Genetic approach to minimizing energy consumption of VLSI processors using multiple supply voltages

Masanori Hariyama, Tetsuya Aoyama, Michitaka Kameyama

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

This paper presents an efficient search method for a scheduling and module selection problem using multiple supply voltages so as to minimize dynamic energy consumption under time and area constraints. The proposed algorithm is based on a genetic algorithm so that it can find near-optimal solutions in a short time for large-size problems, n efficient search can be achieved by crossover that prevents generating nonvalid individuals and a local search is also utilized in the algorithm. Experimental results for large-size problems with 1,000 operations demonstrate that the proposed method can achieve significant energy reduction up to 50 percent and can find a near-optimal solution (within 2.8 percent from the lower bound of optimal solutions) in 10 minutes. On the other hand, the ILP-based method cannot find any feasible solution in one hour for the large-size problem, even if a state-of-art mathematical programming solver is used.

Original languageEnglish
Pages (from-to)642-650
Number of pages9
JournalIEEE Transactions on Computers
Volume54
Issue number6
DOIs
Publication statusPublished - 2005 Jun

Keywords

  • Automatic synthesis
  • Data-path design
  • Module selection
  • Scheduling

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computational Theory and Mathematics

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