T h e I m p a c t of Job Arrival P a t t e r n s on Parallel S c h e d u l i n g M a r k S. Squillante IBM T.J. Watson Research Center Yorktown Heights, NY 10598 ross@watson.ibm.corn David D. Yao The Chinese University of Hong Kong Shatin, N.T., Hong Kong yao@se.cuhk.edu.hk Li Z h a n g IBM T.J. Watson Research Center Yorktown Heights, NY 10598 zhangl@watson.ibm.com Abstract In this paper we present an initial analysis of the job arrival patterns from a real parallel computing system and we develop a class of traJ~c models to characterize these arrival patterns. Our analysis of the job arrival data illustrates traffic patterns that exhibit heavy-tail behavior and other characteristics which are quite different from the arrival processes used in previous studies of parallel scheduling. We then investigate the impact of these arrival traffic patterns on the performance of parallel space-sharing scheduling strategies. Introduction The scheduling of computing resources among the parallel jobs submitted for execution is a fundamental aspect of parallel processing systems. Several classes of scheduling strategies have been proposed for such computing environments, each differing in the
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The impact of job arrival patterns on parallel scheduling
Squillante, Mark S.; Yao, David D.; Zhang, Li
Follow ACM SIGMETRICS Performance Evaluation Review
, Volume 26 (4)
Association for Computing Machinery – Mar 1, 1999
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