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GCSS:a global collaborative scheduling strategy for wide-area high-performance computing

查看全文 作　　者：Yao [1,2]SONG;Limin [1,2]XIAO;Liang [2]WANG;Guangjun [3]QIN;Bing [1,2]WEI;Baicheng [1,2]YAN;Chenhao [1,2]ZHANG 高影响力作者 机构地区：[1]State Key Laboratory of Software Development Environment,Beihang University,Beijing 100191,China;[2]School of Computer Science and Engineering,Beihang University,Beijing 100191,China;[3]Smart City College,Beijing Union University,Beijing 100101,China高影响力机构 出　　处：《Frontiers of Computer Science》索引2022年第16卷第5期,共15页高影响力期刊 基　　金：This work was supported by the National key R&D Program of China(2018YFB0203901);the National Natural Science Foundation of China under(Grant No.61772053);the fund of the State Key Laboratory of Software Development Environment(SKLSDE-2020ZX15). 摘　　要：Wide-area high-performance computing is widely used for large-scale parallel computing applications owing to its high computing and storage resources.However,the geographical distribution of computing and storage resources makes efficient task distribution and data placement more challenging.To achieve a higher system performance,this study proposes a two-level global collaborative scheduling strategy for wide-area high-performance computing environments.The collaborative scheduling strategy integrates lightweight solution selection,redundant data placement and task stealing mechanisms,optimizing task distribution and data placement to achieve efficient computing in wide-area environments.The experimental results indicate that compared with the state-of-the-art collaborative scheduling algorithm HPS+,the proposed scheduling strategy reduces the makespan by 23.24%,improves computing and storage resource utilization by 8.28%and 21.73%respectively,and achieves similar global data migration costs. 关 键 词：high-performance computing scheduling strategy task scheduling data placement
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