
FOLLOWUS
CAEP Software Center for High Performance Numerical Simulation, Beijing 100088, China
Institute of Applied Physics and Computational Mathematics, Beijing 100094, China
[ "Ze-yao MO, E-mail: zeyao_mo@iapcm.ac.cn" ]
收稿:2018-07-07,
修回:2018-10-15,
纸质出版:2018-10
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莫则尧. 超大规模并行计算:瓶颈与对策[J]. 信息与电子工程前沿(英文), 2018,19(10):1251-1260.
Ze-yao MO. Extreme-scale parallel computing: bottlenecks and strategies[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(10): 1251-1260.
莫则尧. 超大规模并行计算:瓶颈与对策[J]. 信息与电子工程前沿(英文), 2018,19(10):1251-1260. DOI: 10.1631/FITEE.1800421.
Ze-yao MO. Extreme-scale parallel computing: bottlenecks and strategies[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(10): 1251-1260. DOI: 10.1631/FITEE.1800421.
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。
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.
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