基于元启发式算法的VLSI平面规划优化研究综述

Rajendra Bahadur Singh, A. Baghel, Ayush Agarwal
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引用次数: 13

摘要

在VLSI物理设计中,平面规划是必不可少的设计步骤,因为它决定了芯片中模块的大小、形状和位置,因此它估计了芯片的总面积、互连和延迟。在计算上,VLSI平面规划是一个NP困难问题。因此,许多研究者提出了各种启发式和元启发式算法来解决超大规模集成电路的平面设计问题。平面图的表达是平面图设计阶段的一个重要方面。平面布置图的表达方式对平面布置图设计的复杂性和搜索空间有着重要的影响。在本文中,我们研究和比较了PSO、SA和ACO作为平面规划的优化算法,以及VLSI平面规划问题中所涉及的表示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A review on VLSI floorplanning optimization using metaheuristic algorithms
In the VLSI physical design, floorplanning is an essential design step, as it determines the size, shape, and locations of modules in a chip and as such it estimates the total chip area, the interconnects, and, delay. Computationally, VLSI floorplanning is an NP hard problem. So many researchers have suggested various heuristics and metaheuristic algorithms to solve the VLSI floorplan problem. The representation of floorplan is an important aspect of the floorplanning Stage. The floorplan representations have an important impact on the complexity and search space of the floorplan design. In this paper, we included studying and comparing PSO, SA and ACO as optimization algorithms for floorplanning and the representations involved in the VLSI floorplanning problem.
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