...
首页> 外文期刊>International Journal of Bio-Inspired Computation >A hybrid bio-inspired optimisation approach for wirelength minimisation of hardware tasks placement in field programmable gate array devices
【24h】

A hybrid bio-inspired optimisation approach for wirelength minimisation of hardware tasks placement in field programmable gate array devices

机译:用于现场可编程门阵列设备中硬件任务的Wirelenge最小化的混合生物启发优化方法

获取原文
获取原文并翻译 | 示例
           

摘要

In computer-aided design (CAD) flow of VLSI circuits, placement process is an NP-complete problem which requires an optimisation approach to obtain the system performance better. The main objective of placement is to reduce the wire length between the tasks with zero overlap. Fast response and better convergence algorithms are required to meet these desires. In this regard, bio-inspired optimisation algorithms such as genetic algorithm (GA) and particle swarm optimisation (PSO) algorithm have been considered. By using the salient features of these two algorithms, the optimised solution for placement problem has been obtained. The concept of GA has been applied followed by genetic algorithm to obtain optimised result. For experimentation, various directed data flow graphs (DDFGs) are randomly generated and the comparison is made between the GA, PSO and hybrid (GA-PSO) methods. The hybrid approach using GA-PSO produces better experimental results in wire length minimisation and, hence outperforms than the others.
机译:在计算机辅助设计(CAD)流量的VLSI电路流中,放置过程是一个NP完整的问题,需要优化方法来更好地获得系统性能。放置的主要目的是减少具有零重叠的任务之间的线长度。快速响应和更好的收敛算法需要满足这些欲望。在这方面,已经考虑了生物启发优化算法,例如遗传算法(GA)和粒子群优化(PSO)算法。通过使用这两种算法的突出特征,已经获得了放置问题的优化解决方案。 GA的概念已被应用于遗传算法,以获得优化结果。对于实验,随机生成各种定向数据流图(DDFG),并且在GA,PSO和混合(GA-PSO)方法之间进行比较。使用GA-PSO的混合方法在线长度最小化产生更好的实验结果,因此优于其他更好的实验结果。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号