ASC-FFT: Area-Efficient Low-Latency FFT Design Based on Asynchronous Stochastic Computing

Patricia Gonzalez-Guerrero, Xinfei Guo, M. Stan
{"title":"ASC-FFT: Area-Efficient Low-Latency FFT Design Based on Asynchronous Stochastic Computing","authors":"Patricia Gonzalez-Guerrero, Xinfei Guo, M. Stan","doi":"10.1109/LASCAS.2019.8667599","DOIUrl":null,"url":null,"abstract":"Asynchronous Stochastic Computing (ASC) is a new paradigm that addresses Synchronous Stochastic Computing (SSC) drawbacks, expensive stochastic number generation (SNG) and long latency, by using continuous time streams (CTS). To go beyond the basic operations of addition and multiplication in ASC we need to incorporate a memory element. Although for SSC the natural memory element is a clocked-flip-flop, using the same approach with no synchronized data leads to unacceptable large error. In this paper, we propose to use a capacitor embedded in a feedback loop as the ASC memory element. Based on this idea, we design a low-error asynchronous adder that stores the carry information in the capacitor. Our adder enables the implementation of more complex computation logic. As an example, we implement an asynchronous stochastic Fast Fourier Transform (ASC-FFT) using a FinFET1X1 technology. The proposed adder requires 76%-24% less hardware cost compared against conventional and SSC adders respectively. Besides, the ASC-FFT shows 3X less latency when compared with SSC-FFT approaches and significant improvements in latency and area over conventional FFT architectures with no degradation of the computation accuracy measured by the FFT Signal to Noise Ratio (SNR).","PeriodicalId":142430,"journal":{"name":"2019 IEEE 10th Latin American Symposium on Circuits & Systems (LASCAS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 10th Latin American Symposium on Circuits & Systems (LASCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LASCAS.2019.8667599","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

Asynchronous Stochastic Computing (ASC) is a new paradigm that addresses Synchronous Stochastic Computing (SSC) drawbacks, expensive stochastic number generation (SNG) and long latency, by using continuous time streams (CTS). To go beyond the basic operations of addition and multiplication in ASC we need to incorporate a memory element. Although for SSC the natural memory element is a clocked-flip-flop, using the same approach with no synchronized data leads to unacceptable large error. In this paper, we propose to use a capacitor embedded in a feedback loop as the ASC memory element. Based on this idea, we design a low-error asynchronous adder that stores the carry information in the capacitor. Our adder enables the implementation of more complex computation logic. As an example, we implement an asynchronous stochastic Fast Fourier Transform (ASC-FFT) using a FinFET1X1 technology. The proposed adder requires 76%-24% less hardware cost compared against conventional and SSC adders respectively. Besides, the ASC-FFT shows 3X less latency when compared with SSC-FFT approaches and significant improvements in latency and area over conventional FFT architectures with no degradation of the computation accuracy measured by the FFT Signal to Noise Ratio (SNR).
ASC-FFT:基于异步随机计算的区域高效低延迟FFT设计
异步随机计算(ASC)是一种新的范式,通过使用连续时间流(CTS)来解决同步随机计算(SSC)的缺点,即昂贵的随机数生成(SNG)和长延迟。为了在ASC中超越加法和乘法的基本操作,我们需要加入一个存储元素。虽然对于SSC来说,自然内存元素是一个带时钟的触发器,但使用没有同步数据的相同方法会导致不可接受的大错误。在本文中,我们建议使用嵌入在反馈回路中的电容器作为ASC存储元件。在此基础上,设计了一种将进位信息存储在电容中的低误差异步加法器。我们的加法器可以实现更复杂的计算逻辑。作为一个例子,我们使用FinFET1X1技术实现了异步随机快速傅里叶变换(ASC-FFT)。与传统加法器和SSC加法器相比,该加法器的硬件成本分别降低了76%-24%。此外,与SSC-FFT方法相比,ASC-FFT的延迟减少了3倍,并且在延迟和面积上比传统FFT架构有了显著改善,并且FFT信噪比(SNR)测量的计算精度没有下降。
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