallelism. The Rubus compiler relieves the programmer from manually specifying the low-level details. It analyses and transforms a sequential program into a parallel program automatically, without any user intervention. This achieves massive speedup and better utilization of the underlying hardware without a programmer’s expertise in parallel programming. For five different benchmarks, on average a speedup of 34.54 times has been achieved by Rubus as compared to Java on a basic GPU having only 96 cores. Whereas, for a matrix multiplication benchmark the average execution speedup of 84 times has been

Rubus: A compiler for seamless and extensible parallelism.

Directory of Open Access Journals (Sweden)

Muhammad Adnan

Full Text Available Nowadays, a typical processor may have multiple processing cores on a single chip. Furthermore, a special purpose processing unit called Graphic Processing Unit (GPU, originally designed for 2D/3D games, is now available for general purpose use in computers and mobile devices. However, the traditional programming languages which were designed to work with machines having single core CPUs, cannot utilize the parallelism available on multi-core processors efficiently. Therefore, to exploit the extraordinary processing power of multi-core processors, researchers are working on new tools and techniques to facilitate parallel programming. To this end, languages like CUDA and OpenCL have been introduced, which can be used to write code with parallelism. The main shortcoming of these languages is that programmer needs to specify all the complex details manually in order to parallelize the code across multiple cores. Therefore, the code written in these languages is difficult to understand, debug and maintain. Furthermore, to parallelize legacy code can require rewriting a significant portion of code in CUDA or OpenCL, which can consume significant time and resources. Thus, the amount of parallelism achieved is proportional to the skills of the programmer and the time spent in code optimizations. This paper proposes a new open source compiler, Rubus, to achieve seamless parallelism. The Rubus compiler relieves the programmer from manually specifying the low-level details. It analyses and transforms a sequential program into a parallel program automatically, without any user intervention. This achieves massive speedup and better utilization of the underlying hardware without a programmer's expertise in parallel programming. For five different benchmarks, on average a speedup of 34.54 times has been achieved by Rubus as compared to Java on a basic GPU having only 96 cores. Whereas, for a matrix multiplication benchmark the average execution speedup of 84

New massive gravity

NARCIS (Netherlands)

Bergshoeff, Eric A.; Hohm, Olaf; Townsend, Paul K.

2012-01-01

We present a brief review of New Massive Gravity, which is a unitary theory of massive gravitons in three dimensions obtained by considering a particular combination of the Einstein-Hilbert and curvature squared terms.

Massive-MIMO Sparse Uplink Channel Estimation Using Implicit Training and Compressed Sensing

Directory of Open Access Journals (Sweden)

Babar Mansoor

2017-01-01

Full Text Available Massive multiple-input multiple-output (massive-MIMO is foreseen as a potential technology for future 5G cellular communication networks due to its substantial benefits in terms of increased spectral and energy efficiency. These advantages of massive-MIMO are a consequence of equipping the base station (BS with quite a large number of antenna elements, thus resulting in an aggressive spatial multiplexing. In order to effectively reap the benefits of massive-MIMO, an adequate estimate of the channel impulse response (CIR between each transmit–receive link is of utmost importance. It has been established in the literature that certain specific multipath propagation environments lead to a sparse structured CIR in spatial and/or delay domains. In this paper, implicit training and compressed sensing based CIR estimation techniques are proposed for the case of massive-MIMO sparse uplink channels. In the proposed superimposed training (SiT based techniques, a periodic and low power training sequence is superimposed (arithmetically added over the information sequence, thus avoiding any dedicated time/frequency slots for the training sequence. For the estimation of such massive-MIMO sparse uplink channels, two greedy pursuits based compressed sensing approaches are proposed, viz: SiT based stage-wise orthogonal matching pursuit (SiT-StOMP and gradient pursuit (SiT-GP. In order to demonstrate the validity of proposed techniques, a performance comparison in terms of normalized mean square error (NCMSE and bit error rate (BER is performed with a notable SiT based least squares (SiT-LS channel estimation technique. The effect of channels’ sparsity, training-to-information power ratio (TIR and signal-to-noise ratio (SNR on BER and NCMSE performance of proposed schemes is thoroughly studied. For a simulation scenario of: 4 × 64 massive-MIMO with a channel sparsity level of 80 % and signal-to-noise ratio (SNR of 10 dB , a performance gain of 18 dB and 13 d

STABLE ISOTOPE GEOCHEMISTRY OF MASSIVE ICE

Directory of Open Access Journals (Sweden)

Yurij K. Vasil’chuk

2016-01-01

Full Text Available The paper summarises stable-isotope research on massive ice in the Russian and North American Arctic, and includes the latest understanding of massive-ice formation. A new classification of massive-ice complexes is proposed, encompassing the range and variabilityof massive ice. It distinguishes two new categories of massive-ice complexes: homogeneousmassive-ice complexes have a similar structure, properties and genesis throughout, whereasheterogeneous massive-ice complexes vary spatially (in their structure and properties andgenetically within a locality and consist of two or more homogeneous massive-ice bodies.Analysis of pollen and spores in massive ice from Subarctic regions and from ice and snow cover of Arctic ice caps assists with interpretation of the origin of massive ice. Radiocarbon ages of massive ice and host sediments are considered together with isotope values of heavy oxygen and deuterium from massive ice plotted at a uniform scale in order to assist interpretation and correlation of the ice.

Parallel nanostructuring of GeSbTe film with particle mask

Energy Technology Data Exchange (ETDEWEB)

Wang, Z.B.; Hong, M.H.; Wang, Q.F.; Chong, T.C. [Data Storage Institute, DSI Building, 5 Engineering Drive 1, 117608, Singapore (Singapore); Department of Electrical and Computer Engineering, National University of Singapore, 119260, Singapore (Singapore); Luk' yanchuk, B.S.; Huang, S.M.; Shi, L.P. [Data Storage Institute, DSI Building, 5 Engineering Drive 1, 117608, Singapore (Singapore)

2004-09-01

Parallel nanostructuring of a GeSbTe film may significantly improve the recording performance in data storage. In this paper, a method that permits direct and massively parallel nanopatterning of the substrate surface by laser irradiation is investigated. Polystyrene spherical particles were deposited on the surface in a monolayer array by self-assembly. The array was then irradiated with a 248-nm KrF laser. A sub-micron nanodent array can be obtained after single-pulse irradiation. These nanodents change their shapes at different laser energies. The optical near-field distribution around the particles was calculated according to the exact solution of the light-scattering problem. The influence of the presence of the substrate on the optical near field was also studied. The mechanisms for the generation of the nanodent structures are discussed. (orig.)

Parallel programming practical aspects, models and current limitations

CERN Document Server

Tarkov, Mikhail S

2014-01-01

Parallel programming is designed for the use of parallel computer systems for solving time-consuming problems that cannot be solved on a sequential computer in a reasonable time. These problems can be divided into two classes: 1. Processing large data arrays (including processing images and signals in real time)2. Simulation of complex physical processes and chemical reactions For each of these classes, prospective methods are designed for solving problems. For data processing, one of the most promising technologies is the use of artificial neural networks. Particles-in-cell method and cellular automata are very useful for simulation. Problems of scalability of parallel algorithms and the transfer of existing parallel programs to future parallel computers are very acute now. An important task is to optimize the use of the equipment (including the CPU cache) of parallel computers. Along with parallelizing information processing, it is essential to ensure the processing reliability by the relevant organization ...

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

Massive Black Hole Mergers: Can We "See" what LISA will "Hear"?

Science.gov (United States)

Centrella, Joan

2010-01-01

The final merger of massive black holes produces strong gravitational radiation that can be detected by the space-borne LISA. If the black hole merger takes place in the presence of gas and magnetic fields, various types of electromagnetic signals may also be produced. Modeling such electromagnetic counterparts of the final merger requires evolving the behavior of both gas and fields in the strong-field regions around the black holes. We will review current efforts to simulate these systems, and discuss possibilities for observing the electromagnetic signals they produce.

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.

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.

