{"title":"基于精确综合的随机电路设计","authors":"Xiang He, Zhufei Chu","doi":"10.1109/CSTIC52283.2021.9461462","DOIUrl":null,"url":null,"abstract":"Stochastic computing enables computationally complex arithmetic using binary numbers converted to stochastic bitstreams. A large number of applications have used stochastic computing due to its fault-tolerant nature. However, stochastic circuit synthesis presents a larger solution space when compared to classical logic synthesis. Previous methods synthesize stochastic circuits using a heuristic method. In this paper, a novel exact synthesis method using Boolean satisfiability (SAT) is proposed to obtain an optimal stochastic circuit represented by majority-inverter graphs (MIGs). The experimental results suggest that the proposed approach can achieve 21% area reduction, 4% delay improvement, with a 3% mean absolute error trade-off.","PeriodicalId":186529,"journal":{"name":"2021 China Semiconductor Technology International Conference (CSTIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Stochastic Circuit Design Based on Exact Synthesis\",\"authors\":\"Xiang He, Zhufei Chu\",\"doi\":\"10.1109/CSTIC52283.2021.9461462\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Stochastic computing enables computationally complex arithmetic using binary numbers converted to stochastic bitstreams. A large number of applications have used stochastic computing due to its fault-tolerant nature. However, stochastic circuit synthesis presents a larger solution space when compared to classical logic synthesis. Previous methods synthesize stochastic circuits using a heuristic method. In this paper, a novel exact synthesis method using Boolean satisfiability (SAT) is proposed to obtain an optimal stochastic circuit represented by majority-inverter graphs (MIGs). The experimental results suggest that the proposed approach can achieve 21% area reduction, 4% delay improvement, with a 3% mean absolute error trade-off.\",\"PeriodicalId\":186529,\"journal\":{\"name\":\"2021 China Semiconductor Technology International Conference (CSTIC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-03-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 China Semiconductor Technology International Conference (CSTIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSTIC52283.2021.9461462\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 China Semiconductor Technology International Conference (CSTIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSTIC52283.2021.9461462","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Stochastic Circuit Design Based on Exact Synthesis
Stochastic computing enables computationally complex arithmetic using binary numbers converted to stochastic bitstreams. A large number of applications have used stochastic computing due to its fault-tolerant nature. However, stochastic circuit synthesis presents a larger solution space when compared to classical logic synthesis. Previous methods synthesize stochastic circuits using a heuristic method. In this paper, a novel exact synthesis method using Boolean satisfiability (SAT) is proposed to obtain an optimal stochastic circuit represented by majority-inverter graphs (MIGs). The experimental results suggest that the proposed approach can achieve 21% area reduction, 4% delay improvement, with a 3% mean absolute error trade-off.