{"title":"Callisto:协同调度并行运行时系统","authors":"T. Harris, Martin Maas, Virendra J. Marathe","doi":"10.1145/2592798.2592807","DOIUrl":null,"url":null,"abstract":"It is increasingly important for parallel applications to run together on the same machine. However, current performance is often poor: programs do not adapt well to dynamically varying numbers of cores, and the CPU time received by concurrent jobs can differ drastically. This paper introduces Callisto, a resource management layer for parallel runtime systems. We describe Callisto and the implementation of two Callisto-enabled runtime systems---one for OpenMP, and another for a task-parallel programming model. We show how Callisto eliminates almost all of the scheduler-related interference between concurrent jobs, while still allowing jobs to claim otherwise-idle cores. We use examples from two recent graph analytics projects and from SPEC OMP.","PeriodicalId":20737,"journal":{"name":"Proceedings of the Eleventh European Conference on Computer Systems","volume":"3 1","pages":"24:1-24:14"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"63","resultStr":"{\"title\":\"Callisto: co-scheduling parallel runtime systems\",\"authors\":\"T. Harris, Martin Maas, Virendra J. Marathe\",\"doi\":\"10.1145/2592798.2592807\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"It is increasingly important for parallel applications to run together on the same machine. However, current performance is often poor: programs do not adapt well to dynamically varying numbers of cores, and the CPU time received by concurrent jobs can differ drastically. This paper introduces Callisto, a resource management layer for parallel runtime systems. We describe Callisto and the implementation of two Callisto-enabled runtime systems---one for OpenMP, and another for a task-parallel programming model. We show how Callisto eliminates almost all of the scheduler-related interference between concurrent jobs, while still allowing jobs to claim otherwise-idle cores. We use examples from two recent graph analytics projects and from SPEC OMP.\",\"PeriodicalId\":20737,\"journal\":{\"name\":\"Proceedings of the Eleventh European Conference on Computer Systems\",\"volume\":\"3 1\",\"pages\":\"24:1-24:14\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"63\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Eleventh European Conference on Computer Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2592798.2592807\",\"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 the Eleventh European Conference on Computer Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2592798.2592807","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
It is increasingly important for parallel applications to run together on the same machine. However, current performance is often poor: programs do not adapt well to dynamically varying numbers of cores, and the CPU time received by concurrent jobs can differ drastically. This paper introduces Callisto, a resource management layer for parallel runtime systems. We describe Callisto and the implementation of two Callisto-enabled runtime systems---one for OpenMP, and another for a task-parallel programming model. We show how Callisto eliminates almost all of the scheduler-related interference between concurrent jobs, while still allowing jobs to claim otherwise-idle cores. We use examples from two recent graph analytics projects and from SPEC OMP.