Massive graviton geons

Science.gov (United States)

Aoki, Katsuki; Maeda, Kei-ichi; Misonoh, Yosuke; Okawa, Hirotada

2018-02-01

We find vacuum solutions such that massive gravitons are confined in a local spacetime region by their gravitational energy in asymptotically flat spacetimes in the context of the bigravity theory. We call such self-gravitating objects massive graviton geons. The basic equations can be reduced to the Schrödinger-Poisson equations with the tensor "wave function" in the Newtonian limit. We obtain a nonspherically symmetric solution with j =2 , ℓ=0 as well as a spherically symmetric solution with j =0 , ℓ=2 in this system where j is the total angular momentum quantum number and ℓ is the orbital angular momentum quantum number, respectively. The energy eigenvalue of the Schrödinger equation in the nonspherical solution is smaller than that in the spherical solution. We then study the perturbative stability of the spherical solution and find that there is an unstable mode in the quadrupole mode perturbations which may be interpreted as the transition mode to the nonspherical solution. The results suggest that the nonspherically symmetric solution is the ground state of the massive graviton geon. The massive graviton geons may decay in time due to emissions of gravitational waves but this timescale can be quite long when the massive gravitons are nonrelativistic and then the geons can be long-lived. We also argue possible prospects of the massive graviton geons: applications to the ultralight dark matter scenario, nonlinear (in)stability of the Minkowski spacetime, and a quantum transition of the spacetime.

Molecular dynamics beyonds the limits: Massive scaling on 72 racks of a BlueGene/P and supercooled glass dynamics of a 1 billion particles system

KAUST Repository

Allsopp, Nicholas; Ruocco, Giancarlo; Fratalocchi, Andrea

2012-01-01

We report scaling results on the world's largest supercomputer of our recently developed Billions-Body Molecular Dynamics (BBMD) package, which was especially designed for massively parallel simulations of the short-range atomic dynamics

A PC parallel port button box provides millisecond response time accuracy under Linux.

Science.gov (United States)

Stewart, Neil

2006-02-01

For psychologists, it is sometimes necessary to measure people's reaction times to the nearest millisecond. This article describes how to use the PC parallel port to receive signals from a button box to achieve millisecond response time accuracy. The workings of the parallel port, the corresponding port addresses, and a simple Linux program for controlling the port are described. A test of the speed and reliability of button box signal detection is reported. If the reader is moderately familiar with Linux, this article should provide sufficient instruction for him or her to build and test his or her own parallel port button box. This article also describes how the parallel port could be used to control an external apparatus.

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 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.

The Acoustic and Peceptual Effects of Series and Parallel Processing

Directory of Open Access Journals (Sweden)

Melinda C. Anderson

2009-01-01

Full Text Available Temporal envelope (TE cues provide a great deal of speech information. This paper explores how spectral subtraction and dynamic-range compression gain modifications affect TE fluctuations for parallel and series configurations. In parallel processing, algorithms compute gains based on the same input signal, and the gains in dB are summed. In series processing, output from the first algorithm forms the input to the second algorithm. Acoustic measurements show that the parallel arrangement produces more gain fluctuations, introducing more changes to the TE than the series configurations. Intelligibility tests for normal-hearing (NH and hearing-impaired (HI listeners show (1 parallel processing gives significantly poorer speech understanding than an unprocessed (UNP signal and the series arrangement and (2 series processing and UNP yield similar results. Speech quality tests show that UNP is preferred to both parallel and series arrangements, although spectral subtraction is the most preferred. No significant differences exist in sound quality between the series and parallel arrangements, or between the NH group and the HI group. These results indicate that gain modifications affect intelligibility and sound quality differently. Listeners appear to have a higher tolerance for gain modifications with regard to intelligibility, while judgments for sound quality appear to be more affected by smaller amounts of gain modification.

SIERRA Mechanics, an emerging massively parallel HPC capability, for use in coupled THMC analyses of HLW repositories in clay/shale

International Nuclear Information System (INIS)

Bean, J.E.; Sanchez, M.; Arguello, J.G.

2012-01-01

Document available in extended abstract form only. Because, until recently, U.S. efforts had been focused on the volcanic tuff site at Yucca Mountain, radioactive waste disposal in U.S. clay/shale formations has not been considered for many years. However, advances in multi-physics computational modeling and research into clay mineralogy continue to improve the scientific basis for assessing nuclear waste repository performance in such formations. Disposal of high-level radioactive waste (HLW) in suitable clay/shale formations is attractive because the material is essentially impermeable and self-sealing, conditions are chemically reducing, and sorption tends to prevent radionuclide transport. Vertically and laterally extensive shale and clay formations exist in multiple locations in the contiguous 48 states. This paper describes an emerging massively parallel (MP) high performance computing (HPC) capability - SIERRA Mechanics - that is applicable to the simulation of coupled-physics processes occurring within a potential clay/shale repository for disposal of HLW within the U.S. The SIERRA Mechanics code development project has been underway at Sandia National Laboratories for approximately the past decade under the auspices of the U.S. Department of Energy's Advanced Scientific Computing (ASC) program. SIERRA Mechanics was designed and developed from its inception to run on the latest and most sophisticated massively parallel computing hardware, with the capability to span the hardware range from single workstations to systems with thousands of processors. The foundation of SIERRA Mechanics is the SIERRA tool-kit, which provides finite element application-code services such as: (1) mesh and field data management, both parallel and distributed; (2) transfer operators for mapping field variables from one mechanics application to another; (3) a solution controller for code coupling; and (4) included third party libraries (e.g., solver libraries, communications

Hot stars in young massive clusters: Mapping the current Galactic metallicity

Science.gov (United States)

de la Fuente, Diego; Najarro, Francisco; Davies, Ben; Trombley, Christine; Figer, Donald F.; Herrero, Artemio

2013-06-01

Young Massive Clusters (YMCs) with ages guarantee that these objects present the same chemical composition than the surrounding environment where they are recently born. Finally, the YMCs host very massive stars whose extreme luminosities allow to accomplish detailed spectroscopic analyses even in the most distant regions of the Milky Way. Our group has carried out ISAAC/VLT spectroscopic observations of hot massive stars belonging to several YMCs in different locations around the Galactic disk. As a result, high signal-to-noise, near-infrared spectra of dozens of blue massive stars (including many OB supergiants, Wolf-Rayet stars and a B hypergiant) have been obtained. These data are fully reduced, and NLTE spherical atmosphere modeling is in process. Several line diagnostics will be combined in order to calculate metal abundances accurately for each cluster. The diverse locations of the clusters will allow us to draw a two-dimensional chemical map of the Galactic disk for the first time. The study of the radial and azimuthal variations of elemental abundances will be crucial for understanding the chemical evolution of the Milky Way. Particularly, the ratio between Fe-peak and alpha elements will constitute a powerful tool to investigate the past stellar populations that originated the current Galactic chemistry.

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.

The design and development of massive BES job submit and management system

International Nuclear Information System (INIS)

Shi Jingyan; Liang Dong; Sun Gongxing; Chen Gang

2010-01-01

The system was designed to provide an easy and efficient way for the physicists to run their physical jobs. The system sends jobs to the different computing backend under the request of the user, besides, the system can monitor the jobs status, re-submit the job automatically. The BES job is the typical data massive calculation. To realize the parallelized job running, the big job was split into many sub-jobs to be run on many worknodes at the same time. Web Service is adopted to provide users flexible interface. (authors)

Modulation, plasticity and pathophysiology of the parallel fiber-Purkinje cell synapse

Directory of Open Access Journals (Sweden)

