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A GRASP Algorithm for Multi-objective Circuit Partitioning

A GRASP Algorithm for Multi-objective Circuit Partitioning
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摘要 Circuit partitioning plays a crucial role in very large-scale integrated circuit (VLSI) physical design automation. With current trends, partitioning with multiple objectives which includes cutsize, area, delay, and power obtains much concentration. In this paper, a multi-objective greedy randomized adaptive search procedure (GRASP) is presented for simultaneous cutsize and circuit delay minimization. Each objective is assigned a preference or weight to direct the search procedure and generate a variety of efficient solutions by changing the preference. To get a good initial partition with minimal cutsize and circuit delay, the gain of each module in a circuit is computed by considering both signal nets and circuit delay. The performance of the proposed algorithm is evaluated on a standard set of partitioning benchmark. The experimental results show that the proposed algorithm can generate a set of Pareto optimal solutions and is efficient for tackling multi-objective circuit partitioning. Circuit partitioning plays a crucial role in very large-scale integrated circuit (VLSI) physical design automation. With current trends, partitioning with multiple objectives which includes cutsize, area, delay, and power obtains much concentration. In this paper, a multi.objective greedy randomized adaptive search procedure (GRASP) is presented for simultaneous cutsize and circuit delay minimization. Each objective is assigned a preference or weight to direct the search procedure and generate a variety of efficient solutions by changing the preference. To get a good initial partition with minimal cutsize and circuit delay, the gain of each module in a circuit is computed by considering both signal nets and circuit delay. The performance of the proposed algorithm is evaluated on a standard set of partitioning benchmark. The experimental results show that the proposed algorithm can generate a set of Pareto optimal solutions and is efficient for tackling multi-objective circuit partitioning.
出处 《Journal of Donghua University(English Edition)》 EI CAS 2012年第1期1-4,共4页 东华大学学报(英文版)
基金 National Natural Science Foudation of China (No. 61070020 ) Research Foundation for Doctoral Program of Ministry of Education,China (No. 20093514110004) Foundations of Education Department of Fujian Province,China (No. JA10284,No. JB07283)
关键词 circuit partitioning multi-objective optimization greedy randomized adaptive search procedure (GRASP) circuit partitioning multi-objective optimization greedy randomized adaptive search procedure (GRASP)
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