Optimal VLSI networks for multidimensional transforms

This paper presents a new class of AT/sup 2/-optimal networks for computing the multidimensional discrete Fourier transform. Although optimal networks have been proposed previously, the networks proposed in this paper are based on a new methodology for mapping large K-shuffle networks, K/spl ges/2,...

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Bibliographic Details
Published in:IEEE transactions on parallel and distributed systems 1994-07, Vol.5 (7), p.763-769
Main Author: Alnuweiri, H.M.
Format: Article
Language:English
Subjects:
Applied sciences
Computer architecture
Computer networks
Computer science
control theory
systems
Concurrent computing
Discrete Fourier transforms
Discrete transforms
Electronics
Exact sciences and technology
Fourier transforms
Integrated circuits
Multidimensional systems
Parallel processing
Pins
Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices
Software
Software engineering
Very large scale integration
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Summary:This paper presents a new class of AT/sup 2/-optimal networks for computing the multidimensional discrete Fourier transform. Although optimal networks have been proposed previously, the networks proposed in this paper are based on a new methodology for mapping large K-shuffle networks, K/spl ges/2, onto smaller area networks that maintain the optimality of the DFT network. Such networks are used to perform the index-rotation operations needed by the multidimensional computation. The resulting networks have simple regular layouts, and can be easily partitioned among several chips in order to reduce the number of input-output pins per chip.< >
ISSN:1045-9219
1558-2183
DOI:10.1109/71.296321