Eriola Hoxha

2016-11-01

Full Text Available The parallel fiber-Purkinje cell synapse represents the point of maximal signal divergence in the cerebellar cortex with an estimated number of about 60 billion synaptic contacts in the rat and 100,000 billions in humans. At the same time, the Purkinje cell dendritic tree is a site of remarkable convergence of more than 100,000 parallel fiber synapses. Parallel fibers activity generates fast postsynaptic currents via AMPA receptors, and slower signals, mediated by mGlu1 receptors, resulting in Purkinje cell depolarization accompanied by sharp calcium elevation within dendritic regions. Long-term depression and long-term potentiation have been widely described for the parallel fiber-Purkinje cell synapse and have been proposed as mechanisms for motor learning. The mechanisms of induction for LTP and LTD involve different signaling mechanisms within the presynaptic terminal and/or at the postsynaptic site, promoting enduring modification in the neurotransmitter release and change in responsiveness to the neurotransmitter. The parallel fiber-Purkinje cell synapse is finely modulated by several neurotransmitters, including serotonin, noradrenaline, and acetylcholine. The ability of these neuromodulators to gate LTP and LTD at the parallel fiber-Purkinje cell synapse could, at least in part, explain their effect on cerebellar-dependent learning and memory paradigms. Overall, these findings have important implications for understanding the cerebellar involvement in a series of pathological conditions, ranging from ataxia to autism. For example, parallel fiber-Purkinje cell synapse dysfunctions have been identified in several murine models of spinocerebellar ataxia (SCA types 1, 3, 5 and 27. In some cases, the defect is specific for the AMPA receptor signaling (SCA27, while in others the mGlu1 pathway is affected (SCA1, 3, 5. Interestingly, the parallel fiber-Purkinje cell synapse has been shown to be hyper-functional in a mutant mouse model of autism

Evaluation of dual-source parallel RF excitation for diffusion-weighted whole-body MR imaging with background body signal suppression at 3.0 T

Energy Technology Data Exchange (ETDEWEB)

Muertz, Petra, E-mail: petra.muertz@ukb.uni-bonn.de [Department of Radiology, University of Bonn (Germany); Kaschner, Marius, E-mail: marius.kaschner@ukb.uni-bonn.de [Department of Radiology, University of Bonn (Germany); Traeber, Frank, E-mail: frank.traeber@ukb.uni-bonn.de [Department of Radiology, University of Bonn (Germany); Kukuk, Guido M., E-mail: guido.kukuk@ukb.uni-bonn.de [Department of Radiology, University of Bonn (Germany); Buedenbender, Sarah M., E-mail: sarah_m_buedenbender@yahoo.de [Department of Radiology, University of Bonn (Germany); Skowasch, Dirk, E-mail: dirk.skowasch@ukb.uni-bonn.de [Department of Medicine, University of Bonn (Germany); Gieseke, Juergen, E-mail: juergen.gieseke@philips.com [Philips Healthcare, Best (Netherlands); Department of Radiology, University of Bonn (Germany); Schild, Hans H., E-mail: hans.schild@ukb.uni-bonn.de [Department of Radiology, University of Bonn (Germany); Willinek, Winfried A., E-mail: winfried.willinek@ukb.uni-bonn.de [Department of Radiology, University of Bonn (Germany)

2012-11-15

Purpose: To evaluate the use of dual-source parallel RF excitation (TX) for diffusion-weighted whole-body MRI with background body signal suppression (DWIBS) at 3.0 T. Materials and methods: Forty consecutive patients were examined on a clinical 3.0-T MRI system using a diffusion-weighted (DW) spin-echo echo-planar imaging sequence with a combination of short TI inversion recovery and slice-selective gradient reversal fat suppression. DWIBS of the neck (n = 5), thorax (n = 8), abdomen (n = 6) and pelvis (n = 21) was performed both with TX (2:56 min) and with standard single-source RF excitation (4:37 min). The quality of DW images and reconstructed inverted maximum intensity projections was visually judged by two readers (blinded to acquisition technique). Signal homogeneity and fat suppression were scored as 'improved', 'equal', 'worse' or 'ambiguous'. Moreover, the apparent diffusion coefficient (ADC) values were measured in muscles, urinary bladder, lymph nodes and lesions. Results: By the use of TX, signal homogeneity was 'improved' in 25/40 and 'equal' in 15/40 cases. Fat suppression was 'improved' in 17/40 and 'equal' in 23/40 cases. These improvements were statistically significant (p < 0.001, Wilcoxon signed-rank test). In five patients, fluid-related dielectric shading was present, which improved remarkably. The ADC values did not significantly differ for the two RF excitation methods (p = 0.630 over all data, pairwise Student's t-test). Conclusion: Dual-source parallel RF excitation improved image quality of DWIBS at 3.0 T with respect to signal homogeneity and fat suppression, reduced scan time by approximately one-third, and did not influence the measured ADC values.

Multilayer control for inverters in parallel operation without signal interconnection

DEFF Research Database (Denmark)

Hua, Ming; Hu, Haibing; Xing, Yan

2011-01-01

A multilayer control is proposed for inverters with wireless parallel operation in this paper. The control is embedded in every inverter respectively and consists of three layers. The first layer is based on an improved droop method, which shares the active and reactive power in each module...

Parallel peak pruning for scalable SMP contour tree computation

Energy Technology Data Exchange (ETDEWEB)

Carr, Hamish A. [Univ. of Leeds (United Kingdom); Weber, Gunther H. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Davis, CA (United States); Sewell, Christopher M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Ahrens, James P. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-03-09

As data sets grow to exascale, automated data analysis and visualisation are increasingly important, to intermediate human understanding and to reduce demands on disk storage via in situ analysis. Trends in architecture of high performance computing systems necessitate analysis algorithms to make effective use of combinations of massively multicore and distributed systems. One of the principal analytic tools is the contour tree, which analyses relationships between contours to identify features of more than local importance. Unfortunately, the predominant algorithms for computing the contour tree are explicitly serial, and founded on serial metaphors, which has limited the scalability of this form of analysis. While there is some work on distributed contour tree computation, and separately on hybrid GPU-CPU computation, there is no efficient algorithm with strong formal guarantees on performance allied with fast practical performance. Here in this paper, we report the first shared SMP algorithm for fully parallel contour tree computation, withfor-mal guarantees of O(lgnlgt) parallel steps and O(n lgn) work, and implementations with up to 10x parallel speed up in OpenMP and up to 50x speed up in NVIDIA Thrust.

Massive Black-Hole Binary Mergers: Dynamics, Environments & Expected Detections

Science.gov (United States)

Kelley, Luke Zoltan

2018-05-01

This thesis studies the populations and dynamics of massive black-hole binaries and their mergers, and explores the implications for electromagnetic and gravitational-wave signals that will be detected in the near future. Massive black-holes (MBH) reside in the centers of galaxies, and when galaxies merge, their MBH interact and often pair together. We base our study on the populations of MBH and galaxies from the `Illustris' cosmological hydrodynamic simulations. The bulk of the binary merger dynamics, however, are unresolved in cosmological simulations. We implement a suite of comprehensive physical models for the merger process, like dynamical friction and gravitational wave emission, which are added in post-processing. Contrary to many previous studies, we find that the most massive binaries with near equal-mass companions are the most efficient at coalescing; though the process still typically takes gigayears.From the data produced by these MBH binary populations and their dynamics, we calculate the expected gravitational wave (GW) signals: both the stochastic, GW background of countless unresolved sources, and the GW foreground of individually resolvable binaries which resound above the noise. Ongoing experiments, called pulsar timing arrays, are sensitive to both of these types of signals. We find that, while the current lack of detections is unsurprising, both the background and foreground will plausibly be detected in the next decade. Unlike previous studies which have predicted the foreground to be significantly harder to detect than the background, we find their typical amplitudes are comparable.With traditional electromagnetic observations, there has also been a dearth of confirmed detections of MBH binary systems. We use our binaries, combined with models of emission from accreting MBH systems, to make predictions for the occurrence rate of systems observable using photometric, periodic-variability surveys. These variables should be detectable in

A Robust Parallel Algorithm for Combinatorial Compressed Sensing

Science.gov (United States)

Mendoza-Smith, Rodrigo; Tanner, Jared W.; Wechsung, Florian

2018-04-01

In previous work two of the authors have shown that a vector $x \\in \\mathbb{R}^n$ with at most $k Parallel-$\\ell_0$ decoding algorithm, where $\\mathrm{nnz}(A)$ denotes the number of nonzero entries in $A \\in \\mathbb{R}^{m \\times n}$. In this paper we present the Robust-$\\ell_0$ decoding algorithm, which robustifies Parallel-$\\ell_0$ when the sketch $Ax$ is corrupted by additive noise. This robustness is achieved by approximating the asymptotic posterior distribution of values in the sketch given its corrupted measurements. We provide analytic expressions that approximate these posteriors under the assumptions that the nonzero entries in the signal and the noise are drawn from continuous distributions. Numerical experiments presented show that Robust-$\\ell_0$ is superior to existing greedy and combinatorial compressed sensing algorithms in the presence of small to moderate signal-to-noise ratios in the setting of Gaussian signals and Gaussian additive noise.

