DE OLIVEIRA CASTRO, Pablo; LOUISE, Stéphane; BARTHOU, Denis

doi:10.1109/HPCS.2010.5547134

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DE OLIVEIRA CASTRO, Pablo
Laboratoire d'Intégration des Systèmes et des Technologies [LIST (CEA)]

LOUISE, Stéphane
Laboratoire d'Intégration des Systèmes et des Technologies [LIST (CEA)]

BARTHOU, Denis
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Efficient runtime systems for parallel architectures [RUNTIME]

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International IEEE Conference on High Performance Computing and Simulation, International IEEE Conference on High Performance Computing and Simulation, International IEEE Conference on High Performance Computing and Simulation, 2011-06-28, Caen. 2010-06-28p. p171-180

Résumé en anglais

Stream languages explicitly describe fork-join parallelism and pipelines, offering a powerful programming model for many-core Multi-Processor Systems on Chip (MPSoC). In an embedded resource-constrained system, adapting stream programs to fit memory requirements is particularly important. In this paper we present a new approach to re- duce the memory footprint required to run stream programs on MPSoC. Through an exploration of equivalent program variants, the method selects parallel code minimizing mem- ory consumption. For large program instances, a heuristic accelerating the exploration phase is proposed and evalu- ated. We demonstrate the interest of our method on a panel of ten significant benchmarks. Using a multi-core modulo scheduling technique, our approach lowers considerably the minimal amount of memory required to run seven of these benchmarks while preserving throughput.< Réduire

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Graph Transformations

Stream Languages

Data Flow

Mem- ory

Graph Transformations.

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Reducing Memory Requirements of Stream Programs by Graph Transformations

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