Adaptive Online Scheduling of Task Graphs with Dynamic Resilience
文献类型:期刊论文
作者 | Menglan Hu; Jun Luo; Yang Wang; Bharadwaj Veeravalli |
刊名 | IEEE Transactions on Computers
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出版日期 | 2017 |
文献子类 | 期刊论文 |
英文摘要 | This paper studies a scheduling problem of task graphs on a non-dedicated networked computing platform. The networked platform is characterized by a set of fully connected processors such as a multiprocessor system that can be shared by multiple tasks. Therefore, the computation and communication capacities of the computing platform dynamically fluctuate. To deal with this fluctuations for high performance task graph computing, we propose an online dynamic resilience scheduling algorithm called Adaptive Scheduling Algorithm (ASA) that bears certain distinct features compared to existing algorithms. First, the proposed algorithm deliberately assigns tasks to idle processors in multiple rounds to prevent any unfavorable decisions and also to avoid inefficient assignments of certain key tasks to slow processors. Second, the algorithm adopts task duplication as an attempt to minimize serious increase of schedule length due to unexpected processor slowdown. Finally, a look-ahead message transmission policy is applied to save communication time and further improve the overall performance. Performance evaluation results are presented to demonstrate the effectiveness and competitiveness of our approaches when compared with the existing algorithms. |
URL标识 | 查看原文 |
语种 | 英语 |
源URL | [http://ir.siat.ac.cn:8080/handle/172644/12518] ![]() |
专题 | 深圳先进技术研究院_数字所 |
作者单位 | IEEE Transactions on Computers |
推荐引用方式 GB/T 7714 | Menglan Hu,Jun Luo,Yang Wang,et al. Adaptive Online Scheduling of Task Graphs with Dynamic Resilience[J]. IEEE Transactions on Computers,2017. |
APA | Menglan Hu,Jun Luo,Yang Wang,&Bharadwaj Veeravalli.(2017).Adaptive Online Scheduling of Task Graphs with Dynamic Resilience.IEEE Transactions on Computers. |
MLA | Menglan Hu,et al."Adaptive Online Scheduling of Task Graphs with Dynamic Resilience".IEEE Transactions on Computers (2017). |
入库方式: OAI收割
来源:深圳先进技术研究院
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