Light weakly interacting massive particles

Science.gov (United States)

Gelmini, Graciela B.

2017-08-01

Light weakly interacting massive particles (WIMPs) are dark matter particle candidates with weak scale interaction with the known particles, and mass in the GeV to tens of GeV range. Hints of light WIMPs have appeared in several dark matter searches in the last decade. The unprecedented possible coincidence into tantalizingly close regions of mass and cross section of four separate direct detection experimental hints and a potential indirect detection signal in gamma rays from the galactic center, aroused considerable interest in our field. Even if these hints did not so far result in a discovery, they have had a significant impact in our field. Here we review the evidence for and against light WIMPs as dark matter candidates and discuss future relevant experiments and observations.

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.

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.

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/.

Using pre-distorted PAM-4 signal and parallel resistance circuit to enhance the passive solar cell based visible light communication

Science.gov (United States)

Wang, Hao-Yu; Wu, Jhao-Ting; Chow, Chi-Wai; Liu, Yang; Yeh, Chien-Hung; Liao, Xin-Lan; Lin, Kun-Hsien; Wu, Wei-Liang; Chen, Yi-Yuan

2018-01-01

Using solar cell (or photovoltaic cell) for visible light communication (VLC) is attractive. Apart from acting as a VLC receiver (Rx), the solar cell can provide energy harvesting. This can be used in self-powered smart devices, particularly in the emerging ;Internet of Things (IoT); networks. Here, we propose and demonstrate for the first time using pre-distortion pulse-amplitude-modulation (PAM)-4 signal and parallel resistance circuit to enhance the transmission performance of solar cell Rx based VLC. Pre-distortion is a simple non-adaptive equalization technique that can significantly mitigate the slow charging and discharging of the solar cell. The equivalent circuit model of the solar cell and the operation of using parallel resistance to increase the bandwidth of the solar cell are discussed. By using the proposed schemes, the experimental results show that the data rate of the solar cell Rx based VLC can increase from 20 kbit/s to 1.25 Mbit/s (about 60 times) with the bit error-rate (BER) satisfying the 7% forward error correction (FEC) limit.

Algorithmically specialized parallel computers

CERN Document Server

Snyder, Lawrence; Gannon, Dennis B

1985-01-01

Algorithmically Specialized Parallel Computers focuses on the concept and characteristics of an algorithmically specialized computer.This book discusses the algorithmically specialized computers, algorithmic specialization using VLSI, and innovative architectures. The architectures and algorithms for digital signal, speech, and image processing and specialized architectures for numerical computations are also elaborated. Other topics include the model for analyzing generalized inter-processor, pipelined architecture for search tree maintenance, and specialized computer organization for raster

A parallel algorithm for solving the integral form of the discrete ordinates equations

International Nuclear Information System (INIS)

Zerr, R. J.; Azmy, Y. Y.

2009-01-01

The integral form of the discrete ordinates equations involves a system of equations that has a large, dense coefficient matrix. The serial construction methodology is presented and properties that affect the execution times to construct and solve the system are evaluated. Two approaches for massively parallel implementation of the solution algorithm are proposed and the current results of one of these are presented. The system of equations May be solved using two parallel solvers-block Jacobi and conjugate gradient. Results indicate that both methods can reduce overall wall-clock time for execution. The conjugate gradient solver exhibits better performance to compete with the traditional source iteration technique in terms of execution time and scalability. The parallel conjugate gradient method is synchronous, hence it does not increase the number of iterations for convergence compared to serial execution, and the efficiency of the algorithm demonstrates an apparent asymptotic decline. (authors)

Magnetic Integration for Parallel Interleaved VSCs Connected in a Whiffletree Configuration

DEFF Research Database (Denmark)

Gohil, Ghanshyamsinh Vijaysinh; Bede, Lorand; Teodorescu, Remus

2016-01-01

The Voltage Source Converters (VSCs) are often connected in parallel to realize a high current rating. In such systems, the harmonic quality of the output voltage can be improved by interleaving the carrier signals of the parallel VSCs. However, an additional inductive filter is often required...

Implementing a low-latency parallel graphic equalizer with heterogeneous computing

NARCIS (Netherlands)

Norilo, Vesa; Verstraelen, Martinus Johannes Wilhelmina; Valimaki, Vesa; Svensson, Peter; Kristiansen, Ulf

2015-01-01

This paper describes the implementation of a recently introduced parallel graphic equalizer (PGE) in a heterogeneous way. The control and audio signal processing parts of the PGE are distributed to a PC and to a signal processor, of WaveCore architecture, respectively. This arrangement is

Massive Conformal Gravity

International Nuclear Information System (INIS)

Faria, F. F.

2014-01-01

We construct a massive theory of gravity that is invariant under conformal transformations. The massive action of the theory depends on the metric tensor and a scalar field, which are considered the only field variables. We find the vacuum field equations of the theory and analyze its weak-field approximation and Newtonian limit.

Massive gravity from bimetric gravity

International Nuclear Information System (INIS)

Baccetti, Valentina; Martín-Moruno, Prado; Visser, Matt

2013-01-01

We discuss the subtle relationship between massive gravity and bimetric gravity, focusing particularly on the manner in which massive gravity may be viewed as a suitable limit of bimetric gravity. The limiting procedure is more delicate than currently appreciated. Specifically, this limiting procedure should not unnecessarily constrain the background metric, which must be externally specified by the theory of massive gravity itself. The fact that in bimetric theories one always has two sets of metric equations of motion continues to have an effect even in the massive gravity limit, leading to additional constraints besides the one set of equations of motion naively expected. Thus, since solutions of bimetric gravity in the limit of vanishing kinetic term are also solutions of massive gravity, but the contrary statement is not necessarily true, there is no complete continuity in the parameter space of the theory. In particular, we study the massive cosmological solutions which are continuous in the parameter space, showing that many interesting cosmologies belong to this class. (paper)

The position dependent influence that sensitivity correction processing gives the signal-to-noise ratio measurement in parallel imaging

International Nuclear Information System (INIS)

Murakami, Koichi; Yoshida, Koji; Yanagimoto, Shinichi

2012-01-01

We studied the position dependent influence that sensitivity correction processing gave the signal-to-noise ratio (SNR) measurement of parallel imaging (PI). Sensitivity correction processing that referred to the sensitivity distribution of the body coil improved regional uniformity more than the sensitivity uniformity correction filter with a fixed correction factor. In addition, the position dependent influence to give the SNR measurement in PI was different from the sensitivity correction processing. Therefore, if we divide SNR of the sensitivity correction processing image by SNR of the original image in each pixel and calculate SNR ratio, we can show the position dependent influence that sensitivity correction processing gives the SNR measurement in PI. It is with an index of the sensitivity correction processing precision. (author)

Identification of the first homozygous 1-bp deletion in GDF9 gene leading to primary ovarian insufficiency by using targeted massively parallel sequencing.

