Multicore Challenges and Benefits for High Performance Scientific Computing

Until recently, performance gains in processors were achieved largely by improvements in clock speeds and instruction level parallelism. Thus, applications could obtain performance increases with relatively minor changes by upgrading to the latest generation of computing hardware. Currently, however...

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Main Authors: Ida M.B. Nielsen, Curtis L. Janssen
Format: Article
Language:English
Published: Hindawi Limited 2008-01-01
Series:Scientific Programming
Online Access:http://dx.doi.org/10.3233/SPR-2008-0260
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spelling doaj-2663a1ca70e048029a7c7fb39da571cc2021-07-02T04:10:40ZengHindawi LimitedScientific Programming1058-92441875-919X2008-01-0116427728510.3233/SPR-2008-0260Multicore Challenges and Benefits for High Performance Scientific ComputingIda M.B. Nielsen0Curtis L. Janssen1Sandia National Laboratories, P.O. Box 969, Livermore, CA 94551, USASandia National Laboratories, P.O. Box 969, Livermore, CA 94551, USAUntil recently, performance gains in processors were achieved largely by improvements in clock speeds and instruction level parallelism. Thus, applications could obtain performance increases with relatively minor changes by upgrading to the latest generation of computing hardware. Currently, however, processor performance improvements are realized by using multicore technology and hardware support for multiple threads within each core, and taking full advantage of this technology to improve the performance of applications requires exposure of extreme levels of software parallelism. We will here discuss the architecture of parallel computers constructed from many multicore chips as well as techniques for managing the complexity of programming such computers, including the hybrid message-passing/multi-threading programming model. We will illustrate these ideas with a hybrid distributed memory matrix multiply and a quantum chemistry algorithm for energy computation using Møller–Plesset perturbation theory.http://dx.doi.org/10.3233/SPR-2008-0260
collection DOAJ
language English
format Article
sources DOAJ
author Ida M.B. Nielsen
Curtis L. Janssen
spellingShingle Ida M.B. Nielsen
Curtis L. Janssen
Multicore Challenges and Benefits for High Performance Scientific Computing
Scientific Programming
author_facet Ida M.B. Nielsen
Curtis L. Janssen
author_sort Ida M.B. Nielsen
title Multicore Challenges and Benefits for High Performance Scientific Computing
title_short Multicore Challenges and Benefits for High Performance Scientific Computing
title_full Multicore Challenges and Benefits for High Performance Scientific Computing
title_fullStr Multicore Challenges and Benefits for High Performance Scientific Computing
title_full_unstemmed Multicore Challenges and Benefits for High Performance Scientific Computing
title_sort multicore challenges and benefits for high performance scientific computing
publisher Hindawi Limited
series Scientific Programming
issn 1058-9244
1875-919X
publishDate 2008-01-01
description Until recently, performance gains in processors were achieved largely by improvements in clock speeds and instruction level parallelism. Thus, applications could obtain performance increases with relatively minor changes by upgrading to the latest generation of computing hardware. Currently, however, processor performance improvements are realized by using multicore technology and hardware support for multiple threads within each core, and taking full advantage of this technology to improve the performance of applications requires exposure of extreme levels of software parallelism. We will here discuss the architecture of parallel computers constructed from many multicore chips as well as techniques for managing the complexity of programming such computers, including the hybrid message-passing/multi-threading programming model. We will illustrate these ideas with a hybrid distributed memory matrix multiply and a quantum chemistry algorithm for energy computation using Møller–Plesset perturbation theory.
url http://dx.doi.org/10.3233/SPR-2008-0260
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