A unified runtime system for heterogeneous multicore architectures
AUGONNET, Cédric
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Efficient runtime systems for parallel architectures [RUNTIME]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Efficient runtime systems for parallel architectures [RUNTIME]
NAMYST, Raymond
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Efficient runtime systems for parallel architectures [RUNTIME]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Efficient runtime systems for parallel architectures [RUNTIME]
AUGONNET, Cédric
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Efficient runtime systems for parallel architectures [RUNTIME]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Efficient runtime systems for parallel architectures [RUNTIME]
NAMYST, Raymond
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Efficient runtime systems for parallel architectures [RUNTIME]
< Réduire
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Efficient runtime systems for parallel architectures [RUNTIME]
Langue
en
Communication dans un congrès
Ce document a été publié dans
2nd Workshop on Highly Parallel Processing on a Chip (HPPC 2008), 2008-08-26, Las Palmas de Gran Canaria. 2008
Résumé en anglais
Approaching the theoretical performance of heterogeneous multicore architectures, equipped with specialized accelerators, is a challenging issue. Unlike regular CPUs that can transparently access the whole global memory ...Lire la suite >
Approaching the theoretical performance of heterogeneous multicore architectures, equipped with specialized accelerators, is a challenging issue. Unlike regular CPUs that can transparently access the whole global memory address range, accelerators usually embed local memory on which they perform all their computations using a specific instruction set. While many research efforts have been devoted to offloading parts of a program over such coprocessors, the real challenge is to find a programming model providing a unified view of all available computing units. In this paper, we present an original runtime system providing a high-level, unified execution model allowing seamless execution of tasks over the underlying heterogeneous hardware. The runtime is based on a hierarchical memory management facility and on a codelet scheduler. We demonstrate the efficiency of our solution with a LU decomposition for both homogeneous (3.8 speedup on 4 cores) and heterogeneous machines (95% efficiency). We also show that a "granularity aware" scheduling can improve execution time by 35%.< Réduire
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Importé de halUnités de recherche