CIRCUIT-LEVEL EVOLUTIONARY PARTITIONING ALGORITHMS
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This book presents novel circuit-level evolutionary partitioning algorithms to optimize VLSI physical design automation. It addresses limitations in traditional partitioning methods by introducing enhanced techniques such as Modified Genetic Algorithm (MGA), Modified Particle Swarm Optimization (MPSO), and a new Graph Cellular Automata (GCA) approach. These algorithms aim to minimize cut size, reduce interconnection delays, and improve overall circuit performance. Experimental validation using ISCAS'85 benchmark circuits confirms the efficiency and superiority of the proposed methods in terms ...
This book presents novel circuit-level evolutionary partitioning algorithms to optimize VLSI physical design automation. It addresses limitations in traditional partitioning methods by introducing enhanced techniques such as Modified Genetic Algorithm (MGA), Modified Particle Swarm Optimization (MPSO), and a new Graph Cellular Automata (GCA) approach. These algorithms aim to minimize cut size, reduce interconnection delays, and improve overall circuit performance. Experimental validation using ISCAS'85 benchmark circuits confirms the efficiency and superiority of the proposed methods in terms of partition quality and computational time.
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