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2-D Wavelet Transform Enhancement on General- Purpose Microprocessors: Memory Hierarchy and SIMD Parallelism Exploitation

  • Daniel Chaver
  • Christian Tenllado
  • Luis Piñuel
  • Manuel Prieto
  • Francisco Tirado
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2552)

Abstract

This paper addresses the implementation of a 2-D Discrete Wavelet Transform on general-purpose microprocessors, focusing on both memory hierarchy and SIMD parallelization issues. Both topics are somewhat related, since SIMD extensions are only useful if the memory hierarchy is efficiently exploited. In this work, locality has been significantly improved by means of a novel approach called pipelined computation, which complements previous techniques based on loop tiling and non-linear layouts. As experimental platforms we have employed a Pentium-III (P-III) and a Pentium-4 (P-4) microprocessor. However, our SIMD-oriented tuning has been exclusively performed at source code level. Basically, we have reordered some loops and introduced some modifications that allow automatic vectorization. Taking into account the abstraction level at which the optimizations are carried out, the speedups obtained on the investigated platforms are quite satisfactory, even though further improvement can be obtained by dropping the level of abstraction (compiler intrinsics or assembly code).

Keywords

Discrete Wavelet Transform Versus Versus Versus Versus Versus Single Instruction Multiple Data Memory Hierarchy Memory Access Pattern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Daniel Chaver
    • 1
  • Christian Tenllado
    • 1
  • Luis Piñuel
    • 1
  • Manuel Prieto
    • 1
  • Francisco Tirado
    • 1
  1. 1.Departamento de Arquitectura de Computadores y Automatica,Facultad de Ciencias FisicasUniversidad ComplutenseMadridSpain

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