GCSS: a global collaborative scheduling strategy for wide-area high-performance computing |
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Authors: | Yao SONG Limin XIAO Liang WANG Guangjun QIN Bing WEI Baicheng YAN Chenhao ZHANG |
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Affiliation: | 1. State Key Laboratory of Software Development Environment, Beihang University, Beijing 100191, China2. School of Computer Science and Engineering, Beihang University, Beijing 100191, China3. Smart City College, Beijing Union University, Beijing 100101, China |
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Abstract: | 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. |
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Keywords: | high-performance computing scheduling strategy task scheduling data placement |
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