Fast FPGA placement algorithm using Quantum Genetic Algorithm with Simulated Annealing

Xiao Guo,Teng Wang,Zhihui Chen,Lingli Wang,Wenqing Zhao

Changsha, Hunan（2009）

引用 4|浏览5

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摘要

Field-programmable gate array (FPGA) attracts more and more attentions in the digital-design field for its excellent features such as reconfiguration and fast time to market. But the implementation of FPGA is restricted by its hardware framework and the CAD software. This paper proposes quantum genetic algorithm with simulated annealing (QGASA) as a hybrid FPGA placement algorithm, which combined the advantage of the fast global search ability of QGA and local adjusting ability of simulated annealing (SA) algorithm. The experimental results are compared with the state-of-the-art placement tool versatile place and route (VPR) by running the MCNC benchmark circuits. The results show that the path-timing driven cost of QGASA is similar to VPR, but the overall CPU time is reduced by 70%.

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关键词

versatile place-and-route tool,fpga placement,cad software,fast global search ability,fast fpga placement algorithm,qgasa,hardware framework,genetic algorithms,benchmark testing,quantum genetic algorithm,cpu time,network analysis,field-programmable gate array,field programmable gate arrays,simulated annealing,congestion-avoidance,digital-design field,mcnc benchmark circuits,path-timing driven,field programmable gate array,digital design,central processing unit,genetic algorithm,solid modeling,logic gates,quantum computing

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