{"title":"gpu加速标准和多种群文化算法","authors":"Jianqiang Dong, Bo Yuan","doi":"10.1109/ICSS.2013.39","DOIUrl":null,"url":null,"abstract":"In this paper, we present three parallel cultural algorithms using CUDA-enabled GPUs. Firstly, we used the GPU to accelerate an expensive fitness function. Next, the parallel versions of both standard and multi-population CAs were presented. Experiments show that the standard CA with an expensive fitness function was made more than 600 times faster. On lightweight benchmark problems, the speedups were only 3-4 times for the standard CA while the multi-population CA can still achieve 30-50 times speedups.","PeriodicalId":213782,"journal":{"name":"2013 International Conference on Service Sciences (ICSS)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"GPU-Accelerated Standard and Multi-population Cultural Algorithms\",\"authors\":\"Jianqiang Dong, Bo Yuan\",\"doi\":\"10.1109/ICSS.2013.39\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present three parallel cultural algorithms using CUDA-enabled GPUs. Firstly, we used the GPU to accelerate an expensive fitness function. Next, the parallel versions of both standard and multi-population CAs were presented. Experiments show that the standard CA with an expensive fitness function was made more than 600 times faster. On lightweight benchmark problems, the speedups were only 3-4 times for the standard CA while the multi-population CA can still achieve 30-50 times speedups.\",\"PeriodicalId\":213782,\"journal\":{\"name\":\"2013 International Conference on Service Sciences (ICSS)\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-04-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Service Sciences (ICSS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSS.2013.39\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Service Sciences (ICSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSS.2013.39","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
GPU-Accelerated Standard and Multi-population Cultural Algorithms
In this paper, we present three parallel cultural algorithms using CUDA-enabled GPUs. Firstly, we used the GPU to accelerate an expensive fitness function. Next, the parallel versions of both standard and multi-population CAs were presented. Experiments show that the standard CA with an expensive fitness function was made more than 600 times faster. On lightweight benchmark problems, the speedups were only 3-4 times for the standard CA while the multi-population CA can still achieve 30-50 times speedups.