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A Mean Field Model of Work Stealing in Large-Scale Systems

Nicolas Gast 1 Bruno Gaujal 1
1 MESCAL - Middleware efficiently scalable
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble [2007-2015]
Abstract : In this paper, we consider a generic model of computational grids, seen as several clusters of homogeneous processors. In such systems, a key issue when designing efficient job allocation policies is to balance the workload over the different resources. We present a Markovian model for performance evaluation of such a policy, namely work stealing (idle processors steal work from others) in large-scale heterogeneous systems. Using mean field theory, we show that when the size of the system grows, it converges to a system of deterministic ordinary differential equations that allows one to compute the expectation of performance functions (such as average response times) as well as the distributions of these functions.
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https://hal.inria.fr/hal-00788862
Contributor : Arnaud Legrand <>
Submitted on : Friday, February 15, 2013 - 1:09:40 PM
Last modification on : Thursday, July 9, 2020 - 9:44:36 AM

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Nicolas Gast, Bruno Gaujal. A Mean Field Model of Work Stealing in Large-Scale Systems. ACM sigmetrics, 2010, New-York, United States. pp.13-24, ⟨10.1145/1811039.1811042⟩. ⟨hal-00788862⟩

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