Hardware efficient base-4 systolic architecture for computing the discrete Fourier transform

A systolic architecture is described for computing the 1-D discrete Fourier transform, which provides a significant reduction in array area by reducing the number of complex multipliers compared to previous systolic approaches. This design improvement is achieved by taking advantage of a more efficient computation scheme based on symmetries in the coefficient matrix and a radix-4 butterfly. Comparisons are provided with previous systolic architectures. Systolic architecture designs were created using a CAD tool able to find optimal non-uniform array designs starting from high-level coded descriptions of the algorithm.

[1]  Hyesook Lim,et al.  Multidimensional systolic arrays for the implementation of discrete Fourier transforms , 1999, IEEE Trans. Signal Process..

[2]  Roger F. Woods,et al.  A new FFT architecture and chip design for motion compensation based on phase correlation , 1996, Proceedings of International Conference on Application Specific Systems, Architectures and Processors: ASAP '96.

[3]  Shietung Peng,et al.  Design of Array Processors for 2-D Discrete Fourier Transform (Special Issue on Parallel and Distributed Supercomputing) , 1997 .

[4]  Mats Torkelson,et al.  A new approach to pipeline FFT processor , 1996, Proceedings of International Conference on Parallel Processing.

[5]  S. Kung,et al.  VLSI Array processors , 1985, IEEE ASSP Magazine.

[6]  W. Steenaart,et al.  Efficient one-dimensional systolic array realization of the discrete Fourier transform , 1989 .

[7]  Graham A. Jullien,et al.  A VLSI array for computing the DFT based on RNS , 1986, ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[8]  J. Gregory Nash Constraint directed CAD tool for automatic latency-optimal implementation of 1-D and 2-D Fourier transforms , 2002, SPIE ITCom.

[9]  Long-Wen Chan,et al.  A new systolic array for discrete Fourier transform , 1988, IEEE Trans. Acoust. Speech Signal Process..

[10]  D J Evans,et al.  Parallel processing , 1986 .