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检索条件"任意字段=Working Conference on Massively Parallel Programming Models"

共 234 条记录，以下是91-100 订阅

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Solving irregular problems with High Performance Fortran

Solving irregular problems with High Performance Fortran

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working conference on massively parallel programming models

作者： P. Mehrotra J. Van Rosendale H. Zima MS 132C NASA Langely Research Center ICASE Hampton VA USA Institute for Software Technology and Parallel Systems University of Technology Vienna Vienna Austria

High Performance Fortran (HPF) provides a high-level interface for data-parallel scientific applications, while delegating to the compiler the task of generating an explicitly parallel message-passing program. The main objective of this paper is to study the applicability of the language to a class of irregular scientific applications. After giving an outline of developments that led to HPF and shortly explaining its major features, we discuss a variety of approaches for solving multiblock problems and applications dealing with unstructured meshes. We show that the efficient solution of these problems does not only need the full range of the HPF approved extensions, but also requires additional features such as the explicit control of communication schedules and support for value-based alignment.

关键词： NASA Communication system control Contracts Space technology Application software Program processors Yarn Transportation parallel processing Distributed computing

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A massively parallel reservoir simulator on the GPU architecture

A massively parallel reservoir simulator on the GPU architec...

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SPE Reservoir Simulation conference 2021, RSC 2021

作者： Middya, Usuf Manea, Abdulrahman Alhubail, Maitham Ferguson, Todd Byer, Thomas Dogru, Ali Saudi Aramco Aramco Americas

ISBN: (纸本)9781613997475

Reservoir simulation computational costs have been continuously growing due to high-resolution reservoir characterization, increasing model complexity, and uncertainty analysis workflows. Reducing simulation costs by upscaling is often necessary for operational requirements. Fast evolving HPC technologies offer opportunities to reduce cost without compromising fidelity. This work presents a novel in-house massively parallel full-physics reservoir simulator running on the emerging GPU architecture. Almost all the simulation kernels have been designed and implemented to honor the GPU SIMD programming paradigm. These kernels include physical property calculations, phase equilibrium computations, Jacobian construction, linear and nonlinear solvers, and wells. Novel techniques are devised in various kernels to expose enough parallelism to ensure that the control and data-flow patterns are well suited for the GPU environment. Mixed-precision computation is also employed when appropriate (e.g., in derivative calculation) to reduce computational costs without compromising the solution accuracy. The GPU implementation of the simulator is tested and benchmarked using various reservoir models, ranging from the synthetic SPE10 Benchmark (Christie & Blunt, 2001) to several industrial-scale models. These real field models range in size from tens of millions of cells to more than billion cells with black-oil and multicomponent compositional fluid. The GPU simulator is benchmarked on the IBM AC922 massively parallel architecture having tens of NVidia Volta V100 GPUs. To compare performance with CPU architectures, an optimized CPU implementation of the simulator is benchmarked on the IBM AC922 CPUs and on a cluster consisting of thousands of Intel's Haswell-EP Xeon® CPU E5-2680 v3. Detailed analysis of several numerical experiments comparing the simulator performance on the GPU and the CPU architectures is presented. In almost all of the cases, the analysis shows that the use of har

关键词： Graphics processing unit

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parallelization of virtual screening in drug discovery on massively parallel architectures

Parallelization of virtual screening in drug discovery on ma...

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20th Euromicro International conference on parallel, Distributed and Network-Based Processing, PDP 2012

作者： Guerrero, Ginés D. Pérez-Sánchez, Horacio E. Cecilia, José M. García, José M. Grupo de Arquitectura y Computación Paralela Dpto. de Ingeniería y Tecnología de Computadores Universidad de Murcia Campus de Espinardo 30100 Murcia Spain

ISBN: (纸本)9780769546339

The current trend in medical research for the discovery of new drugs is the use of Virtual Screening (VS) methods. In these methods, the calculation of the non-bonded interactions, such as electrostatics or van der Waals forces, plays an important role, representing up to 80% of the total execution time. These kernels are computational intensive and massively parallel in nature, and thus they are well suited to be accelerated on parallel architectures. In this work, we discuss the effective parallelization of the non-bonded electrostatic interactions kernel for VS on three different parallel architectures: a shared memory system, a distributed memory system, and a Graphics Processing Units (GPUs). For an efficient handling of the computational intensive and massively parallelism of this kernel, we enable different data policies on those architectures to take advantage of all computational resources offered by them. Four implementations are provided based on MPI, OpenMP, Hybrid MPIOpenMP and CUDA programming models. The sequential implementation is defeated by a wide margin by all parallel implementations, obtaining up to 72x speed-up factor on the shared memory system through OpenMP, up to 60x and 229x speed-ups factors on the distributed memory system for the MPI implementation and the Hybrid MPI-OpenMP implementation respectively, and finally, up to 213x speedup factor for the CUDA implementation on the GPU architecture to offer the best alternative in terms of performance/ cost ratio. © 2012 IEEE.

