Efficient hierarchical clustering method for the multiple constant multiplication problem

Akihiro Matsuura, Mitsuteru Yukishita, Akira Nagoya

Research output: Contribution to conferencePaperpeer-review

3 Citations (Scopus)

Abstract

In this paper, we propose an efficient solution for the Multiple Constant Multiplication (MCM) problem. The method exploits common subexpressions among constants based on hierarchical clustering and reduce the number of shifts, additions, and subtractions. The algorithm defines appropriate weights which indicate the operation priorities and selects the common subexpressions which results in the least number of local operations. It can also be extended to various high-level synthesis tasks such as arbitrary linear transforms. Experimental results show the effectiveness of our method.

Original languageEnglish
Pages83-88
Number of pages6
Publication statusPublished - Jan 1 1997
Externally publishedYes
EventProceedings of the 1997 Asia and South Pacific Design Automation Conference, ASP-DAC - Chiba, Jpn
Duration: Jan 28 1997Jan 31 1997

Other

OtherProceedings of the 1997 Asia and South Pacific Design Automation Conference, ASP-DAC
CityChiba, Jpn
Period1/28/971/31/97

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering

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