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The Fast Fourier Transform on Hypercube Parallel Computers

TLDR
This thesis investigates several different aspects of parallel Fast Fourier Transform implementation techniques for distributed-memory message-passing systems such as hypercube multiprocessors with excellent speedup when implemented on the Intel iPSC hypercube.
Abstract
The Fast Fourier Transform appears frequently in scientific computing. Therefore it is desirable to implement it efficiently on parallel computers. In this thesis, we investigate several different aspects of parallel Fast Fourier Transform implementation techniques for distributed-memory message-passing systems such as hypercube multiprocessors. We describe various Fast Fourier Transform algorithms using a matrix notation. An error analysis is presented that considers the effect of different methods used in the computation of the Fourier Transform coefficients as well as accumulated roundoff. New implementations of one and two-dimensional Fast Fourier Transforms are presented along with comparisons with existing methods. New algorithms for symmetric transforms are also developed and the results show excellent speedup when implemented on the Intel iPSC hypercube.

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Journal ArticleDOI

Accuracy of the Discrete Fourier Transform and the Fast Fourier Transform

TL;DR: Fast Fourier transform (FFT)-based computations can be far more accurate than the slow transforms suggest, but these results depend critically on the accuracy of the FFT software employed, which should generally be considered suspect.
Journal ArticleDOI

Worst and Average Case Roundoff Error Analysis for FFT

TL;DR: This paper presents both worst case and average case analysis of roundoff errors occuring in the floating point computation of fast Fourier transform with precomputed twiddle factors and shows the strong influence of precomputation errors on the numerical stability of FFT.
Journal ArticleDOI

Improved Roundoff Error Analysis for Precomputed Twiddle Factors

TL;DR: Both worst case and average case analysis of roundoff errors occurring in eight precomputation methods of twiddle factors are presented.
Journal ArticleDOI

Componentwise error analysis for FFTs with applications to fast Helmholtz solvers

TL;DR: It is shown by means of a statistical error analysis that in realistic cases the max-norm error grows asymptotically like the logarithm of the sequence length by machine precision.