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Optimization of Thermal Aware VLSI Non-Slicing Floorplanning Using Hybrid Particle Swarm Optimization Algorithm-Harmony Search Algorithm

机译:混合粒子群算法-和声搜索算法优化热感知VLSI非切片布局

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Floorplanning is a prominent area in the Very Large-Scale Integrated (VLSI) circuit design automation, because it influences the performance, size, yield and reliability of the VLSI chips. It is the process of estimating the positions and shapes of the modules. A high packing density, small feature size and high clock frequency make the Integrated Circuit (IC) to dissipate large amount of heat. So, in this paper, a methodology is presented to distribute the temperature of the module on the layout while simultaneously optimizing the total area and wirelength by using a hybrid Particle Swarm Optimization-Harmony Search (HPSOHS) algorithm. This hybrid algorithm employs diversification technique (PSO) to obtain global optima and intensification strategy (HS) to achieve the best solution at the local level and Modified Corner List algorithm (MCL) for floorplan representation. A thermal modelling tool called hotspot tool is integrated with the proposed algorithm to obtain the temperature at the block level. The proposed algorithm is illustrated using Microelectronics Centre of North Carolina (MCNC) benchmark circuits. The results obtained are compared with the solutions derived from other stochastic algorithms and the proposed algorithm provides better solution.
机译:布局规划是超大规模集成(VLSI)电路设计自动化中的一个突出领域,因为它会影响VLSI芯片的性能,尺寸,良率和可靠性。这是估计模块位置和形状的过程。高封装密度,小特征尺寸和高时钟频率使集成电路(IC)能够散发大量热量。因此,在本文中,提出了一种使用混合粒子群优化-和谐搜索(HPSOHS)算法同时在布局上分布模块温度,同时优化总面积和线长的方法。该混合算法采用多样化技术(PSO)来获得全局最优和强化策略(HS),以在局部级别获得最佳解决方案,而改进的角落列表算法(MCL)用于平面布置图表示。将一种称为热点工具的热建模工具与所提出的算法集成在一起,以获取块级的温度。使用北卡罗来纳州微电子中心(MCNC)基准电路对提出的算法进行了说明。将获得的结果与其他随机算法得出的解进行比较,所提出的算法提供了更好的解。

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