Science.gov (United States)

França, M M; Funari, M F A; Nishi, M Y; Narcizo, A M; Domenice, S; Costa, E M F; Lerario, A M; Mendonca, B B

2018-02-01

Targeted massively parallel sequencing (TMPS) has been used in genetic diagnosis for Mendelian disorders. In the past few years, the TMPS has identified new and already described genes associated with primary ovarian insufficiency (POI) phenotype. Here, we performed a targeted gene sequencing to find a genetic diagnosis in idiopathic cases of Brazilian POI cohort. A custom SureSelect XT DNA target enrichment panel was designed and the sequencing was performed on Illumina NextSeq sequencer. We identified 1 homozygous 1-bp deletion variant (c.783delC) in the GDF9 gene in 1 patient with POI. The variant was confirmed and segregated using Sanger sequencing. The c.783delC GDF9 variant changed an amino acid creating a premature termination codon (p.Ser262Hisfs*2). This variant was not present in all public databases (ExAC/gnomAD, NHLBI/EVS and 1000Genomes). Moreover, it was absent in 400 alleles from fertile Brazilian women screened by Sanger sequencing. The patient's mother and her unaffected sister carried the c.783delC variant in a heterozygous state, as expected for an autosomal recessive inheritance. Here, the TMPS identified the first homozygous 1-bp deletion variant in GDF9. This finding reveals a novel inheritance pattern of pathogenic variant in GDF9 associated with POI, thus improving the genetic diagnosis of this disorder. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

State-space-based harmonic stability analysis for paralleled grid-connected inverters

DEFF Research Database (Denmark)

Wang, Yanbo; Wang, Xiongfei; Chen, Zhe

2016-01-01

This paper addresses a state-space-based harmonic stability analysis of paralleled grid-connected inverters system. A small signal model of individual inverter is developed, where LCL filter, the equivalent delay of control system, and current controller are modeled. Then, the overall small signal...... model of paralleled grid-connected inverters is built. Finally, the state space-based stability analysis approach is developed to explain the harmonic resonance phenomenon. The eigenvalue traces associated with time delay and coupled grid impedance are obtained, which accounts for how the unstable...... inverter produces the harmonic resonance and leads to the instability of whole paralleled system. The proposed approach reveals the contributions of the grid impedance as well as the coupled effect on other grid-connected inverters under different grid conditions. Simulation and experimental 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.

Vaidya spacetime in massive gravity's rainbow

Directory of Open Access Journals (Sweden)

Yaghoub Heydarzade

2017-11-01

Full Text Available In this paper, we will analyze the energy dependent deformation of massive gravity using the formalism of massive gravity's rainbow. So, we will use the Vainshtein mechanism and the dRGT mechanism for the energy dependent massive gravity, and thus analyze a ghost free theory of massive gravity's rainbow. We study the energy dependence of a time-dependent geometry, by analyzing the radiating Vaidya solution in this theory of massive gravity's rainbow. The energy dependent deformation of this Vaidya metric will be performed using suitable rainbow functions.

Large Scale Parallel DNA Detection by Two-Dimensional Solid-State Multipore Systems.

Science.gov (United States)

Athreya, Nagendra Bala Murali; Sarathy, Aditya; Leburton, Jean-Pierre

2018-04-23

We describe a scalable device design of a dense array of multiple nanopores made from nanoscale semiconductor materials to detect and identify translocations of many biomolecules in a massively parallel detection scheme. We use molecular dynamics coupled to nanoscale device simulations to illustrate the ability of this device setup to uniquely identify DNA parallel translocations. We show that the transverse sheet currents along membranes are immune to the crosstalk effects arising from simultaneous translocations of biomolecules through multiple pores, due to their ability to sense only the local potential changes. We also show that electronic sensing across the nanopore membrane offers a higher detection resolution compared to ionic current blocking technique in a multipore setup, irrespective of the irregularities that occur while fabricating the nanopores in a two-dimensional membrane.

Parallel imaging for first-pass myocardial perfusion

NARCIS (Netherlands)

Irwan, Roy; Lubbers, Daniel D.; van der Vleuten, Pieter A.; Kappert, Peter; Gotte, Marco J. W.; Sijens, Paul E.

Two parallel imaging methods used for first-pass myocardial perfusion imaging were compared in terms of signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and image artifacts. One used adaptive Time-adaptive SENSitivity Encoding (TSENSE) and the other used GeneRalized Autocalibrating

Digital parallel-to-series pulse-train converter

Science.gov (United States)

Hussey, J.

1971-01-01

Circuit converts number represented as two level signal on n-bit lines to series of pulses on one of two lines, depending on sign of number. Converter accepts parallel binary input data and produces number of output pulses equal to number represented by input data.

An inherently parallel method for solving discretized diffusion equations

International Nuclear Information System (INIS)

Eccleston, B.R.; Palmer, T.S.

1999-01-01

A Monte Carlo approach to solving linear systems of equations is being investigated in the context of the solution of discretized diffusion equations. While the technique was originally devised decades ago, changes in computer architectures (namely, massively parallel machines) have driven the authors to revisit this technique. There are a number of potential advantages to this approach: (1) Analog Monte Carlo techniques are inherently parallel; this is not necessarily true to today's more advanced linear equation solvers (multigrid, conjugate gradient, etc.); (2) Some forms of this technique are adaptive in that they allow the user to specify locations in the problem where resolution is of particular importance and to concentrate the work at those locations; and (3) These techniques permit the solution of very large systems of equations in that matrix elements need not be stored. The user could trade calculational speed for storage if elements of the matrix are calculated on the fly. The goal of this study is to compare the parallel performance of Monte Carlo linear solvers to that of a more traditional parallelized linear solver. The authors observe the linear speedup that they expect from the Monte Carlo algorithm, given that there is no domain decomposition to cause significant communication overhead. Overall, PETSc outperforms the Monte Carlo solver for the test problem. The PETSc parallel performance improves with larger numbers of unknowns for a given number of processors. Parallel performance of the Monte Carlo technique is independent of the size of the matrix and the number of processes. They are investigating modifications to the scheme to accommodate matrix problems with positive off-diagonal elements. They are also currently coding an on-the-fly version of the algorithm to investigate the solution of very large linear systems

A longitudinal multi-bunch feedback system using parallel digital signal processors

International Nuclear Information System (INIS)

Sapozhnikov, L.; Fox, J.D.; Olsen, J.J.; Oxoby, G.; Linscott, I.; Drago, A.; Serio, M.

1994-01-01

A programmable longitudinal feedback system based on four AT ampersand T 1610 digital signal processors has been developed as a component of the PEP-II R ampersand D program. This longitudinal quick prototype is a proof of concept for the PEP-II system and implements full-speed bunch-by-bunch signal processing for storage rings with bunch spacings of 4 ns. The design incorporates a phase-detector-based front end that digitizes the oscillation phases of bunches at the 250 MHz crossing rate, four programmable signal processors that compute correction signals, and a 250-MHz hold buffer/kicker driver stage that applies correction signals back on the beam. The design implements a general-purpose, table-driven downsampler that allows the system to be operated at several accelerator facilities. The hardware architecture of the signal processing is described, and the software algorithms used in the feedback signal computation are discussed. The system configuration used for tests at the LBL Advanced Light Source is presented

Statistical Challenges in Modeling Big Brain Signals

KAUST Repository

Yu, Zhaoxia; Pluta, Dustin; Shen, Tong; Chen, Chuansheng; Xue, Gui; Ombao, Hernando

2017-01-01

Brain signal data are inherently big: massive in amount, complex in structure, and high in dimensions. These characteristics impose great challenges for statistical inference and learning. Here we review several key challenges, discuss possible

Performance modeling of parallel algorithms for solving neutron diffusion problems

International Nuclear Information System (INIS)

Azmy, Y.Y.; Kirk, B.L.

1995-01-01

Neutron diffusion calculations are the most common computational methods used in the design, analysis, and operation of nuclear reactors and related activities. Here, mathematical performance models are developed for the parallel algorithm used to solve the neutron diffusion equation on message passing and shared memory multiprocessors represented by the Intel iPSC/860 and the Sequent Balance 8000, respectively. The performance models are validated through several test problems, and these models are used to estimate the performance of each of the two considered architectures in situations typical of practical applications, such as fine meshes and a large number of participating processors. While message passing computers are capable of producing speedup, the parallel efficiency deteriorates rapidly as the number of processors increases. Furthermore, the speedup fails to improve appreciably for massively parallel computers so that only small- to medium-sized message passing multiprocessors offer a reasonable platform for this algorithm. In contrast, the performance model for the shared memory architecture predicts very high efficiency over a wide range of number of processors reasonable for this architecture. Furthermore, the model efficiency of the Sequent remains superior to that of the hypercube if its model parameters are adjusted to make its processors as fast as those of the iPSC/860. It is concluded that shared memory computers are better suited for this parallel algorithm than message passing computers

MassiveNuS: cosmological massive neutrino simulations

Science.gov (United States)

Liu, Jia; Bird, Simeon; Zorrilla Matilla, José Manuel; Hill, J. Colin; Haiman, Zoltán; Madhavacheril, Mathew S.; Petri, Andrea; Spergel, David N.

