线性斯坦纳树优化的GPSO混合算法

Subhrapratim Nath, Sagnik Gupta, S. Biswas, Rupam Banerjee, J. Sing, Subir Kumar Sarkar
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引用次数: 4

摘要

布线是VLSI电路物理层设计中最重要的阶段之一。VLSI技术的快速发展使得优化电路的导线长度(即优化布线计划)成为必要。地板规划和放置策略对超大规模集成电路的路由规划有重要影响,这反过来又要求路由成本优化。随着端点数量的增加,这个问题变得复杂,成为np完全问题。在此背景下,本文提出了一种混合元启发式优化算法——梯度-粒子群算法(GPSO),该算法将梯度下降算法和粒子群算法相结合,用于线性斯坦纳最小树(RSMT)的优化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GPSO Hybrid Algorithm for Rectilinear Steiner Tree Optimization
Routing is one of the most important stages in the physical layer design of VLSI circuits. The rapid advancement in VLSI technology has necessitated a greater need to optimize the wire length of the circuits i.e. optimize the routing plan. The floor planning and placement strategies manifest a significant effect on the routing plan of a VLSI circuit which in turn requires routing cost optimization. This problem becomes complex when the number of terminal points increases which turns it into an NP-complete problem. In this context, this paper proposes a hybrid metaheuristic optimization algorithm, the Gradient-PSO (GPSO), which hybridizes Gradient Descent and Particle Swarm Optimization for optimization of Rectilinear Steiner Minimal Tree (RSMT).
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