Scheduling multithreaded computations by work stealing

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Abstract
This paper studies the problem of efficiently scheduling fully strict (i.e., well-structured) multithreaded computations on parallel computers. A popular and practical method of scheduling this kind of dynamic MIMD-style computation is "work stealing," in which processors needing work steal computational threads from other processors. In this paper, we give the first provably good work-stealing scheduler for multithreaded computations with dependencies. Specifically, our analysis shows that the expected time T/sub P/ to execute a fully strict computation on P processors using our work-stealing scheduler is T/sub P/=O(T/sub 1//P+T/sub /spl infin//), where T/sub 1/ is the minimum serial execution time of the multithreaded computation and T/sub /spl infin// is the minimum execution time with an infinite number of processors. Moreover, the space S/sub P/ required by the execution satisfies S/sub P//spl les/S/sub 1/P. We also show that the expected total communication of the algorithm is at most O(T/sub /spl infin//S/sub max/P), where S/sub max/ is the size of the largest activation record of any thread, thereby justifying the folk wisdom that work-stealing schedulers are more communication efficient than their work-sharing counterparts. All three of these bounds are existentially optimal to within a constant factor.

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