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Improving Data Locality by Chunking

Cédric Bastoul 1 Paul Feautrier 2
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
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.
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https://hal.inria.fr/inria-00001055
Contributor : Cédric Bastoul <>
Submitted on : Tuesday, January 24, 2006 - 11:59:21 PM
Last modification on : Friday, January 10, 2020 - 3:42:17 PM
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  • HAL Id : inria-00001055, version 1

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Cédric Bastoul, Paul Feautrier. Improving Data Locality by Chunking. CC'2003 12th International Conference on Compiler Construction, Apr 2003, Warsaw/Poland. ⟨inria-00001055⟩

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