Techniques for power reduction in an SIMD implementation of the VQ/SOM algorithms

David C Hendry, Roberta Cambio

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Hardware implementations of the VQ (vector quantization) and SOM (self organizing map) permit the deployment of these computationally intensive algorithms as single chips or IP cores. This paper discusses the design of an IP core based on an SIMD (single instruction multiple data) processor array
for such an implementation with emphasis on those aspects of the design which lead to a low power implementation. Power reduction techniques described are: local memory sharing between processors; processor instruction set and data path organization; implementation of the winner take all calculation;
and use of a thresholding algorithm to permit power down of processors during the distance calculation. It is shown that with a typical 0:13 um low power semiconductor process and with a clock speed of 100MHz the power dissipation per processor is approximately 1mW without use of thresholding. Including thresholding reduces this power to less than 0.5mW per processor. Area for a
256 processor array with 256 8-bit vector elements per processor is 3.5mm 2.5 mm.
Original languageEnglish
Pages (from-to)291-300
Number of pages10
JournalNeurocomputing
Volume74
Issue number1-3
Early online date27 Mar 2010
DOIs
Publication statusPublished - Dec 2010

Keywords

  • vector quantization
  • self organising map
  • VLSi
  • SIMD
  • low power
  • system on chip

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