{"title":"fpga的低延迟双精度浮点除法","authors":"B. Liebig, A. Koch","doi":"10.1109/FPT.2014.7082762","DOIUrl":null,"url":null,"abstract":"With growing FPGA capacities, applications requiring more intensive use of floating-point arithmetic become feasible candidates for acceleration using reconfigurable logic. Still among the more uncommon operations, however, are fast double-precision divider units. Since our application domain (acceleration of custom-compiled convex solvers) heavily relies on these blocks, we have implemented low-latency dividers based on the Goldschmidt algorithm that are accurate up to 1 bit of least precision (1-ULP). On Virtex-6 devices, our units operate at 200 MHz and significantly outperform other state-of-the-art 1-ULP dividers. We evaluate our blocks both stand-alone, as well as on the application-level when used for the high-level synthesis of the convex solver cores.","PeriodicalId":6877,"journal":{"name":"2014 International Conference on Field-Programmable Technology (FPT)","volume":"29 1","pages":"107-114"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Low-latency double-precision floating-point division for FPGAs\",\"authors\":\"B. Liebig, A. Koch\",\"doi\":\"10.1109/FPT.2014.7082762\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With growing FPGA capacities, applications requiring more intensive use of floating-point arithmetic become feasible candidates for acceleration using reconfigurable logic. Still among the more uncommon operations, however, are fast double-precision divider units. Since our application domain (acceleration of custom-compiled convex solvers) heavily relies on these blocks, we have implemented low-latency dividers based on the Goldschmidt algorithm that are accurate up to 1 bit of least precision (1-ULP). On Virtex-6 devices, our units operate at 200 MHz and significantly outperform other state-of-the-art 1-ULP dividers. We evaluate our blocks both stand-alone, as well as on the application-level when used for the high-level synthesis of the convex solver cores.\",\"PeriodicalId\":6877,\"journal\":{\"name\":\"2014 International Conference on Field-Programmable Technology (FPT)\",\"volume\":\"29 1\",\"pages\":\"107-114\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Field-Programmable Technology (FPT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FPT.2014.7082762\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Field-Programmable Technology (FPT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FPT.2014.7082762","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Low-latency double-precision floating-point division for FPGAs
With growing FPGA capacities, applications requiring more intensive use of floating-point arithmetic become feasible candidates for acceleration using reconfigurable logic. Still among the more uncommon operations, however, are fast double-precision divider units. Since our application domain (acceleration of custom-compiled convex solvers) heavily relies on these blocks, we have implemented low-latency dividers based on the Goldschmidt algorithm that are accurate up to 1 bit of least precision (1-ULP). On Virtex-6 devices, our units operate at 200 MHz and significantly outperform other state-of-the-art 1-ULP dividers. We evaluate our blocks both stand-alone, as well as on the application-level when used for the high-level synthesis of the convex solver cores.