{"title":"使用OpenACC指令的天鹅绒汇编器","authors":"E. B. Costa, Gabriel P. Silva","doi":"10.29007/pzbt","DOIUrl":null,"url":null,"abstract":"There are several programs available in bioinformatics for DNA sequence assembly. This is typically an extremely time-consuming endeavor, as DNA sequences can be extensive and intricate. Velvet was created to combine short and long read sequencing data into larger genomic sequences. Using OpenMP parallel programming, the last version of Velvet was created to support multiple threads. Through OpenACC directives, we present a new version of Velvet that takes advantage of multiprocessing using graphical processing units (GPU). Our tests demonstrate that this extension of Velvet allows for faster performance and efficient memory use.","PeriodicalId":93549,"journal":{"name":"EPiC series in computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Velvet Assembler Using OpenACC Directives\",\"authors\":\"E. B. Costa, Gabriel P. Silva\",\"doi\":\"10.29007/pzbt\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There are several programs available in bioinformatics for DNA sequence assembly. This is typically an extremely time-consuming endeavor, as DNA sequences can be extensive and intricate. Velvet was created to combine short and long read sequencing data into larger genomic sequences. Using OpenMP parallel programming, the last version of Velvet was created to support multiple threads. Through OpenACC directives, we present a new version of Velvet that takes advantage of multiprocessing using graphical processing units (GPU). Our tests demonstrate that this extension of Velvet allows for faster performance and efficient memory use.\",\"PeriodicalId\":93549,\"journal\":{\"name\":\"EPiC series in computing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"EPiC series in computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.29007/pzbt\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"EPiC series in computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29007/pzbt","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
There are several programs available in bioinformatics for DNA sequence assembly. This is typically an extremely time-consuming endeavor, as DNA sequences can be extensive and intricate. Velvet was created to combine short and long read sequencing data into larger genomic sequences. Using OpenMP parallel programming, the last version of Velvet was created to support multiple threads. Through OpenACC directives, we present a new version of Velvet that takes advantage of multiprocessing using graphical processing units (GPU). Our tests demonstrate that this extension of Velvet allows for faster performance and efficient memory use.