Article information
2018 , Volume 23, ¹ 1, p.85-95
Rakitskiy A.A., Ryabko B.Y.
Informational-theoretical approach to the evaluation of supercomputers
In this paper we present the informational-theoretical approach to the evaluation of performance for supercomputers. This approach is based on the computer capacity characteristic which can be estimated theoretically (without any experiments over the working model of the investigated computer) relying on the description of the architecture of the system under study. We describe the method for estimation of the supercomputers Computer capacity which takes into account the influence of the interprocess communication. The described method is used in this paper to estimate the performance of the five supercomputers among the first fifty positions in TOP500 list (according to November 2016 data). The obtained results are compared with the values of LINPACK benchmark and Theoretical peak characteristic which are used to form the TOP500 rating. Based on the comparison we draw conclusions about the applicability of the presented approach to the evaluation of supercomputers performance at the design stage.
[full text] Keywords: performance, computer capacity, supercomputer, information theory, processor
doi: 10.5072/ICT.2018.1.11999
Author(s): Rakitskiy Anton Andreevich PhD. , Associate Professor Office: Siberian State University of Telecommunications and Informatics Address: 630102, Russia, Novosibirsk
E-mail: rakitsky.anton@gmail.com SPIN-code: 7056-8681Ryabko Boris Yakovlevich Dr. , Professor Position: Head of Laboratory Office: Federal Research Center for Information and Computational Technologies, Novosibirsk State University Address: 630090, Russia, Novosibirsk, Academician M.A. Lavrentiev avenue, 6
Phone Office: (383) 334-91-24 E-mail: boris@ryabko.net SPIN-code: 5580-5794 References: [1] Weicker, R.P. A detailed look at some popular benchmarks. Parallel Computing. 1991; (17):1153–1172.
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Bibliography link: Rakitskiy A.A., Ryabko B.Y. Informational-theoretical approach to the evaluation of supercomputers // Computational technologies. 2018. V. 23. ¹ 1. P. 85-95
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