Abstract | ||
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In a multicore processor system, running multiple applications on different cores in the same chip could cause resource contention, which leads to performance degradation. Recent studies have shown that job co-scheduling can effectively reduce the contention. However, most existing co-schedulers do not aim to find the optimal co-scheduling solution. It is very useful to know the optimal co-scheduling performance so that the system and scheduler designers can know how much room there is for further performance improvement. Moreover, most co-schedulers only consider serial jobs, and do not take parallel jobs into account. This paper aims to tackle the above issues. In this paper, we first present a new approach to modelling the problem of co-scheduling both parallel and serial jobs. Further, a method is developed to find the optimal co-scheduling solutions. The simulation results show that compare to the method that only considers serial jobs, our developed method to co-schedule parallel jobs can improve the performance by 31% on average. |
Year | DOI | Venue |
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2013 | 10.4230/OASIcs.ICCSW.2013.144 | ICCSW |
Field | DocType | Volume |
Graph,Know-how,Co scheduling,Resource contention,Computer science,Parallel computing,Chip,Multi-core processor,Distributed computing,Performance improvement | Conference | 35 |
Citations | PageRank | References |
1 | 0.36 | 0 |
Authors | ||
2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Huanzhou Zhu | 1 | 11 | 2.19 |
Ligang He | 2 | 542 | 56.73 |