Scheduling of Linear Algebra Kernels on Multiple Heterogeneous Resources

Olivier Beaumont 1 Terry Cojean 2 Lionel Eyraud-Dubois 1 Abdou Guermouche 3 Suraj Kumar 2
1 Realopt - Reformulations based algorithms for Combinatorial Optimization
LaBRI - Laboratoire Bordelais de Recherche en Informatique, IMB - Institut de Mathématiques de Bordeaux, Inria Bordeaux - Sud-Ouest
2 STORM - STatic Optimizations, Runtime Methods
LaBRI - Laboratoire Bordelais de Recherche en Informatique, Inria Bordeaux - Sud-Ouest
3 HiePACS - High-End Parallel Algorithms for Challenging Numerical Simulations
LaBRI - Laboratoire Bordelais de Recherche en Informatique, Inria Bordeaux - Sud-Ouest
Abstract : In this paper, we consider task-based dense linear algebra applications on a single heterogeneous node which contains regular CPU cores and a set of GPU devices. Efficient scheduling strategies are crucial in this context in order to achieve good and portable performance. HeteroPrio, a resource-centric dynamic scheduling strategy has been introduced in a previous work and evaluated for the special case of nodes with exactly two types of resources. However, this restriction can be limiting, for example on nodes with several types of accelerators, but not only this. Indeed, an interesting approach to increase resource usage is to group several CPU cores together, which allows to use intra-task parallelism. We propose a generalization of HeteroPrio to the case with several classes of heterogeneous workers. We provide extensive evaluation of this algorithm with Cholesky factorization, both through simulation and actual execution, compared with HEFT-based scheduling strategy, the state of the art dynamic scheduling strategy for heterogeneous systems. Experimental evaluation shows that our approach is efficient even for highly heterogeneous configurations and significantly outperforms HEFT-based strategy.
Type de document :
Communication dans un congrès
International Conference on High Performance Computing, Data, and Analytics (HiPC 2016), Dec 2016, Hyderabad, India. IEEE, 2016, Proceedings of the IEEE International Conference on High Performance Computing (HiPC 2016). <http://www.hipc.org/hipc2016/>
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https://hal.inria.fr/hal-01361992
Contributeur : Suraj Kumar <>
Soumis le : vendredi 23 septembre 2016 - 13:40:02
Dernière modification le : lundi 9 janvier 2017 - 07:25:46

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Olivier Beaumont, Terry Cojean, Lionel Eyraud-Dubois, Abdou Guermouche, Suraj Kumar. Scheduling of Linear Algebra Kernels on Multiple Heterogeneous Resources. International Conference on High Performance Computing, Data, and Analytics (HiPC 2016), Dec 2016, Hyderabad, India. IEEE, 2016, Proceedings of the IEEE International Conference on High Performance Computing (HiPC 2016). <http://www.hipc.org/hipc2016/>. <hal-01361992v2>

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