Design-Space Exploration of Stream Programs through Semantic-Preserving Transformations

Pablo de Oliveira Castro (1) , Stéphane Louise (1) , Denis Barthou (2)

1 LIST (CEA) - Laboratoire d'Intégration des Systèmes et des Technologies
2 LaBRI - Laboratoire Bordelais de Recherche en Informatique

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 design-space exploration technique to reduce the minimal memory required when running stream programs on MPSoC; this allows to target memory constrained systems and in some cases obtain better performance. Using a set of semantically preserving transformations, we explore a large number of equivalent program variants; we select the variant that minimizes a buffer evaluation metric. To cope efficiently with large program instances we propose and evaluate an heuristic for this method. We demonstrate the interest of our method on a panel of ten significant benchmarks. As an illustration, we measure the minimal memory required using a multi-core modulo scheduling. Our approach lowers considerably the minimal memory required for seven of the ten benchmarks.

Mots clés: stream; graph; embedded; memory; csdf; transformations; design-space; parallel; multi-core; MPSOC

Domaines: Calcul parallèle, distribué et partagé [cs.DC]

Pablo de Oliveira Castro, Stéphane Louise, Denis Barthou. Design-Space Exploration of Stream Programs through Semantic-Preserving Transformations. 2009. ⟨hal-00447376⟩