An Application-Level Scheduling with Task Bundling Approach for Many-Task Computing in Heterogeneous Environments

Abstract : Many-Task Computing (MTC) is a widely used computing paradigm for large-scale task-parallel processing. One of the key issues in MTC is to schedule a large number of independent tasks onto heterogeneous resources. Traditional task-level scheduling heuristics, like Min-Min, Sufferage and MaxStd, cannot readily be applied in this scenario. As most of MTC tasks are usually fine-grained, the resource management overhead would be prominent and the multi-core nodes might become hard to be fully utilized. In this paper we propose an application-level scheduling with task bundling approach that utilizes the knowledge of both applications and tasks to overcome these difficulties. Furthermore we adapt the traditional task-level heuristics to our model for MTC scheduling. Experimental results show that these application-level scheduling approaches, when equipped with task bundling, can deliver good performance for Many-Task Computing in terms of both Makespan and Flowtime.
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Communication dans un congrès
James J. Park; Albert Zomaya; Sang-Soo Yeo; Sartaj Sahni. 9th International Conference on Network and Parallel Computing (NPC), Sep 2012, Gwangju, South Korea. Springer, Lecture Notes in Computer Science, LNCS-7513, pp.1-13, 2012, Network and Parallel Computing. 〈10.1007/978-3-642-35606-3_1〉
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Jian Xiao, Yu Zhang, Shuwei Chen, Huashan Yu. An Application-Level Scheduling with Task Bundling Approach for Many-Task Computing in Heterogeneous Environments. James J. Park; Albert Zomaya; Sang-Soo Yeo; Sartaj Sahni. 9th International Conference on Network and Parallel Computing (NPC), Sep 2012, Gwangju, South Korea. Springer, Lecture Notes in Computer Science, LNCS-7513, pp.1-13, 2012, Network and Parallel Computing. 〈10.1007/978-3-642-35606-3_1〉. 〈hal-01551355〉

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