{"title":"基于FPGA的系统发育树重构的最大简约算法硬件加速","authors":"Henry Block, T. Maruyama","doi":"10.1109/FPT.2013.6718376","DOIUrl":null,"url":null,"abstract":"In this paper, we present a hardware acceleration approach for a phylogenetic tree reconstruction with maximum parsimony algorithm using FPGA. The algorithm is based on a stochastic local search with the progressive tree neighborhood. The hardware architecture is divided in different units, each of which performs a specific task of the algorithm, to take advantage of the parallel processing capabilities of the FPGA. We show results for four real-world biological datasets, and compare them against results from two programs: our C++ implementation and TNT (a program for phylogenetic analysis). High acceleration rates are obtained against our C++ implementation, but not against TNT, which even shows to be faster in some cases. We conclude our work with a discussion on this issue.","PeriodicalId":344469,"journal":{"name":"2013 International Conference on Field-Programmable Technology (FPT)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"A hardware acceleration of a phylogenetic tree reconstruction with maximum parsimony algorithm using FPGA\",\"authors\":\"Henry Block, T. Maruyama\",\"doi\":\"10.1109/FPT.2013.6718376\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present a hardware acceleration approach for a phylogenetic tree reconstruction with maximum parsimony algorithm using FPGA. The algorithm is based on a stochastic local search with the progressive tree neighborhood. The hardware architecture is divided in different units, each of which performs a specific task of the algorithm, to take advantage of the parallel processing capabilities of the FPGA. We show results for four real-world biological datasets, and compare them against results from two programs: our C++ implementation and TNT (a program for phylogenetic analysis). High acceleration rates are obtained against our C++ implementation, but not against TNT, which even shows to be faster in some cases. We conclude our work with a discussion on this issue.\",\"PeriodicalId\":344469,\"journal\":{\"name\":\"2013 International Conference on Field-Programmable Technology (FPT)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Field-Programmable Technology (FPT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FPT.2013.6718376\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Field-Programmable Technology (FPT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FPT.2013.6718376","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A hardware acceleration of a phylogenetic tree reconstruction with maximum parsimony algorithm using FPGA
In this paper, we present a hardware acceleration approach for a phylogenetic tree reconstruction with maximum parsimony algorithm using FPGA. The algorithm is based on a stochastic local search with the progressive tree neighborhood. The hardware architecture is divided in different units, each of which performs a specific task of the algorithm, to take advantage of the parallel processing capabilities of the FPGA. We show results for four real-world biological datasets, and compare them against results from two programs: our C++ implementation and TNT (a program for phylogenetic analysis). High acceleration rates are obtained against our C++ implementation, but not against TNT, which even shows to be faster in some cases. We conclude our work with a discussion on this issue.