Coscheduling has been shown to be a critical factor in achieving efficient parallel execution in timeshared environments [12, 19, 4]. However, the most common approach, gang scheduling, has limitations in scaling, can compromise good interactive response, and requires that communicating processes be identified in advance. We explore a technique called dynamic coscheduling (DCS) which produces emergent coscheduling of the processes constituting a parallel job. Experiments are performed in a workstation environment with high performance networks and autonomous timesharing schedulers for each CPU. The results demonstrate that DCS can achieve effective, robust coscheduling for a range of workloads and background loads. Empirical comparisons to implicit scheduling and uncoordinated scheduling are presented. Under spin-block synchronization, DCS reduces job response times by up to 20% over implicit scheduling while maintaining fairness; and under spinning synchronization, DCS reduces job response times by up to two decimal orders of magnitude over uncoordinated scheduling. The results suggest that DCS is a promising avenue for achieving coordinated parallel scheduling in an environment that coexists with autonomous node schedulers.
CITATION STYLE
Sobalvarro, P. G., Pakin, S., Weihl, W. E., & Chien, A. A. (1998). Dynamic coscheduling on workstation clusters. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1459, pp. 231–256). Springer Verlag. https://doi.org/10.1007/bfb0053990
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