{"title":"内存需求平衡，因此渐近加速FFT计算在处理器阵列上","authors":"J. Shieh","doi":"10.1109/IPPS.1992.223045","DOIUrl":null,"url":null,"abstract":"The paper proves that for a linearly-connected array of alpha processors or a mesh-connected array of alpha /sup 2/ processors, where each processor has computation bandwidth C, I/O bandwidth I and C/I=logm, Omega (m/sup alpha /) memory size is required in each processor to minimize the I/O requirement in balancing the FFT computation. Then it presents balanced FFT algorithms on these arrays to meet their memory size lower bounds. These algorithms are time optimal exhibiting full speedups.<<ETX>>","PeriodicalId":340070,"journal":{"name":"Proceedings Sixth International Parallel Processing Symposium","volume":"21 5","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Memory requirements to balance thus asymptotically full-speedup FFT computation on processor arrays\",\"authors\":\"J. Shieh\",\"doi\":\"10.1109/IPPS.1992.223045\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper proves that for a linearly-connected array of alpha processors or a mesh-connected array of alpha /sup 2/ processors, where each processor has computation bandwidth C, I/O bandwidth I and C/I=logm, Omega (m/sup alpha /) memory size is required in each processor to minimize the I/O requirement in balancing the FFT computation. Then it presents balanced FFT algorithms on these arrays to meet their memory size lower bounds. These algorithms are time optimal exhibiting full speedups.<<ETX>>\",\"PeriodicalId\":340070,\"journal\":{\"name\":\"Proceedings Sixth International Parallel Processing Symposium\",\"volume\":\"21 5\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings Sixth International Parallel Processing Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IPPS.1992.223045\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Sixth International Parallel Processing Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPPS.1992.223045","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Memory requirements to balance thus asymptotically full-speedup FFT computation on processor arrays
The paper proves that for a linearly-connected array of alpha processors or a mesh-connected array of alpha /sup 2/ processors, where each processor has computation bandwidth C, I/O bandwidth I and C/I=logm, Omega (m/sup alpha /) memory size is required in each processor to minimize the I/O requirement in balancing the FFT computation. Then it presents balanced FFT algorithms on these arrays to meet their memory size lower bounds. These algorithms are time optimal exhibiting full speedups.<>
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
