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Meta-heuristics for circuit partitioning in parallel test generation

  • C. Gil
  • J. Ortega
  • A. F. Diaz
  • M. G. Montoya
Workshop on Biologically Inspired Solutions to Parallel Processing Problems Albert V. Zomaya, The University of Western Australia Fikret Ercal, University of Missouri-Rolla Stephan Olariu, Old Dominion University
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1388)

Abstract

In this communication Simulated Annealing and Genetic Algorithms, are applied to the graph partitioning problem. These techniques mimic processes in statistical mechanics and biology, respectively, and are the most popular meta-heuristics or general-purpose optimization strategies. A hybrid algorithm for circuit partitioning, which uses tabu search to improve the simulated annealing meta-heuristics, is also proposed and compared with pure tabu search and simulated annealing algorithms, and also with a genetic algorithm. The solutions obtained are compared and evaluated by including the hybrid partitioning algorithm in a parallel test generator which is used to determine the test patterns for the circuits of the frequently used ISCAS benchmark set.

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References

  1. [1]
    Alpert, C.J., and Kahng, A., “Recent Developments in Netlist Partitioning: A survey”. Integration: the VLSIJournal, 19/ 1-2 (1995) 1–81. *** DIRECT SUPPORT *** A0008D07 00011CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • C. Gil
    • 1
  • J. Ortega
    • 2
  • A. F. Diaz
    • 2
  • M. G. Montoya
    • 1
  1. 1.Dept. de Arquitectura de Computadores y ElectrónicaUniv. AlmeriaAlmeriaSpain
  2. 2.Dept. de Arquitectura y Tecnologfa de ComputadoresUniv. GranadaGranadaSpain

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