{"title":"随机电路的谱变换方法","authors":"Armin Alaghi, J. Hayes","doi":"10.1109/ICCD.2012.6378658","DOIUrl":null,"url":null,"abstract":"Stochastic computing (SC) processes data in the form of long pseudo-random bit-streams denoting probabilities. Its key advantages are simple computational elements and high soft-error tolerance. Recent technology developments have revealed important new SC applications such as image processing and LDPC decoding. Despite its long history, SC still lacks a comprehensive design methodology; existing methods tend to be ad hoc and limited to a few arithmetic functions. We demonstrate a fundamental relation between stochastic circuits and spectral transforms. Based on this, we propose a transform approach to the analysis and synthesis of SC circuits. We illustrate the approach for a variety of basic combinational SC design problems, and show that the area cost associated with stochastic number generation can be significantly reduced.","PeriodicalId":313428,"journal":{"name":"2012 IEEE 30th International Conference on Computer Design (ICCD)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"45","resultStr":"{\"title\":\"A spectral transform approach to stochastic circuits\",\"authors\":\"Armin Alaghi, J. Hayes\",\"doi\":\"10.1109/ICCD.2012.6378658\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Stochastic computing (SC) processes data in the form of long pseudo-random bit-streams denoting probabilities. Its key advantages are simple computational elements and high soft-error tolerance. Recent technology developments have revealed important new SC applications such as image processing and LDPC decoding. Despite its long history, SC still lacks a comprehensive design methodology; existing methods tend to be ad hoc and limited to a few arithmetic functions. We demonstrate a fundamental relation between stochastic circuits and spectral transforms. Based on this, we propose a transform approach to the analysis and synthesis of SC circuits. We illustrate the approach for a variety of basic combinational SC design problems, and show that the area cost associated with stochastic number generation can be significantly reduced.\",\"PeriodicalId\":313428,\"journal\":{\"name\":\"2012 IEEE 30th International Conference on Computer Design (ICCD)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"45\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE 30th International Conference on Computer Design (ICCD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCD.2012.6378658\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE 30th International Conference on Computer Design (ICCD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCD.2012.6378658","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A spectral transform approach to stochastic circuits
Stochastic computing (SC) processes data in the form of long pseudo-random bit-streams denoting probabilities. Its key advantages are simple computational elements and high soft-error tolerance. Recent technology developments have revealed important new SC applications such as image processing and LDPC decoding. Despite its long history, SC still lacks a comprehensive design methodology; existing methods tend to be ad hoc and limited to a few arithmetic functions. We demonstrate a fundamental relation between stochastic circuits and spectral transforms. Based on this, we propose a transform approach to the analysis and synthesis of SC circuits. We illustrate the approach for a variety of basic combinational SC design problems, and show that the area cost associated with stochastic number generation can be significantly reduced.