{"title":"SCOJO的自适应时间/空间共享","authors":"A. Sodan, Xuemin Huang","doi":"10.1504/IJHPCN.2006.013481","DOIUrl":null,"url":null,"abstract":"Time-shared execution of parallel jobs via gang scheduling is known to yield better average response times than space sharing. We incorporate adaptive CPU/node-resource allocation to consider varying system load and to reduce fragmentation. As main innovations, our SCOJO approach provides a clear model how to adapt, and considers realistic job mixes with moldable, malleable and rigid jobs. Our adaptive SCOJO significantly decreases response times and average slowdowns, while using a lower multiprogramming level than standard gang scheduling uses best and, therefore, decreasing the memory pressure. These benefits apply though the realistic job mixes limit the flexibility in resource allocation.","PeriodicalId":384857,"journal":{"name":"International Journal of High Performance Computing and Networking","volume":"122 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Adaptive time/space sharing with SCOJO\",\"authors\":\"A. Sodan, Xuemin Huang\",\"doi\":\"10.1504/IJHPCN.2006.013481\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Time-shared execution of parallel jobs via gang scheduling is known to yield better average response times than space sharing. We incorporate adaptive CPU/node-resource allocation to consider varying system load and to reduce fragmentation. As main innovations, our SCOJO approach provides a clear model how to adapt, and considers realistic job mixes with moldable, malleable and rigid jobs. Our adaptive SCOJO significantly decreases response times and average slowdowns, while using a lower multiprogramming level than standard gang scheduling uses best and, therefore, decreasing the memory pressure. These benefits apply though the realistic job mixes limit the flexibility in resource allocation.\",\"PeriodicalId\":384857,\"journal\":{\"name\":\"International Journal of High Performance Computing and Networking\",\"volume\":\"122 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-08-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of High Performance Computing and Networking\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJHPCN.2006.013481\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of High Performance Computing and Networking","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJHPCN.2006.013481","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Time-shared execution of parallel jobs via gang scheduling is known to yield better average response times than space sharing. We incorporate adaptive CPU/node-resource allocation to consider varying system load and to reduce fragmentation. As main innovations, our SCOJO approach provides a clear model how to adapt, and considers realistic job mixes with moldable, malleable and rigid jobs. Our adaptive SCOJO significantly decreases response times and average slowdowns, while using a lower multiprogramming level than standard gang scheduling uses best and, therefore, decreasing the memory pressure. These benefits apply though the realistic job mixes limit the flexibility in resource allocation.