{"title":"基于改进粒子群算法的嵌入式系统软硬件划分","authors":"Qiaoling Tong, X. Zou, Qiao Zhang, Fei Gao, Hengqing Tong","doi":"10.1109/SEC.2008.23","DOIUrl":null,"url":null,"abstract":"Hardware/software partitioning is a key problem in hardware/software co-design. This paper presents a new hardware/software partitioning methodology based on improved particle swarm optimization algorithm. The model of the embedded system was constructed by directed acyclic graph to obtain the objective function. Then improvement strategies are introduced in order to overcome the problems of low precision and divergence in traditional particle swarm optimization algorithm. The improved algorithm can avoid local optimal solution efficiently and be conveniently implemented in the field of hardware/software partitioning.","PeriodicalId":231129,"journal":{"name":"2008 Fifth IEEE International Symposium on Embedded Computing","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"The Hardware/Software Partitioning in Embedded System by Improved Particle Swarm Optimization Algorithm\",\"authors\":\"Qiaoling Tong, X. Zou, Qiao Zhang, Fei Gao, Hengqing Tong\",\"doi\":\"10.1109/SEC.2008.23\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Hardware/software partitioning is a key problem in hardware/software co-design. This paper presents a new hardware/software partitioning methodology based on improved particle swarm optimization algorithm. The model of the embedded system was constructed by directed acyclic graph to obtain the objective function. Then improvement strategies are introduced in order to overcome the problems of low precision and divergence in traditional particle swarm optimization algorithm. The improved algorithm can avoid local optimal solution efficiently and be conveniently implemented in the field of hardware/software partitioning.\",\"PeriodicalId\":231129,\"journal\":{\"name\":\"2008 Fifth IEEE International Symposium on Embedded Computing\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-10-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 Fifth IEEE International Symposium on Embedded Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SEC.2008.23\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Fifth IEEE International Symposium on Embedded Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SEC.2008.23","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Hardware/Software Partitioning in Embedded System by Improved Particle Swarm Optimization Algorithm
Hardware/software partitioning is a key problem in hardware/software co-design. This paper presents a new hardware/software partitioning methodology based on improved particle swarm optimization algorithm. The model of the embedded system was constructed by directed acyclic graph to obtain the objective function. Then improvement strategies are introduced in order to overcome the problems of low precision and divergence in traditional particle swarm optimization algorithm. The improved algorithm can avoid local optimal solution efficiently and be conveniently implemented in the field of hardware/software partitioning.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
