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  1. Proceedings of the Fourth Conference on Partitioned Global Address Space Programming Model (PGAS '10)
  2. XcalableMP implementation and performance of NAS Parallel Benchmarks
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Predicting remote reuse distance patterns in UPC applications
Introducing OpenSHMEM: SHMEM for the PGAS community
Hybrid PGAS runtime support for multicore nodes
Asynchronous PGAS runtime for Myrinet networks
Unifying UPC and MPI runtimes: experience with MVAPICH
Introducing mNUMA: an extended PGAS architecture
Performance modeling for multilevel communication in SHMEM+
Improving UPC productivity via integrated development tools
X10-enabled MapReduce
Development and performance analysis of a UPC Particle-in-Cell code
XcalableMP implementation and performance of NAS Parallel Benchmarks
Extensible PGAS semantics for C++
An open-source compiler and runtime implementation for Coarray Fortran
Hiding latency in Coarray Fortran 2.0
Numerical Python for scalable architectures

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XcalableMP implementation and performance of NAS Parallel Benchmarks

Content Provider ACM Digital Library
Author Sato, Mitsuhisa Nakao, Masahiro Boku, Taisuke Lee, Jinpil
Abstract XcalableMP is a parallel extension of existing languages, such as C and Fortran, that was proposed as a new programming model to facilitate program parallel applications for distributed memory systems. In order to investigate the performance of parallel programs written in XcalableMP, we have implemented NAS Parallel Benchmarks, specifically, the Embarrassingly Parallel (EP) benchmark, the Integer Sort (IS) benchmark, and the Conjugate Gradient (CG) benchmark, using XcalableMP. The results show that the performance of XcalableMP is comparable to that of MPI. In particular, the performances of IS with a histogram and CG with two-dimensional parallelization achieve almost the same performance. The results also demonstrate that XcalableMP allows a programmer to write efficient parallel applications at a lower programming cost.
Starting Page 1
Ending Page 10
Page Count 10
File Format PDF
ISBN 9781450304610
DOI 10.1145/2020373.2020384
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2010-10-12
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Distributed memory system High-performance computing Parallel programming language
Content Type Text
Resource Type Article
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