Performance Comparison of PSO and Its New Variants in the Context of VLSI Global Routing

Subhrapratim Nath, J. Sing, S. Sarkar
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引用次数: 8

Abstract

Substantial reduction of gate delay occurred in recent times owing to radical decrement of transistor size. The interconnect length and delay are accordingly increased owing to the exponential escalation of packaging density with additional transistors being fabri- cated on the same chip area. The function of VLSI routing that seems to be more defying to the scholars, is categorized in global routing and detailed routing phase. In global routing phase, the prevalent method to lessen the wire length for reducing interconnect delay is to adjust the cost of the Steiner tree, devised by the terminal nodes to be interconnected. Nevertheless, Steiner tree problem is a NP-complete problem in classical graph theory where meta-heuristics might impart beneficial elucidations. Particle swarm optimization (PSO) is a robust algorithm concerning VLSI routing field. This chapter is regarding the proposal of a self-adaptive mechanism for monitoring acceler- ation coefficient of PSO and evaluating its functionalities with the existing acceleration coefficient controlled PSO in numerous allocation topologies of terminal nodes within definite VLSI layout. The outcomes of PSO variant with constriction factor in context to VLSI route reduction ability and robustness are also inspected. Additionally, a new effort in adapting the PSO with embracement of genetic algorithm is established.
VLSI全局路由环境下PSO及其新变体的性能比较
由于晶体管尺寸的急剧减小,栅极延迟在最近发生了实质性的减少。由于封装密度呈指数级增长,在相同的芯片面积上制造了额外的晶体管,因此互连长度和延迟相应增加。VLSI路由功能分为全局路由和详细路由两个阶段,这一功能在学者看来是比较难以理解的。在全局路由阶段,为减少互连延迟而减少导线长度的常用方法是调整由待互连终端节点设计的斯坦纳树的代价。然而,斯坦纳树问题是经典图论中的np完全问题,元启发式可能会给予有益的解释。粒子群优化算法(PSO)是一种鲁棒的超大规模集成电路路由优化算法。本章提出了一种自适应机制来监测PSO的加速度系数,并利用现有的加速度系数控制的PSO在确定的VLSI布局内的众多终端节点分配拓扑中评估其功能。本文还考察了带有收缩因子的PSO变体对VLSI路由缩减能力和鲁棒性的影响。在此基础上,提出了一种融合遗传算法的粒子群算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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