{"title":"基于图形加速器的粒子群优化求解一维IHCP","authors":"S. Szénási, I. Felde, I. Kovács","doi":"10.1109/SACI.2015.7208230","DOIUrl":null,"url":null,"abstract":"There are several implicit and explicit formulations to solve the Inverse Heat Conduction Problem. One of the most promising methods is the Particle Swarm Optimization; however, it needs a long time to find solutions for large scale problems (large swarm populations). This paper presents the implementation and the evaluation of a parallel approach using graphics accelerators. This GPU implementation is about three times faster than the original CPU based method.","PeriodicalId":312683,"journal":{"name":"2015 IEEE 10th Jubilee International Symposium on Applied Computational Intelligence and Informatics","volume":"121 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Solving one-dimensional IHCP with particle swarm optimization using graphics accelerators\",\"authors\":\"S. Szénási, I. Felde, I. Kovács\",\"doi\":\"10.1109/SACI.2015.7208230\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There are several implicit and explicit formulations to solve the Inverse Heat Conduction Problem. One of the most promising methods is the Particle Swarm Optimization; however, it needs a long time to find solutions for large scale problems (large swarm populations). This paper presents the implementation and the evaluation of a parallel approach using graphics accelerators. This GPU implementation is about three times faster than the original CPU based method.\",\"PeriodicalId\":312683,\"journal\":{\"name\":\"2015 IEEE 10th Jubilee International Symposium on Applied Computational Intelligence and Informatics\",\"volume\":\"121 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-08-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE 10th Jubilee International Symposium on Applied Computational Intelligence and Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SACI.2015.7208230\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 10th Jubilee International Symposium on Applied Computational Intelligence and Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SACI.2015.7208230","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Solving one-dimensional IHCP with particle swarm optimization using graphics accelerators
There are several implicit and explicit formulations to solve the Inverse Heat Conduction Problem. One of the most promising methods is the Particle Swarm Optimization; however, it needs a long time to find solutions for large scale problems (large swarm populations). This paper presents the implementation and the evaluation of a parallel approach using graphics accelerators. This GPU implementation is about three times faster than the original CPU based method.