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CLC number: TP311

On-line Access: 2022-04-22

Received: 2018-07-07

Revision Accepted: 2018-09-14

Crosschecked: 2018-10-15

Cited: 0

Clicked: 2112

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Ze-yao Mo

http://orcid.org/0000-0003-3280-5682

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Frontiers of Information Technology & Electronic Engineering  2018 Vol.19 No.10 P.1251-1260

http://doi.org/10.1631/FITEE.1800421


Extreme-scale parallel computing: bottlenecks and strategies


Author(s):  Ze-yao Mo

Affiliation(s):  CAEP Software Center for High Performance Numerical Simulation, Beijing 100088, China; more

Corresponding email(s):   zeyao_mo@iapcm.ac.cn

Key Words:  Extreme scale, Numerical simulation, Parallel computing, Supercomputers


Ze-yao Mo. Extreme-scale parallel computing: bottlenecks and strategies[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(10): 1251-1260.

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Abstract: 
Extreme-scale numerical simulations seriously demand extreme parallel computing capabilities. To address the challenges of these capabilities toward exascale, we systematically analyze the major bottlenecks of parallel computing research from three perspectives: computational scale, computing efficiency, and programming productivity. For these bottlenecks, we propose a series of urgent key issues and coping strategies. This study will be useful in synchronizing development between the numerical computing capability and supercomputer peak performance.

超大规模并行计算:瓶颈与对策

摘要:超大规模数值模拟极大依赖并行计算能力。从计算规模、计算效率和编程生产率3个维度,系统分析了超大规模并行计算能力的主要瓶颈,提出亟待研究的若干关键技术问题和技术对策。本文对推动数值模拟软件计算能力与超级计算机峰值性能的同步提升具有参考价值。

关键词:超大规模;数值模拟;并行计算;超级计算机

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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