Research Output

FPGA placement using genetic algorithm with simulated annealing.

  A mixed Genetic Algorithm and Simulated Annealing (GASA) algorithm is used for the placement of symmetrical FPGA. The prpoposed algortithm includes 2 stage processes. In the first stage process it optimizes placement solutions globally using GA. In the second stage process it locally improves solution. GASA overcomes the slow convergence in the later phases of processing by a genetic algorithm. The results show that GASA consumes less CPU time than GA and could achieve performances as good as versatile placement and routing tools in terms of placement cost.

Citation

Yang, M., Almaini, A. E. A., Wang, L. Y. & Wang, P. (2005). FPGA placement using genetic algorithm with simulated annealing. doi:10.1109/ICASIC.2005.1611450

Authors

Keywords

Genetic algorithms; Deveopments; Simulated annealing; Computer programming; CPU time; Routing tools; Placement costs;

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