Журнал «Информационные технологии и вычислительные системы» - A. V. Alekseev, A. V. Chernov, K. A. Subareva, A. A. Holostov, V. A. Sviridov High-Performance Computing Systems. Development of Normative Base

Просматривается номер 2022 / 03

COMPUTING SYSTEMS AND NETWORKS

A. V. Alekseev, A. V. Chernov, K. A. Subareva, A. A. Holostov, V. A. Sviridov High-Performance Computing Systems. Development of Normative Base

INTELLIGENCE SYSTEMS AND TECHNOLOGIES

V. V. Arlazarov Analysis of the Usage of Problem-Oriented Datasets in Scientific Research

I. A. Krivosheev, M. A. Linnik Dynamic Algorithm of Steganographic Information Embedding Based on LSB

N. Z. Valishina, S. A. Ilyuhin, A.V. Sheshkus, V. L. Arlazarov Automatic Training Data Filtering for Errors Removing and Improving the Quality of the Final Neural Network

V. A. Fedorenko, K. O. Sorokina, P. V. Giverts Multigroup classification of Firing Pin Marks with the use of a Fully Connected Neural Network

V. O. Sirotyuk Methods for Constructing and Analyzing an Ontological Model and a Master Database of a Digital Intellectual Property Fund

MATHEMATICAL MODELING

A.Y. Popkov, Y.A. Dubnov, Y.S. Popkov Forecasting of COVID-19 Dynamics in EU Using Randomized Machine Learning Applied to Dynamic Models

A. V. Smirnov, E. G. Moll, N. N. Teslya Consideration of Human Factors Influence on the Process of Socially-Oriented Decisions Making During Hospitalization in an Epidemic

A. A. Zuenko, A. G. Oleynik, Y. A. Oleynik Integration of Conceptual Modeling and Constraint Programming for the Synthesis of Flowsheets

B. A. Avdeev , A. V. Vyngra , S.G. Chernyi Investigation of the Operation of a Two-Circuit Control System for a Direct Current Propulsion Electric Drive of Autonomous Underwater Vehicles with Parametric Correction


	A. V. Alekseev, A. V. Chernov, K. A. Subareva, A. A. Holostov, V. A. Sviridov High-Performance Computing Systems. Development of Normative Base
Abstract. Currently, the Russian Federation does not have a regulatory and technical framework for determining requirements for high-performance computing systems. High-performance computing systems are a separate type of product with their own properties and characteristics that necessitate the development of appropriate regulatory and technical documents. This article describes the experience of the Technical Committee for Standardization «Mathematical modeling and high performance computing technologies»in developing a regulatory and technical framework that establishes specific requirements for high-performance computing systems. The results of this work are reflected in three national standards defining the terminology, the procedure for conducting acceptance tests of high-performance computing systems, as well as the requirements for test programs. Keywords: high-performance computing system, acceptance testing, standardization, regulatory and technical framework, test program. PP. 3-9. DOI 10.14357/20718632220301 References 1. GOST 34.603–92. 2009. Information technology. Types tests automated systems. Moscow: StandardinformPubls. 6 p. 2. GOST R 15.301–2016. 2018. System of product development and launching into manufacture. Products of industrial and technical designation. Procedure of product development and launching into manufacture. Moscow: StandardinformPubls. 15 p. 3. GOST R 57700.26–2020. 2020. High-perfomance computing systems. Acceptance tests requirements. Moscow: StandardinformPubls. 12 p. 4. GOST R 57700.18–2019. 2019. High-perfomance computing systems. Requirements for acceptance test programs. Moscow: StandardinformPubls. 8 p. 5. GOST R 57700.27–2020. 2018. High-performance computing systems. Terms and definitions. Moscow: StandardinformPubls. 20 p. 6. HPL information [Electronic resource]. URL: http://icl.cs.utk.edu. 7. Stream information [Electronic resource]. URL: http://reality.sgi.com/employees/mccalpin_asd . 8. IOR information [Electronic resource]. URL: https://githab.com/VI4IO/io-500-dev . 9. b_eff information [Electronic resource]. URL: www.hlrs.de/mpi/b_eff. 10. HPCG information [Electronic resource]. URL: www.hpcg-benchmark.org . 11. NPB information [Electronic resource]. URL: http://www.nas.nasa.gov/Software/NPB . 12. Alekseev A.V., Belyaev S.P., Bochkov A.I. et al. Methodological application tests developed at RFNC-VNIIEF for numerically studying parameters of HPC systems // VANT. Ser.: Mathematical simulation of physical processes. 2020. No 2. P. 86–100.

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