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Adaptive Computation of Self Sorting In-Place FFTs on Hierarchical Memory Architectures

  • Ayaz Ali
  • Lennart Johnsson
  • Jaspal Subhlok
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4782)

Abstract

Computing ”in-place and in-order” FFT poses a very difficult problem on hierarchical memory architectures where data movement can seriously degrade the performance. In this paper we present recursive formulation of a self sorting in-place FFT algorithm that adapts to the target architecture. For transform sizes where an in-place, in-order execution is not possible, we show how schedules can be constructed that use minimum work-space to perform the computation efficiently. In order to express and construct FFT schedules, we present a context free grammar that generates the FFT Schedule Specification Language. We conclude by comparing the performance of our in-place in-order FFT implementation with that of other well known FFT libraries. We also present a performance comparison between the out-of-place and in-place execution of various FFT sizes.

Keywords

Fast Fourier Transform Fast Fourier Transform Algorithm Adaptive Computation Installation Time Middle Rank 
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 2007

Authors and Affiliations

  • Ayaz Ali
    • 1
  • Lennart Johnsson
    • 1
  • Jaspal Subhlok
    • 1
  1. 1.Department of Computer Science, University of Houston, Houston,TX 77204 

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