L. Vokorokos, Miroslav Hartinger, N. Ádám, E. Chovancová, J. Radusovsky
{"title":"使用CUDA提高顺序算法程序的执行效率","authors":"L. Vokorokos, Miroslav Hartinger, N. Ádám, E. Chovancová, J. Radusovsky","doi":"10.1109/SAMI.2014.6822422","DOIUrl":null,"url":null,"abstract":"The ambition to achieve higher computing performance, is based on using all the advantages of parallel approach. The devices, software development kits and other technologies are leaping forward. Nowadays, they allow programmer to use more effective and optimized template libraries. They empower him to acces functions of graphics processing unit through the highlevel language. This paper details the experience of using such optimization on basic and more complex algorithms and the measurement of overall effectiveness increase. Our experimental results demonstrate the overall acceleration on various types of GPU.","PeriodicalId":441172,"journal":{"name":"2014 IEEE 12th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Increasing efficiency of the sequential algorithms programs execution using CUDA\",\"authors\":\"L. Vokorokos, Miroslav Hartinger, N. Ádám, E. Chovancová, J. Radusovsky\",\"doi\":\"10.1109/SAMI.2014.6822422\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The ambition to achieve higher computing performance, is based on using all the advantages of parallel approach. The devices, software development kits and other technologies are leaping forward. Nowadays, they allow programmer to use more effective and optimized template libraries. They empower him to acces functions of graphics processing unit through the highlevel language. This paper details the experience of using such optimization on basic and more complex algorithms and the measurement of overall effectiveness increase. Our experimental results demonstrate the overall acceleration on various types of GPU.\",\"PeriodicalId\":441172,\"journal\":{\"name\":\"2014 IEEE 12th International Symposium on Applied Machine Intelligence and Informatics (SAMI)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE 12th International Symposium on Applied Machine Intelligence and Informatics (SAMI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAMI.2014.6822422\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 12th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAMI.2014.6822422","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Increasing efficiency of the sequential algorithms programs execution using CUDA
The ambition to achieve higher computing performance, is based on using all the advantages of parallel approach. The devices, software development kits and other technologies are leaping forward. Nowadays, they allow programmer to use more effective and optimized template libraries. They empower him to acces functions of graphics processing unit through the highlevel language. This paper details the experience of using such optimization on basic and more complex algorithms and the measurement of overall effectiveness increase. Our experimental results demonstrate the overall acceleration on various types of GPU.