{"title":"Impact of FPGA Architecture on Area and Performance of CGRA Overlays","authors":"Ian Taras, J. Anderson","doi":"10.1109/FCCM.2019.00022","DOIUrl":null,"url":null,"abstract":"Coarse-grained reconfigurable arrays (CGRAs) are programmable logic devices with ALU-style processing elements and datapath interconnect. CGRAs can be realized as custom ASICs or implemented on FPGAs as overlays . A key element of CGRAs is that they are typically software programmable with rapid compile times – an advantage arising from their coarse-grained characteristics, simplifying CAD mapping tasks. We implement two previously published CGRAs as overlays on two commercial FPGAs (Intel and Xilinx), and consider the impact of the underlying FPGA architecture on the CGRA area and performance. We present optimizations for the overlays to take advantage of the FPGA architectural features and show a peak performance improvement of 1.93x, as well as maximum area savings of 31.1% and 48.5% for Intel and Xilinx, respectively, relative to a naive first-cut implementation. We also present a novel technique for a configurable multiplexer implementation, which embeds the select signals into SRAM configuration, saving 35.7% in area. The research is conducted using the open-source CGRA-ME (modeling and exploration) framework [1].","PeriodicalId":116955,"journal":{"name":"2019 IEEE 27th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 27th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FCCM.2019.00022","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
Coarse-grained reconfigurable arrays (CGRAs) are programmable logic devices with ALU-style processing elements and datapath interconnect. CGRAs can be realized as custom ASICs or implemented on FPGAs as overlays . A key element of CGRAs is that they are typically software programmable with rapid compile times – an advantage arising from their coarse-grained characteristics, simplifying CAD mapping tasks. We implement two previously published CGRAs as overlays on two commercial FPGAs (Intel and Xilinx), and consider the impact of the underlying FPGA architecture on the CGRA area and performance. We present optimizations for the overlays to take advantage of the FPGA architectural features and show a peak performance improvement of 1.93x, as well as maximum area savings of 31.1% and 48.5% for Intel and Xilinx, respectively, relative to a naive first-cut implementation. We also present a novel technique for a configurable multiplexer implementation, which embeds the select signals into SRAM configuration, saving 35.7% in area. The research is conducted using the open-source CGRA-ME (modeling and exploration) framework [1].