Multi-FFT Vectorization for the Cell Multicore Processor

J. Barhen, T. Humble, P. Mitra, M. Traweek
{"title":"Multi-FFT Vectorization for the Cell Multicore Processor","authors":"J. Barhen, T. Humble, P. Mitra, M. Traweek","doi":"10.1109/CCGRID.2010.78","DOIUrl":null,"url":null,"abstract":"The emergence of streaming multicore processors with multi-SIMD architectures and ultra-low power operation combined with real-time compute and I/O reconfigurability opens unprecedented opportunities for executing sophisticated signal processing algorithms faster and within a much lower energy budget. Here, we present an unconventional FFT implementation scheme for the IBM Cell, named transverse vectorization. It is shown to outperform (both in terms of timing or GFLOP throughput) the fastest FFT results reported to date in the open literature.","PeriodicalId":444485,"journal":{"name":"2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCGRID.2010.78","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

The emergence of streaming multicore processors with multi-SIMD architectures and ultra-low power operation combined with real-time compute and I/O reconfigurability opens unprecedented opportunities for executing sophisticated signal processing algorithms faster and within a much lower energy budget. Here, we present an unconventional FFT implementation scheme for the IBM Cell, named transverse vectorization. It is shown to outperform (both in terms of timing or GFLOP throughput) the fastest FFT results reported to date in the open literature.
Cell多核处理器的多fft矢量化
具有多simd架构和超低功耗操作的流多核处理器的出现,结合了实时计算和I/O可重构性,为在更低的能源预算下更快地执行复杂的信号处理算法提供了前所未有的机会。在这里,我们为IBM Cell提出了一种非常规的FFT实现方案,称为横向矢量化。它被证明优于(在时序或GFLOP吞吐量方面)迄今为止在公开文献中报道的最快FFT结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信