{"title":"Massive Parallel Max-SAT Solver Based on Speculative Computation","authors":"Yasuki Iizuka, Haruki Koshiba","doi":"10.1109/IIAI-AAI.2019.00241","DOIUrl":null,"url":null,"abstract":"This paper proposes a massive parallel Max-Sat solver based on speculative computation using GPUs. Max-SAT is a combinatorial optimization problem that maximizes the true clauses of the SAT clauses, and many Max-SAT solvers have been proposed. Parallelization is expected as an efficiency improvement method when solving problems with a large amount of computation such as Max-SAT. However, many of the Max-SAT solvers are designed as sequential programs, and the effect of parallelization is limited. In this study, we developed a massive parallel search algorithm by designing a parallel stochastic search algorithm and combining it with parallel speculative computation. From the comparison with existing solvers using the Max-SAT problem, we examine the feasibility of this method.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IIAI-AAI.2019.00241","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper proposes a massive parallel Max-Sat solver based on speculative computation using GPUs. Max-SAT is a combinatorial optimization problem that maximizes the true clauses of the SAT clauses, and many Max-SAT solvers have been proposed. Parallelization is expected as an efficiency improvement method when solving problems with a large amount of computation such as Max-SAT. However, many of the Max-SAT solvers are designed as sequential programs, and the effect of parallelization is limited. In this study, we developed a massive parallel search algorithm by designing a parallel stochastic search algorithm and combining it with parallel speculative computation. From the comparison with existing solvers using the Max-SAT problem, we examine the feasibility of this method.