关键词： Van der Waals forces

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Data mining with parallel support vector machines for classification

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4th International conference on Advances in Information Systems

作者： Eitrich, Tatjana Lang, Bruno Res Ctr Juelich Cent Inst Appl Math Julich Germany Univ Gesamthsch Wuppertal Dept Math Appl Comp Sci & Sci Comp Grp D-5600 Wuppertal Germany

ISBN: (纸本)3540462910

The increasing amount of data used for classification, as well as the demand for complex models with a large number of well tuned parameters, naturally lead to the search for efficient approaches making use of massively parallel systems. We describe the parallelization of support vector machine learning for shared memory systems. The support vector machine is a powerful and reliable data mining method. Our learning algorithm relies on a decomposition scheme, which in turn uses a special variable projection method, for solving the quadratic program associated with support vector machine learning. By using hybrid parallel programming, our parallelization approach can be combined with the parallelism of a distributed cross validation routine and parallel parameter optimization methods.

关键词： data mining classification support vector machine parallelization

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Biomimetic models for an Ecological Approach to massively-Deployed Sensor Networks 18

Biomimetic Models for an Ecological Approach to Massively-De...

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18th International conference on parallel and Distributed Computing Systems, PDCS 2005

作者： Jones, K.H. Lodding, K.N. Olariu, S. Wilson, L. Xin, C. NASA Langley Research Center HamptonVA23681 United States Old Dominion University NorfolkVA23529 United States Norfolk State University NorfolkVA23504 United States

ISBN: (纸本)9781604234565

Promises of ubiquitous control of the physical environment by massively-deployed wireless sensor networks open avenues for new applications that will redefine the way we live and work. Due to small size and low cost of sensor devices, visionaries promise systems enabled by deployment of massive numbers of sensors ubiquitous throughout our environment working in concert. Recent research has concentrated on developing techniques for performing relatively simple tasks with minimal energy expense, assuming some form of centralized control. Unfortunately, centralized control is not conducive to parallel activities and does not scale to massive size networks. Execution of simple tasks in sparse networks will not lead to the sophisticated applications predicted. We propose a new way of looking at massively-deployed sensor networks, motivated by lessons learned from the way biological ecosystems are organized. We demonstrate that in such a model, fully distributed data aggregation can be performed in a scalable fashion in massively deployed sensor networks, where motes operate on local information, making local decisions that are aggregated across the network to achieve globally-meaningful effects. We show that such architectures may be used to facilitate communication and synchronization in a fault-tolerant manner, while balancing workload and required energy expenditure throughout the network. © 2005 18th ISCA International conference on parallel and Distributed Computing Systems 2005, PDCS 2005. All rights reserved.

关键词： Cellular automata

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Portability of performance with the BSPLib communications library

Portability of performance with the BSPLib communications li...

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working conference on massively parallel programming models

作者： J.M.D. Hill S.R. Donaldson D. Skillicorn Oxford University Computing Laboratory Oxford UK Department of Computing and Information Science Queen's University Kingston Canada

The BSP cost model makes a new level of power available for designing parallel algorithms. First, it models the actual behaviour of today's parallel computers, and so can be used to choose appropriate algorithms without completely implementing them. Second, it becomes possible to characterise the range of architecture performance over which a particular algorithm is the best choice. This provides the foundations for developing software that is both portable at the source code level, and in its expectation of performance. We illustrate this by comparing three possible implementations of broadcast, and show that a two-phase broadcast algorithm outperforms other techniques whenever the size of the data is large relative to the cost of synchronisation, and that broadcasting using trees is never a good technique (despite its continued popularity). We carry out a similar analysis for samplesort, and show that samplesort cannot perform well on networks of workstations unless the network bandwidth exceeds a certain threshold.

关键词： Libraries Broadcasting Costs Algorithm design and analysis parallel algorithms Concurrent computing Computer architecture Software performance Performance analysis Workstations

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massively parallel Network Coding on GPUs

Massively Parallel Network Coding on GPUs

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27th IEEE International Performance Computing and Communications conference (IPCCC)

作者： Chu, Xiaowen Zhao, Kaiyong Wang, Mea Hong Kong Baptist Univ Dept Comp Sci Hong Kong Hong Kong Peoples R China Univ Calgary Dept Comp Sci Calgary AB T2N 1N4 Canada

ISBN: (纸本)9781424433681

Network coding has recently been widely applied in various networks for system throughput improvement and/or resilience to network dynamics. However, the computational overhead introduced by the network coding operations is not negligible and has become the cornerstone for real deployment of network coding. In this paper, we exploit the computing power of contemporary Graphic Processing Units (GPUs) to accelerate the network coding operations. We proposed three parallel algorithms that maximize the parallelism of the encoding and decoding processes, i.e., the power of GPUs is fully utilized. This paper also shares our optimization design choices and our workarounds to the challenges encountered in working with GPUs. With our implementation of the algorithms, we are able to achieve up to 12 times of speedup over the highly optimized CPU counterpart, using the NVIDIA GPU and the Computer Unified Device Architecture (CUDA) programming model.