2018-03-01

The non-zero mass of neutrinos suppresses the growth of cosmic structure on small scales. Since the level of suppression depends on the sum of the masses of the three active neutrino species, the evolution of large-scale structure is a promising tool to constrain the total mass of neutrinos and possibly shed light on the mass hierarchy. In this work, we investigate these effects via a large suite of N-body simulations that include massive neutrinos using an analytic linear-response approximation: the Cosmological Massive Neutrino Simulations (MassiveNuS). The simulations include the effects of radiation on the background expansion, as well as the clustering of neutrinos in response to the nonlinear dark matter evolution. We allow three cosmological parameters to vary: the neutrino mass sum Mν in the range of 0–0.6 eV, the total matter density Ωm, and the primordial power spectrum amplitude As. The rms density fluctuation in spheres of 8 comoving Mpc/h (σ8) is a derived parameter as a result. Our data products include N-body snapshots, halo catalogues, merger trees, ray-traced galaxy lensing convergence maps for four source redshift planes between zs=1–2.5, and ray-traced cosmic microwave background lensing convergence maps. We describe the simulation procedures and code validation in this paper. The data are publicly available at http://columbialensing.org.

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...

Lysophosphatidic acid-induced RhoA signaling and prolonged macrophage infiltration worsens fibrosis and fatty infiltration following rotator cuff tears.

Science.gov (United States)

Davies, Michael R; Lee, Lawrence; Feeley, Brian T; Kim, Hubert T; Liu, Xuhui

2017-07-01

Previous studies have suggested that macrophage-mediated chronic inflammation is involved in the development of rotator cuff muscle atrophy and degeneration following massive tendon tears. Increased RhoA signaling has been reported in chronic muscle degeneration, such as muscular dystrophy. However, the role of RhoA signaling in macrophage infiltration and rotator muscle degeneration remains unknown. Using a previously established rat model of massive rotator cuff tears, we found RhoA signaling is upregulated in rotator cuff muscle following a massive tendon-nerve injury. This increase in RhoA expression is greatly potentiated by the administration of a potent RhoA activator, lysophosphatidic acid (LPA), and is accompanied by increased TNFα and TGF-β1 expression in rotator cuff muscle. Boosting RhoA signaling with LPA significantly worsened rotator cuff muscle atrophy, fibrosis, and fatty infiltration, accompanied with massive monocytic infiltration of rotator cuff muscles. Co-staining of RhoA and the tissue macrophage marker CD68 showed that CD68+ tissue macrophages are the dominant cell source of increased RhoA signaling in rotator cuff muscles after tendon tears. Taken together, our findings suggest that LPA-mediated RhoA signaling in injured muscle worsens the outcomes of atrophy, fibrosis, and fatty infiltration by increasing macrophage infiltraion in rotator cuff muscle. Clinically, inhibiting RhoA signaling may represent a future direction for developing new treatments to improve muscle quality following massive rotator cuff tears. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:1539-1547, 2017. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Bessel functions: parallel display and processing.

Science.gov (United States)

Lohmann, A W; Ojeda-Castañeda, J; Serrano-Heredia, A

1994-01-01

We present an optical setup that converts planar binary curves into two-dimensional amplitude distributions, which are proportional, along one axis, to the Bessel function of order n, whereas along the other axis the order n increases. This Bessel displayer can be used for parallel Bessel transformation of a signal. Experimental verifications are included.

A parallel algorithm for transient solid dynamics simulations with contact detection

International Nuclear Information System (INIS)

Attaway, S.; Hendrickson, B.; Plimpton, S.; Gardner, D.; Vaughan, C.; Heinstein, M.; Peery, J.

1996-01-01

Solid dynamics simulations with Lagrangian finite elements are used to model a wide variety of problems, such as the calculation of impact damage to shipping containers for nuclear waste and the analysis of vehicular crashes. Using parallel computers for these simulations has been hindered by the difficulty of searching efficiently for material surface contacts in parallel. A new parallel algorithm for calculation of arbitrary material contacts in finite element simulations has been developed and implemented in the PRONTO3D transient solid dynamics code. This paper will explore some of the issues involved in developing efficient, portable, parallel finite element models for nonlinear transient solid dynamics simulations. The contact-detection problem poses interesting challenges for efficient implementation of a solid dynamics simulation on a parallel computer. The finite element mesh is typically partitioned so that each processor owns a localized region of the finite element mesh. This mesh partitioning is optimal for the finite element portion of the calculation since each processor must communicate only with the few connected neighboring processors that share boundaries with the decomposed mesh. However, contacts can occur between surfaces that may be owned by any two arbitrary processors. Hence, a global search across all processors is required at every time step to search for these contacts. Load-imbalance can become a problem since the finite element decomposition divides the volumetric mesh evenly across processors but typically leaves the surface elements unevenly distributed. In practice, these complications have been limiting factors in the performance and scalability of transient solid dynamics on massively parallel computers. In this paper the authors present a new parallel algorithm for contact detection that overcomes many of these limitations

Holographically viable extensions of topologically massive and minimal massive gravity?

Science.gov (United States)

Altas, Emel; Tekin, Bayram

2016-01-01

Recently [E. Bergshoeff et al., Classical Quantum Gravity 31, 145008 (2014)], an extension of the topologically massive gravity (TMG) in 2 +1 dimensions, dubbed as minimal massive gravity (MMG), which is free of the bulk-boundary unitarity clash that inflicts the former theory and all the other known three-dimensional theories, was found. Field equations of MMG differ from those of TMG at quadratic terms in the curvature that do not come from the variation of an action depending on the metric alone. Here we show that MMG is a unique theory and there does not exist a deformation of TMG or MMG at the cubic and quartic order (and beyond) in the curvature that is consistent at the level of the field equations. The only extension of TMG with the desired bulk and boundary properties having a single massive degree of freedom is MMG.

II - Template Metaprogramming for Massively Parallel Scientific Computing - Vectorization with Expression Templates

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...

Parallel deposition, sorting, and reordering methods in the Hybrid Ordered Plasma Simulation (HOPS) code

International Nuclear Information System (INIS)

Anderson, D.V.; Shumaker, D.E.

1993-01-01

From a computational standpoint, particle simulation calculations for plasmas have not adapted well to the transitions from scalar to vector processing nor from serial to parallel environments. They have suffered from inordinate and excessive accessing of computer memory and have been hobbled by relatively inefficient gather-scatter constructs resulting from the use of indirect indexing. Lastly, the many-to-one mapping characteristic of the deposition phase has made it difficult to perform this in parallel. The authors' code sorts and reorders the particles in a spatial order. This allows them to greatly reduce the memory references, to run in directly indexed vector mode, and to employ domain decomposition to achieve parallelization. In this hybrid simulation the electrons are modeled as a fluid and the field equations solved are obtained from the electron momentum equation together with the pre-Maxwell equations (displacement current neglected). Either zero or finite electron mass can be used in the electron model. The resulting field equations are solved with an iteratively explicit procedure which is thus trivial to parallelize. Likewise, the field interpolations and the particle pushing is simple to parallelize. The deposition, sorting, and reordering phases are less simple and it is for these that the authors present detailed algorithms. They have now successfully tested the parallel version of HOPS in serial mode and it is now being readied for parallel execution on the Cray C-90. They will then port HOPS to a massively parallel computer, in the next year

Imaging findings of adiposis dolorosa vs. massive localized lymphedema

Energy Technology Data Exchange (ETDEWEB)

