Implementation of a parallel genetic algorithm for floorplan optimization on IBM SP2

  • Authors:
  • Han Yang Foo;Jianjian Song;Wenjun Zhuang;H. Esbensen;E. S. Kuh

  • Affiliations:
  • -;-;-;-;-

  • Venue:
  • HPC-ASIA '97 Proceedings of the High-Performance Computing on the Information Superhighway, HPC-Asia '97
  • Year:
  • 1997

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Abstract

A Multi-Selection-Multi-Evolution (MSME) scheme for parallelizing a genetic algorithm for floorplan optimization is presented and its implementation with MPI and its experimental results are discussed. Our experimental results on a 16 node IBM SP2 scaleable parallel computer have shown that the scheme is effective in improving performance of floorplanning over that of a sequential implementation. The parallel version could obtain better results with more than 90% of probability. Given 1000 second wall clock time, our parallel program could reduce both chip area and maximum path delay by more than 8% with 8 processors and 12% with 12 processors. Parallel computing can also speed up the evolution process so that there could be higher probability of obtaining a better solution within a given time interval.