StarPU-MPI: Task Programming over Clusters of Machines Enhanced with AcceleratorsReport as inadecuate

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1 LaBRI - Laboratoire Bordelais de Recherche en Informatique 2 RUNTIME - Efficient runtime systems for parallel architectures Inria Bordeaux - Sud-Ouest, UB - Université de Bordeaux, CNRS - Centre National de la Recherche Scientifique : UMR5800

Abstract : GPUs clusters are becoming widespread HPC platforms. Ex- ploiting them is however challenging, as this requires two separate paradigms MPI and CUDA or OpenCL and careful load balancing due to node heterogeneity. Current paradigms usually either limit themselves to of- fload part of the computation and leave CPUs idle, or require static CPU-GPU work partitioning. We thus have previously proposed StarPU, a runtime system able to dynamically scheduling tasks within a single heterogeneous node. We show how we extended the task paradigm of StarPU with MPI to easily map the task graph on MPI clusters and automatically benefit from optimized execution.

Author: Cédric Augonnet - Olivier Aumage - Nathalie Furmento - Raymond Namyst - Samuel Thibault -



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