{"title":"Amoeba-Inspired Hardware SAT Solver with Effective Feedback Control","authors":"Anh Hoang Ngoc Nguyen, M. Aono, Yuko Hara-Azumi","doi":"10.1109/ICFPT47387.2019.00038","DOIUrl":null,"url":null,"abstract":"In this paper, we focus on an amoeba-inspired algorithm, \"AmoebaSAT,\" to solve Boolean satisfiability (SAT) problems. A hardware SAT solver is useful for a variety of control applications in Internet-of-Things edge-computing systems whose control constraints can be reduced to a SAT problem. We develop efficient AmoebaSAT solvers on an FPGA by realizing various feedback controls to find a solution quickly. To extract the inherent parallelism of the AmoebaSAT, a high-level design approach (i.e., high-level synthesis and its pragmas) is applied together with hardware-friendly code transformations/algorithmic extensions. We demonstrate that our FPGA-based AmoebaSAT solvers can achieve significant iterations reduction and speedup to find a solution compared with state-of-the-art SAT solvers. Furthermore, we show the effectiveness of our work in the scalability (i.e., resource utilization in FPGA) and the parallelism.","PeriodicalId":241340,"journal":{"name":"2019 International Conference on Field-Programmable Technology (ICFPT)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Field-Programmable Technology (ICFPT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICFPT47387.2019.00038","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
In this paper, we focus on an amoeba-inspired algorithm, "AmoebaSAT," to solve Boolean satisfiability (SAT) problems. A hardware SAT solver is useful for a variety of control applications in Internet-of-Things edge-computing systems whose control constraints can be reduced to a SAT problem. We develop efficient AmoebaSAT solvers on an FPGA by realizing various feedback controls to find a solution quickly. To extract the inherent parallelism of the AmoebaSAT, a high-level design approach (i.e., high-level synthesis and its pragmas) is applied together with hardware-friendly code transformations/algorithmic extensions. We demonstrate that our FPGA-based AmoebaSAT solvers can achieve significant iterations reduction and speedup to find a solution compared with state-of-the-art SAT solvers. Furthermore, we show the effectiveness of our work in the scalability (i.e., resource utilization in FPGA) and the parallelism.