Petscavage-Thomas, Jonelle M.; Bernard, Stephanie A.; Bennett, Jennifer [Milton S. Hershey Medical Center, Department of Radiology, H066, 500 University Drive, P.O. Box 850, Hershey, PA (United States); Walker, Eric A. [Milton S. Hershey Medical Center, Department of Radiology, H066, 500 University Drive, P.O. Box 850, Hershey, PA (United States); Uniformed Services University of the Health Sciences, Department of Radiology and Nuclear Medicine, Bethesda, MD (United States)

2015-06-01

Adiposis dolorosa (Dercum's disease) is a condition of benign, painful subcutaneous lipomatous lesions associated with weakness, endocrine and lipid abnormalities, and mental disturbances. There is little information documenting the cross-sectional imaging findings that differentiate it from lipomatous and neoplastic soft tissue masses, or massive localized lymphedema. The purpose of this study was to provide a radiological case series of adiposis dolorosa. A 10-year retrospective review of the picture archiving and communications system was performed. Two musculoskeletal radiologists reviewed images to confirm and document imaging features, location, size, and patient demographics. Medical records were reviewed to characterize patients into three groups: one group met at least three of the four criteria of Dercum's syndrome, the second group met less than three criteria, and the third group had clinical diagnosis of cellulitis of the lower extremity. Seventeen cases (25 masses) of adiposis dolorosa were found, nine cases of which met at least three criteria of Dercum's syndrome. All cases in the first two groups demonstrated skin thickening and lymphedema of subcutaneous fat, which was fluid attenuation on CT and low or intermediate T1-weighted and high STIR/T2-weighted MR signal. Two cases with pathology showed mild fatty infiltration with fibrous septa, and the third case showed massive localized lymphedema. The third group of ten cellulitis patients demonstrated non-mass-like subcutaneous edema with similar CT attenuation and MR signal characteristics to the first two groups, but differed by the presence of post-contrast enhancement and non-mass-like appearance in 90 %. Imaging findings of adiposis dolorosa and massive localized lymphedema overlap, as do the symptoms and pathological features. Due to the mass-like engorgement of the soft tissues and pain, patients will often undergo imaging to exclude neoplasm or infection. Knowledge of these

A method of fast mosaic for massive UAV images

Science.gov (United States)

Xiang, Ren; Sun, Min; Jiang, Cheng; Liu, Lei; Zheng, Hui; Li, Xiaodong

2014-11-01

With the development of UAV technology, UAVs are used widely in multiple fields such as agriculture, forest protection, mineral exploration, natural disaster management and surveillances of public security events. In contrast of traditional manned aerial remote sensing platforms, UAVs are cheaper and more flexible to use. So users can obtain massive image data with UAVs, but this requires a lot of time to process the image data, for example, Pix4UAV need approximately 10 hours to process 1000 images in a high performance PC. But disaster management and many other fields require quick respond which is hard to realize with massive image data. Aiming at improving the disadvantage of high time consumption and manual interaction, in this article a solution of fast UAV image stitching is raised. GPS and POS data are used to pre-process the original images from UAV, belts and relation between belts and images are recognized automatically by the program, in the same time useless images are picked out. This can boost the progress of finding match points between images. Levenberg-Marquard algorithm is improved so that parallel computing can be applied to shorten the time of global optimization notably. Besides traditional mosaic result, it can also generate superoverlay result for Google Earth, which can provide a fast and easy way to show the result data. In order to verify the feasibility of this method, a fast mosaic system of massive UAV images is developed, which is fully automated and no manual interaction is needed after original images and GPS data are provided. A test using 800 images of Kelan River in Xinjiang Province shows that this system can reduce 35%-50% time consumption in contrast of traditional methods, and increases respond speed of UAV image processing rapidly.

Parallel implementation of geometrical shock dynamics for two dimensional converging shock waves

Science.gov (United States)

Qiu, Shi; Liu, Kuang; Eliasson, Veronica

2016-10-01

Geometrical shock dynamics (GSD) theory is an appealing method to predict the shock motion in the sense that it is more computationally efficient than solving the traditional Euler equations, especially for converging shock waves. However, to solve and optimize large scale configurations, the main bottleneck is the computational cost. Among the existing numerical GSD schemes, there is only one that has been implemented on parallel computers, with the purpose to analyze detonation waves. To extend the computational advantage of the GSD theory to more general applications such as converging shock waves, a numerical implementation using a spatial decomposition method has been coupled with a front tracking approach on parallel computers. In addition, an efficient tridiagonal system solver for massively parallel computers has been applied to resolve the most expensive function in this implementation, resulting in an efficiency of 0.93 while using 32 HPCC cores. Moreover, symmetric boundary conditions have been developed to further reduce the computational cost, achieving a speedup of 19.26 for a 12-sided polygonal converging shock.

A Highly Parallel and Scalable Motion Estimation Algorithm with GPU for HEVC

Directory of Open Access Journals (Sweden)

Yun-gang Xue

2017-01-01

Full Text Available We propose a highly parallel and scalable motion estimation algorithm, named multilevel resolution motion estimation (MLRME for short, by combining the advantages of local full search and downsampling. By subsampling a video frame, a large amount of computation is saved. While using the local full-search method, it can exploit massive parallelism and make full use of the powerful modern many-core accelerators, such as GPU and Intel Xeon Phi. We implanted the proposed MLRME into HM12.0, and the experimental results showed that the encoding quality of the MLRME method is close to that of the fast motion estimation in HEVC, which declines by less than 1.5%. We also implemented the MLRME with CUDA, which obtained 30–60x speed-up compared to the serial algorithm on single CPU. Specifically, the parallel implementation of MLRME on a GTX 460 GPU can meet the real-time coding requirement with about 25 fps for the 2560×1600 video format, while, for 832×480, the performance is more than 100 fps.

Estimation and Mitigation of Channel Non-Reciprocity in Massive MIMO

Science.gov (United States)

Raeesi, Orod; Gokceoglu, Ahmet; Valkama, Mikko

2018-05-01

Time-division duplex (TDD) based massive MIMO systems rely on the reciprocity of the wireless propagation channels when calculating the downlink precoders based on uplink pilots. However, the effective uplink and downlink channels incorporating the analog radio front-ends of the base station (BS) and user equipments (UEs) exhibit non-reciprocity due to non-identical behavior of the individual transmit and receive chains. When downlink precoder is not aware of such channel non-reciprocity (NRC), system performance can be significantly degraded due to NRC induced interference terms. In this work, we consider a general TDD-based massive MIMO system where frequency-response mismatches at both the BS and UEs, as well as the mutual coupling mismatch at the BS large-array system all coexist and induce channel NRC. Based on the NRC-impaired signal models, we first propose a novel iterative estimation method for acquiring both the BS and UE side NRC matrices and then also propose a novel NRC-aware downlink precoder design which utilizes the obtained estimates. Furthermore, an efficient pilot signaling scheme between the BS and UEs is introduced in order to facilitate executing the proposed estimation method and the NRC-aware precoding technique in practical systems. Comprehensive numerical results indicate substantially improved spectral efficiency performance when the proposed NRC estimation and NRC-aware precoding methods are adopted, compared to the existing state-of-the-art methods.

Pulse shaping for all-optical signal processing of ultra-high bit rate serial data signals

DEFF Research Database (Denmark)

Palushani, Evarist

The following thesis concerns pulse shaping and optical waveform manipulation for all-optical signal processing of ultra-high bit rate serial data signals, including generation of optical pulses in the femtosecond regime, serial-to-parallel conversion and terabaud coherent optical time division...

