机构地区: 山东大学计算机科学与技术学院
出 处: 《计算机工程与应用》 2009年第18期70-71,114,共3页
摘 要: FPGA布局在自动化设计中起到了十分关键的作用。将粒子群蚁群混合算法应用于FPGA布局问题,针对MCNC基准电路进行布局实验,并与模拟退火算法(SA),模拟退火与遗传混合算法(GASA)及蚁群算法(ACO)等进行了对比。结果表明该布局方法具有较好的性能。 Placement is a key issue in FPGA CAD flow.A mixed ant colony and particle swarm algorithm is used for the placement of FPGA.This method is utilized to place a set of Microelectronics Center of North Carolina(MCNC) benchmark circuits, and this paper presents a comparison with Simulated Annealing algorithm(SA),mixed Genetic and Simulated Annealing algorithm (GASA) and Ant Colony algorithm (ACO).The experimental results show that the placement method can achieve performance in terms of placement cost and routing channel density.
关 键 词: 现场可编程门阵列布局 粒子群 蚁群
领 域: [自动化与计算机技术] [自动化与计算机技术]