{"title":"An exponential function accelerator with radix-16 algorithm for spiking neural networks","authors":"Chenxiao Lin, Qingyang Zeng, D. Shang","doi":"10.1587/elex.19.20220393","DOIUrl":null,"url":null,"abstract":"A range reduction method for shift-and-add algorithms for exponential functions is proposed in this paper. An exponential function accelerator with this method and radix-16 shift-and-add algorithm has been implemented in SMIC 55 nm CMOS process. Compared with the existing method, the proposed method reduces the latency (cycles) by 33% and 20% for 16 and 32-bit precision results, respectively; thereby increasing the throughputto50Mexp/sandreducingthepowerconsumptionto4.6pJ/exp.Inaddition,thismethodsavesdieareasincenoarithmeticunitsareadopted.Thisexponentialacceleratorissupposedtobeusedinaneuromorphicchipforspikingneuralnetworkmodeling.","PeriodicalId":13437,"journal":{"name":"IEICE Electron. Express","volume":"101 1","pages":"20220393"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEICE Electron. Express","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1587/elex.19.20220393","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A range reduction method for shift-and-add algorithms for exponential functions is proposed in this paper. An exponential function accelerator with this method and radix-16 shift-and-add algorithm has been implemented in SMIC 55 nm CMOS process. Compared with the existing method, the proposed method reduces the latency (cycles) by 33% and 20% for 16 and 32-bit precision results, respectively; thereby increasing the throughputto50Mexp/sandreducingthepowerconsumptionto4.6pJ/exp.Inaddition,thismethodsavesdieareasincenoarithmeticunitsareadopted.Thisexponentialacceleratorissupposedtobeusedinaneuromorphicchipforspikingneuralnetworkmodeling.
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