SPAWN: An Iterative, Potentials-Based, Dynamic Scheduling and Partitioning Tool

Jean-Charles Papin 1, 2 Christophe Denoual 2 Laurent Colombet 2 Raymond Namyst 3, 4
1 CMLA - Centre de Mathématiques et de Leurs Applications
2 DAM/DIF - DAM Île-de-France
3 STORM - STatic Optimizations, Runtime Methods
LaBRI - Laboratoire Bordelais de Recherche en Informatique, Inria Bordeaux - Sud-Ouest
4 UB - Université de Bordeaux
Abstract : Many applications of physics modeling use regular meshes on which computations of highly variable cost can occur. Distributing the underlying cells over manycore architec-tures is a critical load balancing step that should increase the period until another step is required. Graph partitioning tools are known to be very effective for such problems, but they exhibit scalability problems as the number of cores and the number of cells increases. We introduce a dynamic task scheduling approach inspired by physical particles interactions. Our method allows cores to virtually move over a 2D/3D mesh of tasks and uses a Voronoi domain decomposition to balance workload among cores. Displacements of cores are the result of force computations using a carefully chosen pair potential. We evaluate our method against graph partitioning tools and existing task schedulers with a representative physical application, and demonstrate the relevance of our approach.
Keywords : Simulation dynamic load-balancing tasks many- core pair potential graph partitioning
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Communication dans un congrès
SuperComputing'15 - RESPA Workshop, Nov 2015, Austin, United States. 〈http://respa15.rice.edu/〉
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Soumis le : mardi 3 novembre 2015 - 16:11:10
Dernière modification le : lundi 15 octobre 2018 - 15:54:03
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Jean-Charles Papin, Christophe Denoual, Laurent Colombet, Raymond Namyst. SPAWN: An Iterative, Potentials-Based, Dynamic Scheduling and Partitioning Tool. SuperComputing'15 - RESPA Workshop, Nov 2015, Austin, United States. 〈http://respa15.rice.edu/〉. 〈hal-01223897〉

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