Massive Supergravity and Deconstruction

CERN Document Server

Gregoire, T; Shadmi, Y; Gregoire, Thomas; Schwartz, Matthew D; Shadmi, Yael

2004-01-01

We present a simple superfield Lagrangian for massive supergravity. It comprises the minimal supergravity Lagrangian with interactions as well as mass terms for the metric superfield and the chiral compensator. This is the natural generalization of the Fierz-Pauli Lagrangian for massive gravity which comprises mass terms for the metric and its trace. We show that the on-shell bosonic and fermionic fields are degenerate and have the appropriate spins: 2, 3/2, 3/2 and 1. We then study this interacting Lagrangian using goldstone superfields. We find that a chiral multiplet of goldstones gets a kinetic term through mixing, just as the scalar goldstone does in the non-supersymmetric case. This produces Planck scale (Mpl) interactions with matter and all the discontinuities and unitarity bounds associated with massive gravity. In particular, the scale of strong coupling is (Mpl m^4)^1/5, where m is the multiplet's mass. Next, we consider applications of massive supergravity to deconstruction. We estimate various qu...

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.

Re-use of Low Bandwidth Equipment for High Bit Rate Transmission Using Signal Slicing Technique

DEFF Research Database (Denmark)

Wagner, Christoph; Spolitis, S.; Vegas Olmos, Juan José

: Massive fiber-to-the-home network deployment requires never ending equipment upgrades operating at higher bandwidth. We show effective signal slicing method, which can reuse low bandwidth opto-electronical components for optical communications at higher bit rates.......: Massive fiber-to-the-home network deployment requires never ending equipment upgrades operating at higher bandwidth. We show effective signal slicing method, which can reuse low bandwidth opto-electronical components for optical communications at higher bit rates....

Superweakly interacting massive particle dark matter signals from the early Universe

International Nuclear Information System (INIS)

Feng, Jonathan L.; Rajaraman, Arvind; Takayama, Fumihiro

2003-01-01

Cold dark matter may be made of superweakly interacting massive particles, super-WIMP's, that naturally inherit the desired relic density from late decays of metastable WIMP's. Well-motivated examples are weak-scale gravitinos in supergravity and Kaluza-Klein gravitons from extra dimensions. These particles are impossible to detect in all dark matter experiments. We find, however, that super-WIMP dark matter may be discovered through cosmological signatures from the early Universe. In particular, super-WIMP dark matter has observable consequences for big bang nucleosynthesis and the cosmic microwave background (CMB), and may explain the observed underabundance of 7 Li without upsetting the concordance between deuterium and CMB baryometers. We discuss the implications for future probes of CMB blackbody distortions and collider searches for new particles. In the course of this study, we also present a model-independent analysis of entropy production from late-decaying particles in light of Wilkinson microwave anisotropy probe data

Minimal massive 3D gravity

International Nuclear Information System (INIS)

Bergshoeff, Eric; Merbis, Wout; Hohm, Olaf; Routh, Alasdair J; Townsend, Paul K

2014-01-01

We present an alternative to topologically massive gravity (TMG) with the same ‘minimal’ bulk properties; i.e. a single local degree of freedom that is realized as a massive graviton in linearization about an anti-de Sitter (AdS) vacuum. However, in contrast to TMG, the new ‘minimal massive gravity’ has both a positive energy graviton and positive central charges for the asymptotic AdS-boundary conformal algebra. (paper)

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

Beginning the Dialogue on the e-Transformation: Behavior Analysis' First Massive Open Online Course (MOOC).

Science.gov (United States)

Rehfeldt, Ruth Anne; Jung, Heidi L; Aguirre, Angelica; Nichols, Jane L; Root, William B

2016-03-01

The e-Transformation in higher education, in which Massive Open Online Courses (MOOCs) are playing a pivotal role, has had an impact on the modality in which behavior analysis is taught. In this paper, we survey the history and implications of online education including MOOCs and describe the implementation and results for the discipline's first MOOC, delivered at Southern Illinois University in spring 2015. Implications for the globalization and free access of higher education are discussed, as well as the parallel between MOOCs and Skinner's teaching machines.

IQ imbalance tolerable parallel-channel DMT transmission for coherent optical OFDMA access network

Science.gov (United States)

Jung, Sang-Min; Mun, Kyoung-Hak; Jung, Sun-Young; Han, Sang-Kook

2016-12-01

Phase diversity of coherent optical communication provides spectrally efficient higher-order modulation for optical communications. However, in-phase/quadrature (IQ) imbalance in coherent optical communication degrades transmission performance by introducing unwanted signal distortions. In a coherent optical orthogonal frequency division multiple access (OFDMA) passive optical network (PON), IQ imbalance-induced signal distortions degrade transmission performance by interferences of mirror subcarriers, inter-symbol interference (ISI), and inter-channel interference (ICI). We propose parallel-channel discrete multitone (DMT) transmission to mitigate transceiver IQ imbalance-induced signal distortions in coherent orthogonal frequency division multiplexing (OFDM) transmissions. We experimentally demonstrate the effectiveness of parallel-channel DMT transmission compared with that of OFDM transmission in the presence of IQ imbalance.

Development and application of a massively parallel KKR Green function method for large scale systems

Energy Technology Data Exchange (ETDEWEB)

Thiess, Alexander R.

2011-12-19

In this thesis we present the development of the self-consistent, full-potential Korringa-Kohn-Rostoker (KKR) Green function method KKRnano for calculating the electronic properties, magnetic interactions, and total energy including all electrons on the basis of the density functional theory (DFT) on high-end massively parallelized high-performance computers for supercells containing thousands of atoms without sacrifice of accuracy. KKRnano was used for the following two applications. The first application is centered in the field of dilute magnetic semiconductors. In this field a new promising material combination was identified: gadolinium doped gallium nitride which shows ferromagnetic ordering of colossal magnetic moments above room temperature. It quickly turned out that additional extrinsic defects are inducing the striking properties. However, the question which kind of extrinsic defects are present in experimental samples is still unresolved. In order to shed light on this open question, we perform extensive studies of the most promising candidates: interstitial nitrogen and oxygen, as well as gallium vacancies. By analyzing the pairwise magnetic coupling among defects it is shown that nitrogen and oxygen interstitials cannot support thermally stable ferromagnetic order. Gallium vacancies, on the other hand, facilitate an important coupling mechanism. The vacancies are found to induce large magnetic moments on all surrounding nitrogen sites, which then couple ferromagnetically both among themselves and with the gadolinium dopants. Based on a statistical evaluation it can be concluded that already small concentrations of gallium vacancies can lead to a distinct long-range ferromagnetic ordering. Beyond this important finding we present further indications, from which we infer that gallium vacancies likely cause the striking ferromagnetic coupling of colossal magnetic moments in GaN:Gd. The second application deals with the phase-change material germanium

Development and application of a massively parallel KKR Green function method for large scale systems

International Nuclear Information System (INIS)

Thiess, Alexander R.

2011-01-01

In this thesis we present the development of the self-consistent, full-potential Korringa-Kohn-Rostoker (KKR) Green function method KKRnano for calculating the electronic properties, magnetic interactions, and total energy including all electrons on the basis of the density functional theory (DFT) on high-end massively parallelized high-performance computers for supercells containing thousands of atoms without sacrifice of accuracy. KKRnano was used for the following two applications. The first application is centered in the field of dilute magnetic semiconductors. In this field a new promising material combination was identified: gadolinium doped gallium nitride which shows ferromagnetic ordering of colossal magnetic moments above room temperature. It quickly turned out that additional extrinsic defects are inducing the striking properties. However, the question which kind of extrinsic defects are present in experimental samples is still unresolved. In order to shed light on this open question, we perform extensive studies of the most promising candidates: interstitial nitrogen and oxygen, as well as gallium vacancies. By analyzing the pairwise magnetic coupling among defects it is shown that nitrogen and oxygen interstitials cannot support thermally stable ferromagnetic order. Gallium vacancies, on the other hand, facilitate an important coupling mechanism. The vacancies are found to induce large magnetic moments on all surrounding nitrogen sites, which then couple ferromagnetically both among themselves and with the gadolinium dopants. Based on a statistical evaluation it can be concluded that already small concentrations of gallium vacancies can lead to a distinct long-range ferromagnetic ordering. Beyond this important finding we present further indications, from which we infer that gallium vacancies likely cause the striking ferromagnetic coupling of colossal magnetic moments in GaN:Gd. The second application deals with the phase-change material germanium