Performance-driven MCM partitioning through an adaptive genetic algorithm

S. Raman, L. Patnaik
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引用次数: 15

Abstract

We present a novel genetic algorithm-based partitioning scheme for Multi-Chip Modules (MCMs) which integrates four performance constraints simultaneously: pin count, area, heat dissipation and timing. Experimental studies demonstrate the superiority of this method over deterministic Fiduccia Mattheyes (FM) algorithm and simulated annealing (SA) technique. The algorithm performs better than another such algorithm recently reported. The adaptive change of crossover and mutation probabilities results in better convergence.
性能驱动的MCM分区通过自适应遗传算法
我们提出了一种新的基于遗传算法的多芯片模块(mcm)分区方案,该方案同时集成了四种性能约束:引脚数、面积、散热和时序。实验研究表明,该方法优于确定性模糊模糊(FM)算法和模拟退火(SA)技术。该算法比最近报道的另一种算法性能更好。交叉和突变概率的自适应变化使算法具有较好的收敛性。
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