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Hierarchical congregated ant system for bottom-up VLSI placements

机译:自下而上的VLSI布局的分层聚集蚂蚁系统

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A new perturbation method, called Hierarchical-Congregated Ant System (H-CAS) has been proposed to perform the variable-order bottom-up placement for VLSI. H-CAS exploits the concept of ant colonies, where each ant will generate the perturbation based on differences in dimensions of the VLSI modules in hard modules floorplanning and differences in area of the VLSI modules in soft modules floor-planning. In this paper, it is mathematically proved that the area-based two-dimensional cost function for hard modules floorplanning problem can be reduced to the difference-based one dimensional cost function which avoids local optima problems. Lack of global view is a major drawback in the conventional bottom-up hierarchy, and hence, ants in the H-CAS are made to introduce global information at every level of bottom-up hierarchy. A new relative whitespace formula for bottom-up hierarchy is derived mathematically and the H-CAS embeds it in its unique update formula. The ants in H-CAS are able to communicate among themselves and update the pheromone trails when they reach the destination. Then, the ants will congregate, share their experiences and construct a new pheromone trails that belong to this newly constructed group. The congregation of at least two ants and/or ant consortiums would lead to reduction in subsequent search space and complexity. H-CAS gives the best-so-far near optimal solutions and yields low standard deviations of areas involving 9-600 blocks based on Microelectronics Center of North Carolina (MCNC) and Giga scale Systems Research Center (GSRC) benchmarks. The results obtained establish that H-CAS is a high performance placer in respect of scaling, convergence, precision, stability, and reliability. The above claims are based on the comparisons with the other floorplanning algorithms as depicted graphically.
机译:提出了一种新的摄动方法,称为层次聚集蚂蚁系统(H-CAS),以执行VLSI的自底向上的可变顺序放置。 H-CAS利用蚁群的概念,其中每个蚂蚁都会根据硬模块布局规划中VLSI模块的尺寸差异以及软模块布局规划中VLSI模块的面积差异来产生干扰。本文通过数学证明,可以将针对硬模块布局问题的基于面积的二维成本函数简化为避免局部最优问题的基于差异的一维成本函数。缺乏全局视图是传统的自下而上层次结构的主要缺点,因此,H-CAS中的蚂蚁被用来在自下而上层次结构的每个级别引入全局信息。从数学上推导了一个新的自底向上层次结构的相对空白公式,H-CAS将其嵌入其唯一的更新公式中。 H-CAS中的蚂蚁能够相互通信并在到达目的地时更新信息素路径。然后,蚂蚁会聚在一起,分享他们的经验,并构建属于这个新组的新信息素路径。至少两个蚂蚁和/或蚂蚁财团的聚集将导致随后的搜索空间和复杂性的减小。 H-CAS根据北卡罗来纳州微电子中心(MCNC)和千兆规模系统研究中心(GSRC)基准,提供了迄今为止最好的解决方案,并产生了涉及9-600个区块的较低标准偏差。获得的结果证明,H-CAS在缩放,收敛,精度,稳定性和可靠性方面是高性能的。以上权利要求基于与以图形方式描绘的其他布局规划算法的比较。

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