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2008

Adaptive work-stealing with parallelism feedback

11 years 9 months ago
Adaptive work-stealing with parallelism feedback
We present an adaptive work-stealing thread scheduler, ASTEAL, for fork-join multithreaded jobs, like those written using the Cilk multithreaded language or the Hood work-stealing library. The A-STEAL algorithm is appropriate for large parallel servers where many jobs share a common multiprocessor resource and in which the number of processors available to a particular job may vary during the job's execution. A-STEAL provides continual parallelism feedback to a job scheduler in the form of processor requests, and the job must adapt its execution to the processors allotted to it. Assuming that the job scheduler never allots any job more processors than requested by the job's thread scheduler, A-STEAL guarantees that the job completes in near-optimal time while utilizing at least a constant fraction of the allotted processors. Our analysis models the job scheduler as the thread scheduler's adversary, challenging the thread scheduler to be robust to the system environment ...
Kunal Agrawal, Charles E. Leiserson, Yuxiong He, W
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2008
Where TOCS
Authors Kunal Agrawal, Charles E. Leiserson, Yuxiong He, Wen-Jing Hsu
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