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공공누리This item is licensed Korea Open Government License

Title
Composite Measures of Supercomputer Technology
Author(s)
김남규이종숙고명주조근태온누리
Publisher
Korean Society for Internet Information
Publication Year
2019-08-31
Abstract
We have developed composite measures of supercomputer technology, reflecting various factors of supercomputers using Martino's scoring model. CPUs, accelerators, memory, interconnection networks, and power consumption are chosen as factors of the model. The weight values of the factors are derived based on a survey of 129 domestic and international experts. The measured values are then standardized to integrate measurement units of the factors in the model. This model has been applied to 50 supercomputers, and rank correlation analysis was performed using representative measures. As a consequence, the ranking drastically changes except for the 1st and 2nd supercomputers on the TOP500. In addition, the characteristics of memory and interconnection networks influence the ranking, and the results demonstrate that the proposed model has low correlations with HPL and HPCG but a high correlation with Green500. This indicates that power consumption is an important factor that has a significant effect on the measures of supercomputer technology. In addition, it is determined that the differences between the HPL ranking and the proposed model ranking are influenced by power consumption, CPU theoretical peak performance, and main memory bandwidth in order of significance. In conclusion, the composite measures proposed in this study are more suitable for comprehensively describing supercomputer technology than existing performance measures. The findings of this study are expected to support decision making related to management and policy in the procurement and operation of supercomputers.
Keyword
복합측정; 기술수준측정; 점수제모형; 슈퍼컴퓨터성능; 슈퍼컴퓨터정책; Composite Measures; Measures of Technology; Scoring Model; Supercomputer Performance; Supercomputer policy
Journal Title
KSII Transactions on internet and information systems : TIIS;
Citation Volume
13
ISSN
1976-7277
DOI
10.3837/tiis.2019.08.018
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Appears in Collections:
7. KISTI 연구성과 > 학술지 발표논문
URI
https://repository.kisti.re.kr/handle/10580/16241
Fulltext
 https://scienceon.kisti.re.kr/srch/selectPORSrchArticle.do?cn=JAKO201926358473643
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