{"title":"估算时间扭曲中节流执行的成本","authors":"Samir R Das","doi":"10.1109/PADS.1996.761577","DOIUrl":null,"url":null,"abstract":"Over-optimistic execution has long been identified as a major performance bottleneck in Time Warp based parallel simulation systems. An appropriate throttle or control of optimism can improve performance by reducing the number of rollbacks. However, the design of an appropriate throttle is a difficult task, as correct computations on the critical path may be blocked, thus increasing the overall execution time. In this paper we build a cost model for throttled execution that involves both rollback probability and probability for an event computation being on the critical path. The model can estimate an appropriate size of time window for a throttled execution using statistics collected from the purely optimistic execution. The model is validated by an experimental study with a set of synthetic workloads.","PeriodicalId":326232,"journal":{"name":"Proceedings of Symposium on Parallel and Distributed Tools","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Estimating the Cost of Throttled Execution in Time Warp\",\"authors\":\"Samir R Das\",\"doi\":\"10.1109/PADS.1996.761577\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Over-optimistic execution has long been identified as a major performance bottleneck in Time Warp based parallel simulation systems. An appropriate throttle or control of optimism can improve performance by reducing the number of rollbacks. However, the design of an appropriate throttle is a difficult task, as correct computations on the critical path may be blocked, thus increasing the overall execution time. In this paper we build a cost model for throttled execution that involves both rollback probability and probability for an event computation being on the critical path. The model can estimate an appropriate size of time window for a throttled execution using statistics collected from the purely optimistic execution. The model is validated by an experimental study with a set of synthetic workloads.\",\"PeriodicalId\":326232,\"journal\":{\"name\":\"Proceedings of Symposium on Parallel and Distributed Tools\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of Symposium on Parallel and Distributed Tools\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PADS.1996.761577\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of Symposium on Parallel and Distributed Tools","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PADS.1996.761577","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Estimating the Cost of Throttled Execution in Time Warp
Over-optimistic execution has long been identified as a major performance bottleneck in Time Warp based parallel simulation systems. An appropriate throttle or control of optimism can improve performance by reducing the number of rollbacks. However, the design of an appropriate throttle is a difficult task, as correct computations on the critical path may be blocked, thus increasing the overall execution time. In this paper we build a cost model for throttled execution that involves both rollback probability and probability for an event computation being on the critical path. The model can estimate an appropriate size of time window for a throttled execution using statistics collected from the purely optimistic execution. The model is validated by an experimental study with a set of synthetic workloads.