摘要
针对嵌入式系统中的单MPU和单ASIC体系结构问题,提出一种改进粒子群算法,将该算法应用到数字音视频解码器的软/硬件划分中,一次运行可以获得较多Pareto最优解。讨论目标函数、系统约束、粒子比较准则、拥挤距离函数、变异算子和粒子适应度等问题的处理。实验结果表明,该算法改善了传统算法产生未成熟收敛、较少Pareto最优解和Pareto最优解前端分布不均匀的问题,增强算法的自适应性及结果的全局最优性。
Aiming at the configuration problems of single MPU and ASIC in embedded system,this paper proposes an improved Particle Swarm Optimization(PSO) which is applied to HardWare/SoftWare(HW/SW) partitioning of digital audio/video decoder,each run of the algorithm can produce many Pareto-optional solutions,and the problems of target function,system constraint,Particle comparison criterion,congestion distance function,mutate operator and particle Fitness are discussed.Experimental result shows that the algorithm improves immature convergence,less Pareto-optimal solutions and Front-end distributed heterogeneous of Pareto-optimal solutions of traditional algorithm,strengthens adaptability and global optimality of results
出处
《计算机工程》
CAS
CSCD
北大核心
2011年第13期254-256,271,共4页
Computer Engineering
基金
国家自然科学基金资助项目(60863006)
教育部科学技术研究基金资助重点项目(107106)
关键词
嵌入式系统
软/硬件划分
软硬件协同设计
粒子群优化算法
PARETO最优解
embedded system
HardWare/SoftWare(HW/SW) partition
HW/SW co-design
Particle Swarm Optimization(PSO) algorithm
Pareto-optimal solutions