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首页> 外文期刊>Journal of circuits, systems and computers >A GENETIC ALGORITHM METHODOLOGY TO FIND THE MAXIMUM DATAPATH COVERAGE FOR COMBINATIONAL LOGIC CIRCUITS
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A GENETIC ALGORITHM METHODOLOGY TO FIND THE MAXIMUM DATAPATH COVERAGE FOR COMBINATIONAL LOGIC CIRCUITS

机译:寻找组合逻辑电路最大数据路径覆盖率的遗传算法方法

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摘要

In this paper, we present a genetic algorithm (GA) based methodology for vector generation that maximizes the metric of datapath coverage for a given combinational logic circuit, and compare it with a standard greedy algorithm. The search of maximum coverage vectors is a complex optimization of a satisfiability problem. The GA deals with the optimization problem, whilst an external satisfiability solver is invoked to deal with the coverage problem. Experimental results and performance comparisons based on the large set of MCNC'91 suite of benchmark circuits are presented. They show significant speedups of the GA methodology against a greedy algorithm for large circuits.
机译:在本文中,我们提出了一种基于遗传算法(GA)的矢量生成方法,该方法可使给定组合逻辑电路的数据路径覆盖率最大化,并将其与标准贪婪算法进行比较。最大覆盖向量的搜索是可满足性问题的复杂优化。遗传算法处理最优化问题,同时调用外部可满足性求解器来处理覆盖问题。给出了基于大量MCNC'91基准电路套件的实验结果和性能比较。他们展示了GA方法相对于大型电路的贪婪算法的显着提速。

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