{"title":"CuParcone一种高性能可进化神经网络模型","authors":"Xiaoxi Chen, Lin Gao, H. de Garis","doi":"10.1109/ICICTA.2010.479","DOIUrl":null,"url":null,"abstract":"An algorithm for evolving recurrent neural network via the genetic algorithm was implemented on the CUDA, resulting in a system called CuParcone (CUDA based Partially Connected Neural Evolutionary). Run on a Nvidia Tesla “GPU supercomputer, ” CuParcone achieves a performance increase of 323 times in face gender recognition compared to the comparable Parcone algorithm on a state-of-the-art, commodity single-processor server. The accuracy on this task does not decrease in moving from Parcone to CuParcone, and is comparable to the published results of other algorithms.","PeriodicalId":418904,"journal":{"name":"2010 International Conference on Intelligent Computation Technology and Automation","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"CuParcone A High-Performance Evolvable Neural Network Model\",\"authors\":\"Xiaoxi Chen, Lin Gao, H. de Garis\",\"doi\":\"10.1109/ICICTA.2010.479\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An algorithm for evolving recurrent neural network via the genetic algorithm was implemented on the CUDA, resulting in a system called CuParcone (CUDA based Partially Connected Neural Evolutionary). Run on a Nvidia Tesla “GPU supercomputer, ” CuParcone achieves a performance increase of 323 times in face gender recognition compared to the comparable Parcone algorithm on a state-of-the-art, commodity single-processor server. The accuracy on this task does not decrease in moving from Parcone to CuParcone, and is comparable to the published results of other algorithms.\",\"PeriodicalId\":418904,\"journal\":{\"name\":\"2010 International Conference on Intelligent Computation Technology and Automation\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-05-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Intelligent Computation Technology and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICTA.2010.479\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Intelligent Computation Technology and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICTA.2010.479","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
CuParcone A High-Performance Evolvable Neural Network Model
An algorithm for evolving recurrent neural network via the genetic algorithm was implemented on the CUDA, resulting in a system called CuParcone (CUDA based Partially Connected Neural Evolutionary). Run on a Nvidia Tesla “GPU supercomputer, ” CuParcone achieves a performance increase of 323 times in face gender recognition compared to the comparable Parcone algorithm on a state-of-the-art, commodity single-processor server. The accuracy on this task does not decrease in moving from Parcone to CuParcone, and is comparable to the published results of other algorithms.