关键词： Network coding GPU computing CUDA

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Functional development of massively parallel programs 1st

Functional development of massively parallel programs

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1st International conference on Formal Methods in programming and their Applications, 1993

作者： Pepper, Peter Exner, Jürgen Südholt, Mario Technische Universität Berlin Fachbereich Informatik Germany

ISBN: (纸本)9783540573166

The programming of parallel systems requires a much higher level of abstraction than is provided by traditional programming languages and programming techniques. Therefore we aim at an approach that utilizes the clarity and power of mathematical concepts to the highest possible extent. In this paper we investigate, how a combination of higher-order functions with particular data structure specifications can be used for the programming of parallel algorithms. © Springer-Verlag Berlin Heidelberg 1993.

关键词： Functional programming

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Perpret - A performance prediction tool for massively parallel systems 8th

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8th International conference on Modelling Techniques and Tools for Computer performance Evaluation, Performance Tools 1995 and 8th GI/ITG conference on Measuring, Modelling and Evaluating Computing and Communication Systems, MMB 1995

作者： Brehm, Jürgen Madhukar, Manish Smirni, Evgenia Dowdy, Larry Universität Hannover Institut für Rechnerstrukturen und Betriebssysteme Lange Laube 3 Hannover30159 Germany Vanderbilt University Department of Computer Science Box 1679 B NashvilleTN37235 United States

ISBN: (纸本)9783540603009

Today’s massively parallel machines are typically message passing systems consisting of hundreds or thousands of processors. Implementing parallel applications efficiently in this environment is a challenging task. The Performance Prediction Tool (PerPreT) presented in this paper is useful for system designers and application developers. The system designers can use the tool to examine the effects of changes of architectural parameters on parallel applications (e.g., reduction of setup time, increase of link bandwidth, faster execution units). Application developers are interested in a fast evaluation of different parallelization strategies of their codes. PerPreT uses a relatively simple analytical model to predict speedup, execution time, computation time, and communication time for a parametrized application. Especially for large numbers of processors, PerPreT s analytical model is preferable to traditional models (e.g., Markov based approaches such as queueing and Petri net models). The applications are modelled through parameterized formulae for communication and computation. The parameters used by PerPreT include the problem size and the number of processors used to execute the program. The target systems are described by architectural parameters (e.g., setup times for communication, link bandwidth, and sustained computing performance per node). © Springer-Verlag Berlin Heidelberg 1995.

关键词： Analytical models

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Pangea: A Workbench for Statically Analyzing Multi-Language Software Corpora 14

Pangea: A Workbench for Statically Analyzing Multi-Language ...

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14th IEEE International working conference on Source Code Analysis and Manipulation (SCAM)

作者： Caracciolo, Andrea Chis, Andrei Spasojevic, Boris Lungu, Mircea Univ Bern Software Composit Grp CH-3012 Bern Switzerland

ISBN: (纸本)9780769553047

Software corpora facilitate reproducibility of analyses, however, static analysis for an entire corpus still requires considerable effort, often duplicated unnecessarily by multiple users. Moreover, most corpora are designed for single languages increasing the effort for cross-language analysis. To address these aspects we propose Pangea, an infrastructure allowing fast development of static analyses on multi-language corpora. Pangea uses language-independent meta-models stored as object model snapshots that can be directly loaded into memory and queryed without any parsing overhead. To reduce the effort of performing static analyses, Pangea provides out-of-the box support for: creating and refining analyses in a dedicated environment, deploying an analysis on an entire corpus, using a runner that supports parallel execution, and exporting results in various formats. In this tool demonstration we introduce Pangea and provide several usage scenarios that illustrate how it reduces the cost of analysis.

关键词： program diagnostics query processing Pangea workbench analysis cost reduction analysis creation analysis refining analysis reproducibility cross-language analysis language-independent meta-models multilanguage software corpora object model snapshots parallel execution static analysis Analytical models Java Load modeling Object oriented modeling Software systems Software corpora empirical study multi-language query analysis parallel execution Pangaea Object oriented modeling analysis programme Load modeling Software systems ANALYSIS models Java Java programming language

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