{"title":"三维FFT在分布式存储MIMD系统上的加速和效率","authors":"D. Marinescu","doi":"10.1109/FMPC.1992.234894","DOIUrl":null,"url":null,"abstract":"The author analyzes a 3-D FFT (fast Fourier transform) algorithm for a distributed memory MIMD (multiple-instruction multiple-data) system. It is shown that the communication complexity limits the efficiency even under ideal conditions. The efficiency for the optimal speedup is eta /sub opt/=0.5. Actual applications which experience load imbalance, duplication of work, and blocking are even less efficient. Therefore the speedup with P processing elements, S(P)= eta *P, is disappointingly low. Moreover, the 3-D FFT algorithm is not susceptible to massive parallelization, and the optimal number of PEs is rather low even for large problem size and fast communication. A strategy to reduce the communication complexity is presented.<<ETX>>","PeriodicalId":117789,"journal":{"name":"[Proceedings 1992] The Fourth Symposium on the Frontiers of Massively Parallel Computation","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The speedup and efficiency of 3-D FFT on distributed memory MIMD systems\",\"authors\":\"D. Marinescu\",\"doi\":\"10.1109/FMPC.1992.234894\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The author analyzes a 3-D FFT (fast Fourier transform) algorithm for a distributed memory MIMD (multiple-instruction multiple-data) system. It is shown that the communication complexity limits the efficiency even under ideal conditions. The efficiency for the optimal speedup is eta /sub opt/=0.5. Actual applications which experience load imbalance, duplication of work, and blocking are even less efficient. Therefore the speedup with P processing elements, S(P)= eta *P, is disappointingly low. Moreover, the 3-D FFT algorithm is not susceptible to massive parallelization, and the optimal number of PEs is rather low even for large problem size and fast communication. A strategy to reduce the communication complexity is presented.<<ETX>>\",\"PeriodicalId\":117789,\"journal\":{\"name\":\"[Proceedings 1992] The Fourth Symposium on the Frontiers of Massively Parallel Computation\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-10-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[Proceedings 1992] The Fourth Symposium on the Frontiers of Massively Parallel Computation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FMPC.1992.234894\",\"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 1992] The Fourth Symposium on the Frontiers of Massively Parallel Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FMPC.1992.234894","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
分析了一种适用于分布式存储多指令多数据系统的三维快速傅里叶变换算法。结果表明,即使在理想条件下,通信复杂性也会限制效率。最佳加速效率为eta /sub opt/=0.5。遇到负载不平衡、重复工作和阻塞的实际应用程序甚至效率更低。因此,P个处理元素的加速,S(P)= eta *P,低得令人失望。此外,三维FFT算法不容易受到大规模并行化的影响,即使在大问题规模和快速通信的情况下,pe的最优数量也很低。提出了一种降低通信复杂度的策略。
The speedup and efficiency of 3-D FFT on distributed memory MIMD systems
The author analyzes a 3-D FFT (fast Fourier transform) algorithm for a distributed memory MIMD (multiple-instruction multiple-data) system. It is shown that the communication complexity limits the efficiency even under ideal conditions. The efficiency for the optimal speedup is eta /sub opt/=0.5. Actual applications which experience load imbalance, duplication of work, and blocking are even less efficient. Therefore the speedup with P processing elements, S(P)= eta *P, is disappointingly low. Moreover, the 3-D FFT algorithm is not susceptible to massive parallelization, and the optimal number of PEs is rather low even for large problem size and fast communication. A strategy to reduce the communication complexity is presented.<>