Waste-Efficient Work Stealing

ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming 2026 Open access

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Authors: Kyle Singer, Kunal Agrawal, Tao Benjamin Schardl
DOI: 10.1145/3774934.3786452
Cited by: 0
References: 22

Abstract

Although randomized work stealing is effective at automatically load-balancing task-parallel programs, it can waste computational resources when scheduling programs that lack sufficient parallelism to use all available threads. For such programs, threads will waste cycles attempting to steal parallel tasks when none are available. This waste can reduce the machine’s efficiency by wasting computational resources and energy and needlessly burdening the operating system.

Fields of Study & Subjects

Parallel Computing and Optimization Techniques Distributed and Parallel Computing Systems Distributed systems and fault tolerance

Publication details

Journal / source
ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
Pages
68–80
Publication date
28 January 2026
Language
EN