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Preparing sparse solvers for exascale computing

delete2020-01-20
delete19
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OA
AI
H
Hartwig Anzt
E
Erik G. Boman
F
Falgout, Rob
P
Pieter Ghysels
M
Michael A. Heroux *
X
Xiaoye Li
L
Lois Curfman McInnes
R
Richard Mills
S
Sivasankaran Rajamanickam
K
Karl Rupp
B
Barry Smith
I
Ichitaro Yamazaki
U
Ulrike Meier Yang
DOI:10.1098/rsta.2019.0053delete
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摘要

摘要

En 中文
Sparse solvers provide essential functionality for a wide variety of scientific applications. Highly parallel sparse solvers are essential for continuing advances in high-fidelity, multi-physics and multi-scale simulations, especially as we target exascale platforms. This paper describes the challenges, strategies and progress of the US Department of Energy Exascale Computing project towards providing sparse solvers for exascale computing platforms. We address the demands of systems with thousands of high-performance node devices where exposing concurrency, hiding latency and creating alternative algorithms become essential. The efforts described here are works in progress, highlighting current success and upcoming challenges. This article is part of a discussion meeting issue 'Numerical algorithms for high-performance computational science'.
Keyword:
sparse solvers
mathematical libraries
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期刊

P
Philosophical Transactions of the Royal Society A-Mathematical Physical and Engineering Sciences
IF:
3.7
论文数:
7.8K
被引数:
2.8W

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L
Lawrence Livermore National Laboratory
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论文数: 3.8K
被引数: 9
U
University of Tennessee Knoxville
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1.1W
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被引数: 17
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united states department of energy (doe)
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11.3W
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被引数: 246
University of Tennessee System 封面图
University of Tennessee System
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2.9W
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被引数: 115
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Sandia National Laboratories
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5.5K
论文数: 3.8K
被引数: 6.4K
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