{"title":"Performance Evaluation of Quine-McCluskey Method on Multi-core CPU","authors":"H. Vu, Ngoc-Dai Bui, Anh-Tu Nguyen, ThanhBangLe","doi":"10.1109/NICS54270.2021.9701506","DOIUrl":null,"url":null,"abstract":"The Quine-McCluskey method is an algorithm to minimize Boolean functions. Although the method can be programmed on computers, it takes a long time to return the set of prime implicants, thus slowing the analysis and design of digital logic circuits. As a result, it slows down the dynamic reconfiguration process of programmable logic devices. In this paper, we first propose a data representation for storing implicants in memory to reduce the cache misses of the program. We then propose an algorithm to find all prime implicants of a Boolean function. The algorithm aims to reuse the data available on cache, thus decreasing cache misses. After that, we propose an algorithm for step 2 of the Quine-McCluskey method to select the minimal number of essential prime implicants. The evaluation shows that our proposals achieve much higher performance than the original Quine-McCluskey method. The number of essential prime implicants is a low percentage, less than 50%, of the total prime implicants generated in step 1 of the method.","PeriodicalId":296963,"journal":{"name":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NICS54270.2021.9701506","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 Quine-McCluskey method is an algorithm to minimize Boolean functions. Although the method can be programmed on computers, it takes a long time to return the set of prime implicants, thus slowing the analysis and design of digital logic circuits. As a result, it slows down the dynamic reconfiguration process of programmable logic devices. In this paper, we first propose a data representation for storing implicants in memory to reduce the cache misses of the program. We then propose an algorithm to find all prime implicants of a Boolean function. The algorithm aims to reuse the data available on cache, thus decreasing cache misses. After that, we propose an algorithm for step 2 of the Quine-McCluskey method to select the minimal number of essential prime implicants. The evaluation shows that our proposals achieve much higher performance than the original Quine-McCluskey method. The number of essential prime implicants is a low percentage, less than 50%, of the total prime implicants generated in step 1 of the method.