{"title":"TaskFlow","authors":"L. Versluis, A. Iosup","doi":"10.1145/3491204.3527466","DOIUrl":null,"url":null,"abstract":"Datacenters need to become more power efficient for political and climate reasons. In this work, we introduce an idea for the community to further explore. We embed the idea in TaskFlow: a makespan conservative, energy-aware task placement policy for workflow scheduling. Using static, rough numbers and simulation, we obtain energy savings between [4.24, 47.00]% and [0.1, 13.6]%, respectively. We also present some pitfalls that should be investigated further, notably starvation of large tasks when using TaskFlow.","PeriodicalId":129216,"journal":{"name":"Companion of the 2022 ACM/SPEC International Conference on Performance Engineering","volume":"313 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"TaskFlow\",\"authors\":\"L. Versluis, A. Iosup\",\"doi\":\"10.1145/3491204.3527466\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Datacenters need to become more power efficient for political and climate reasons. In this work, we introduce an idea for the community to further explore. We embed the idea in TaskFlow: a makespan conservative, energy-aware task placement policy for workflow scheduling. Using static, rough numbers and simulation, we obtain energy savings between [4.24, 47.00]% and [0.1, 13.6]%, respectively. We also present some pitfalls that should be investigated further, notably starvation of large tasks when using TaskFlow.\",\"PeriodicalId\":129216,\"journal\":{\"name\":\"Companion of the 2022 ACM/SPEC International Conference on Performance Engineering\",\"volume\":\"313 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Companion of the 2022 ACM/SPEC International Conference on Performance Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3491204.3527466\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Companion of the 2022 ACM/SPEC International Conference on Performance Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3491204.3527466","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Datacenters need to become more power efficient for political and climate reasons. In this work, we introduce an idea for the community to further explore. We embed the idea in TaskFlow: a makespan conservative, energy-aware task placement policy for workflow scheduling. Using static, rough numbers and simulation, we obtain energy savings between [4.24, 47.00]% and [0.1, 13.6]%, respectively. We also present some pitfalls that should be investigated further, notably starvation of large tasks when using TaskFlow.
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