2016
DOI: 10.1093/nsr/nww001
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High-performance computing environment: a review of twenty years of experiments in China

Abstract: A high-performance computing environment, also known as a supercomputing environment, e-Science environment or cyberinfrastructure, is a crucial system that connects users’ applications to supercomputers, and provides usability, efficiency, sharing, and collaboration capabilities. This review presents important lessons drawn from China's nationwide efforts to build and use a high-performance computing environment over the past 20 years (1995–2015), including three observations and two open problems. We present… Show more

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Cited by 17 publications
(9 citation statements)
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“…China's national HPC environment CNGrid (Xu et al 2016) is different from its counterparts in the US, Japan and Europe. It was established by research programs whose funding is for research and development but not for operation.…”
Section: Hpc Service Environmentmentioning
confidence: 98%
“…China's national HPC environment CNGrid (Xu et al 2016) is different from its counterparts in the US, Japan and Europe. It was established by research programs whose funding is for research and development but not for operation.…”
Section: Hpc Service Environmentmentioning
confidence: 98%
“…The thought has a curious coincidence with computational thinking, but it is more specific, vivid, maneuverable and executable compared to the latter. Xu et al presented that the computational lens and computational thinking lead to the emergence of a new computer science that is more universal and fundamental than the previous one in 2011, and the computer science is experiencing fundamental transformations, from its scope, objects of study, basic metrics, main abstractions, fundamental principles, to its relationship to other sciences and to the human society [19,20,21]. It happens that there is a similar case.…”
Section: A Computational Lensmentioning
confidence: 99%
“…simulations which involve either very computationally-intensive algorithms and/or very large datasets ('big data') were once restricted to being carried out on large, expensive supercomputers. The past twenty years has seen a dramatic rise in the use of distributed computing, fast desktop PCs, and GPU cluster supercomputers, together with a sharp drop in the overall implementation and running costs for 'big physics'-capable computation; see for example Fernández, Fernández, Miguel-Dávila, Conde, and Matellán (2019) and Xu, Chi, and Xiao (2016).…”
Section: Physics Simulations For Researchmentioning
confidence: 99%