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.
@InProceedings{zhu_et_al:OASIcs.ICCSW.2013.144, author = {Zhu, Huanzhou and He, Ligang}, title = {{A Graph based approach for Co-scheduling jobs on Multi-core computers}}, booktitle = {2013 Imperial College Computing Student Workshop}, pages = {144--151}, series = {Open Access Series in Informatics (OASIcs)}, ISBN = {978-3-939897-63-7}, ISSN = {2190-6807}, year = {2013}, volume = {35}, editor = {Jones, Andrew V. and Ng, Nicholas}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICCSW.2013.144}, 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} }
Feedback for Dagstuhl Publishing