{"title":"A Tie-Breaking Strategy for Processor Allocation in Meshes","authors":"Christopher R. Johnson, David P. Bunde, V. Leung","doi":"10.1109/ICPPW.2010.50","DOIUrl":null,"url":null,"abstract":"Many of the proposed algorithms for allocating processors to jobs in supercomputers choose arbitrarily among potential allocations that are \"equally good\" according to the allocation algorithm. In this paper, we add a parametrized tie-breaking strategy to the MC1x1 allocation algorithm for mesh supercomputers. This strategy attempts to favor allocations that preserve large regions of free processors, benefiting future allocations and improving machine performance. Trace-based simulations show the promise of our strategy; with good parameter choices, most jobs benefit and no class of jobs is harmed significantly.","PeriodicalId":415472,"journal":{"name":"2010 39th International Conference on Parallel Processing Workshops","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 39th International Conference on Parallel Processing Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPPW.2010.50","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Many of the proposed algorithms for allocating processors to jobs in supercomputers choose arbitrarily among potential allocations that are "equally good" according to the allocation algorithm. In this paper, we add a parametrized tie-breaking strategy to the MC1x1 allocation algorithm for mesh supercomputers. This strategy attempts to favor allocations that preserve large regions of free processors, benefiting future allocations and improving machine performance. Trace-based simulations show the promise of our strategy; with good parameter choices, most jobs benefit and no class of jobs is harmed significantly.
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