{"title":"基于FPGA的顶点中心图处理","authors":"Nina Engelhardt, Hayden Kwok-Hay So","doi":"10.1109/FCCM.2016.31","DOIUrl":null,"url":null,"abstract":"Past research and implementation efforts have shown that FPGAs are efficient at processing many graph algorithms. However, they are notoriously hard to program, leading to impractically long development times even for simple applications. We propose a vertex-centric framework for graph processing on FPGAs, providing a base execution model and distributed architecture so that developers need only write very small application kernels.","PeriodicalId":113498,"journal":{"name":"2016 IEEE 24th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Vertex-Centric Graph Processing on FPGA\",\"authors\":\"Nina Engelhardt, Hayden Kwok-Hay So\",\"doi\":\"10.1109/FCCM.2016.31\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Past research and implementation efforts have shown that FPGAs are efficient at processing many graph algorithms. However, they are notoriously hard to program, leading to impractically long development times even for simple applications. We propose a vertex-centric framework for graph processing on FPGAs, providing a base execution model and distributed architecture so that developers need only write very small application kernels.\",\"PeriodicalId\":113498,\"journal\":{\"name\":\"2016 IEEE 24th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE 24th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FCCM.2016.31\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 24th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FCCM.2016.31","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Past research and implementation efforts have shown that FPGAs are efficient at processing many graph algorithms. However, they are notoriously hard to program, leading to impractically long development times even for simple applications. We propose a vertex-centric framework for graph processing on FPGAs, providing a base execution model and distributed architecture so that developers need only write very small application kernels.