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Harnessing clusters of hybrid nodes with a sequential task-based programming model

Emmanuel Agullo 1 Olivier Aumage 2 Mathieu Faverge 3, 1 Nathalie Furmento 2 Florent Pruvost 1 Marc Sergent 4, 5 Samuel Thibault 2, 4
1 HiePACS - High-End Parallel Algorithms for Challenging Numerical Simulations
LaBRI - Laboratoire Bordelais de Recherche en Informatique, Inria Bordeaux - Sud-Ouest
2 LaBRI - Laboratoire Bordelais de Recherche en Informatique
3 ICL - Innovative Computing Laboratory [Knoxville]
4 STORM - STatic Optimizations, Runtime Methods
LaBRI - Laboratoire Bordelais de Recherche en Informatique, Inria Bordeaux - Sud-Ouest
5 CEA-CESTA - Commissariat à l'Energie Atomique et aux Energies Alternatives
Abstract : Runtime systems usually abstract a single node. The Sequential Task Flow (STF) model has been proven efficient on shared memory applications. When harnessing cluster of nodes, how should they communicate? By using explicit MPI user calls ? By using a specific paradigm ? Or can we keep the same STF paradigm and almost the same code, and leave the runtime system handle data transfers? We show how such a system has been sucessfully implemented on top of the StarPU runtime.
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https://hal.inria.fr/hal-01283949
Contributor : Marc Sergent <>
Submitted on : Monday, March 7, 2016 - 10:35:13 AM
Last modification on : Wednesday, October 14, 2020 - 9:34:02 AM
Long-term archiving on: : Sunday, November 13, 2016 - 8:10:42 AM

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  • HAL Id : hal-01283949, version 1

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Emmanuel Agullo, Olivier Aumage, Mathieu Faverge, Nathalie Furmento, Florent Pruvost, et al.. Harnessing clusters of hybrid nodes with a sequential task-based programming model. International Workshop on Parallel Matrix Algorithms and Applications (PMAA 2014), Jul 2014, Lugano, Switzerland. ⟨hal-01283949⟩

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