License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.ICCSW.2013.144
URN: urn:nbn:de:0030-drops-42837
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2013/4283/
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Zhu, Huanzhou ; He, Ligang

A Graph based approach for Co-scheduling jobs on Multi-core computers

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Abstract

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.

BibTeX - Entry

@InProceedings{zhu_et_al:OASIcs:2013:4283,
  author =	{Huanzhou Zhu and Ligang He},
  title =	{{A Graph based approach for Co-scheduling jobs on Multi-core computers}},
  booktitle =	{2013 Imperial College Computing Student Workshop},
  pages =	{144--151},
  series =	{OpenAccess Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-63-7},
  ISSN =	{2190-6807},
  year =	{2013},
  volume =	{35},
  editor =	{Andrew V. Jones and Nicholas Ng},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2013/4283},
  URN =		{urn:nbn:de:0030-drops-42837},
  doi =		{10.4230/OASIcs.ICCSW.2013.144},
  annote =	{Keywords: Co-scheduling algorithm, Multicore processor, Cache interference, Parallel Job}
}

Keywords: Co-scheduling algorithm, Multicore processor, Cache interference, Parallel Job
Collection: 2013 Imperial College Computing Student Workshop
Issue Date: 2013
Date of publication: 14.10.2013

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