Improving Data Locality by ChunkingReportar como inadecuado




Improving Data Locality by Chunking - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

1 SMIS - Secured and Mobile Information Systems PRISM - Parallélisme, Réseaux, Systèmes, Modélisation, UVSQ - Université de Versailles Saint-Quentin-en-Yvelines, Inria Paris-Rocquencourt, CNRS - Centre National de la Recherche Scientifique : UMR8144 2 LIP - Laboratoire de l-Informatique du Parallélisme

Abstract : Cache memories were invented to decouple fast processors from slow memories. However, this decoupling is only partial, and many researchers have attempted to improve cache use by program optimization. Potential benefits are significant since both energy dissipation and performance highly depend on the traffic between memory levels. But modeling the traffic is difficult; this observation has led to the use of heuristic methods for steering program transformations. In this paper, we propose another approach: we simplify the cache model and we organize the target program in such a way that an asymptotic evaluation of the memory traffic is possible. This information is used by our optimization algorithm in order to find the best reordering of the program operations, at least in an asymptotic sense. Our method optimizes both temporal and spatial locality. It can be applied to any static control program with arbitrary dependences. The optimizer has been partially implemented and applied to non-trivial programs. We present experimental evidence that the amount of cache misses is drastically reduced with corresponding performance improvements.

Keywords : data locality cache memory program transformations compilation cache miss





Autor: Cédric Bastoul - Paul Feautrier -

Fuente: https://hal.archives-ouvertes.fr/



DESCARGAR PDF




Documentos relacionados