{"title":"多核cpu上FFT并行算法的优化","authors":"Fang Aidong","doi":"10.5013/ijssst.a.17.33.23","DOIUrl":null,"url":null,"abstract":"Fast Fourier Transformation is widely applied in fields of digital signal processing and communication.Multi-core CPU is increasingly common,and based on the parallelism of FFT algorithm,butterfly algorithm can be flexibly decomposited;we can improve the computational efficiency of FFT via investigating the allocation of parallel blocks and nested relations to optimize the algorithm,and reasonably allocating threads to realize parallel computing of multi-core CPU.","PeriodicalId":15302,"journal":{"name":"Journal of Changsha University of Electric Power","volume":"36 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimization of FFT Parallel Algorithm on Multi-Core CPUs\",\"authors\":\"Fang Aidong\",\"doi\":\"10.5013/ijssst.a.17.33.23\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fast Fourier Transformation is widely applied in fields of digital signal processing and communication.Multi-core CPU is increasingly common,and based on the parallelism of FFT algorithm,butterfly algorithm can be flexibly decomposited;we can improve the computational efficiency of FFT via investigating the allocation of parallel blocks and nested relations to optimize the algorithm,and reasonably allocating threads to realize parallel computing of multi-core CPU.\",\"PeriodicalId\":15302,\"journal\":{\"name\":\"Journal of Changsha University of Electric Power\",\"volume\":\"36 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Changsha University of Electric Power\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5013/ijssst.a.17.33.23\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Changsha University of Electric Power","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5013/ijssst.a.17.33.23","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimization of FFT Parallel Algorithm on Multi-Core CPUs
Fast Fourier Transformation is widely applied in fields of digital signal processing and communication.Multi-core CPU is increasingly common,and based on the parallelism of FFT algorithm,butterfly algorithm can be flexibly decomposited;we can improve the computational efficiency of FFT via investigating the allocation of parallel blocks and nested relations to optimize the algorithm,and reasonably allocating threads to realize parallel computing of multi-core CPU.
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