Extending a Work-Stealing Framework with Priorities and Weights

Nakashima, Ryusuke; Yoritaka, Hiroshi; Yasugi, Mariko; Hiraishi, Tasuku; Umatani, Seiji

doi:10.1109/ia349570.2019.00008

Cited by 2 publications

(3 citation statements)

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“…The retry loop corresponds to "all workers" in the node in steps ( 3 ) and ( 5) in Section 2.1. Unlike [7], [8], [9], we enable the retryloop option for all evaluations below. Furthermore, unlike [9], priority-based selection is properly applied even for task requests from external nodes.…”

Section: Evaluationsmentioning

confidence: 99%

“…Unlike [7], [8], [9], we enable the retryloop option for all evaluations below. Furthermore, unlike [9], priority-based selection is properly applied even for task requests from external nodes.…”

Section: Evaluationsmentioning

confidence: 99%

“…4 (b) with 96 (128) workers, priority-all, priority-3, weight, and relaxed-3 show 10.0% (12.4%), 4.5% (4.4%), 6.4% (9.5%), and 19.4% (16.5%) improvements over base and 0.7% (2.8%), −4.2% (−4.5%), −2.5% (0.1%), and 9.3% (6.5%) improvements over pg. When the retry-loop option is enabled, unlike [7], [8], [9], pg shows good speedups which are better than vpg.…”

Section: Evaluations In a Shared Memory Environmentmentioning

confidence: 99%

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Work-stealing Strategies That Consider Work Amount and Hierarchy

Nakashima

Yasugi

Yoritaka

et al. 2021

Journal of Information Processing

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This paper proposes work-stealing strategies for an idle worker (thief) to select a victim worker. These strategies avoid small tasks being stolen to reduce the total task-division cost. We implemented these strategies on a work-stealing framework called Tascell. First, we propose new types of priority-and weight-based steal strategies. Programmers can let each worker estimate and declare, as a real number, the amount of remaining work required to complete its current task so that declared values are used as "priorities" or "weights". With a priority-based strategy, a thief selects the victim that has the highest known priority at that time. With a weight-based non-uniformly random strategy, a thief uses the relative weights of victim candidates as their selection probabilities. Second, we propose work-stealing strategies to alleviate excessive intra-node work stealing and excessive "steal backs" (or leapfroggings); for example, we allow workers to steal tasks from external nodes with some frequency even if work remains inside the current node. Our evaluation uses a parallel implementation of the "highly serial" version of the Barnes-Hut force-calculation algorithm in a shared memory environment and five benchmark programs in a distributed memory environment.

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