{"title":"Realization of Game Tree Search Algorithms on FPGA: A Comparative Study","authors":"Pranav Gangwar, Satvik Maurya, N. Pandey","doi":"10.1109/ICICT46931.2019.8977671","DOIUrl":null,"url":null,"abstract":"This paper deals with realization of search algorithms used in the game solvers on the FPGA. Three algorithms namely Minimax, Alpha-Beta Pruning, and NegaScout are realized and compared amongst each other, and also with their software realization for the sake of completion. Results show that the FPGA based implementations are exceptionally faster than their software counterparts, with the NegaScout algorithm outperforming the conventionally used Alpha-Beta Pruning, and the Minimax algorithm, both in software and hardware. The NegaScout algorithm is 1.3 times faster than the Alpha-Beta Pruning algorithm and 2.6 times faster than the Minimax algorithm on hardware, while incurring a nominal cost in terms of FPGA resource utilization.","PeriodicalId":412668,"journal":{"name":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICT46931.2019.8977671","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 deals with realization of search algorithms used in the game solvers on the FPGA. Three algorithms namely Minimax, Alpha-Beta Pruning, and NegaScout are realized and compared amongst each other, and also with their software realization for the sake of completion. Results show that the FPGA based implementations are exceptionally faster than their software counterparts, with the NegaScout algorithm outperforming the conventionally used Alpha-Beta Pruning, and the Minimax algorithm, both in software and hardware. The NegaScout algorithm is 1.3 times faster than the Alpha-Beta Pruning algorithm and 2.6 times faster than the Minimax algorithm on hardware, while incurring a nominal cost in terms of FPGA resource utilization.