{"title":"Task clustering & scheduling with duplication using recursive critical path approach (RCPA)","authors":"A. Ebaid, R. Ammar, S. Rajasekaran, T. Fergany","doi":"10.1109/ISSPIT.2010.5711720","DOIUrl":null,"url":null,"abstract":"This paper address the problem of static task clustering and scheduling of a parallel program given as a Directed Acyclic Graph(DAG) with duplication. Scheduling of task graphs onto multiprocessors is known to be an NP-complete in most cases leading to solutions based on heuristics [1]. In this paper, a novel task-duplication scheduling heuristic is presented. Our approach differs from other heuristics found in literature since task clustering and scheduling are handled during the same phase. This technique omit the need of the independent clustering and scheduling phases (i.e., creating a cluster for every single task in the given DAG followed by the scheduling process) as in [2–6]. Preliminarily results shows that our algorithm outperforms PY, LWB, PLW, TCSD and LG algorithms in terms of the overall makespan, and total number of processors used.","PeriodicalId":308189,"journal":{"name":"The 10th IEEE International Symposium on Signal Processing and Information Technology","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 10th IEEE International Symposium on Signal Processing and Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSPIT.2010.5711720","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
This paper address the problem of static task clustering and scheduling of a parallel program given as a Directed Acyclic Graph(DAG) with duplication. Scheduling of task graphs onto multiprocessors is known to be an NP-complete in most cases leading to solutions based on heuristics [1]. In this paper, a novel task-duplication scheduling heuristic is presented. Our approach differs from other heuristics found in literature since task clustering and scheduling are handled during the same phase. This technique omit the need of the independent clustering and scheduling phases (i.e., creating a cluster for every single task in the given DAG followed by the scheduling process) as in [2–6]. Preliminarily results shows that our algorithm outperforms PY, LWB, PLW, TCSD and LG algorithms in terms of the overall makespan, and total number of processors used.