{"title":"Megrez:严格有序分区并行化FPGA路由","authors":"Minghua Shen, Guojie Luo","doi":"10.1109/FCCM.2017.18","DOIUrl":null,"url":null,"abstract":"FPGAs play a crucial role in the space of customizable accelerators over the next few years. A chief limiting factor is that FPGA CAD tools are cumbersome and time-consuming to most application developers. Routing is the most complex step in FPGA design flow and NP-complete problem. The PathFinder routing algorithm is in dominant use in FPGA CAD research. However, PathFinder is sequential in nature and lengthy in runtime. Parallelization has the potential to solve the issue but faces non-trivial challenges. In this work we introduce Megrez that uses strictly-ordered partitioning to explore the parallelism on GPU. Experimental results show that Megrez achieves an average of 15.13× speedup on GPU with negligible influence on the routing quality.","PeriodicalId":124631,"journal":{"name":"2017 IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Megrez: Parallelizing FPGA Routing with Strictly-Ordered Partitioning\",\"authors\":\"Minghua Shen, Guojie Luo\",\"doi\":\"10.1109/FCCM.2017.18\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"FPGAs play a crucial role in the space of customizable accelerators over the next few years. A chief limiting factor is that FPGA CAD tools are cumbersome and time-consuming to most application developers. Routing is the most complex step in FPGA design flow and NP-complete problem. The PathFinder routing algorithm is in dominant use in FPGA CAD research. However, PathFinder is sequential in nature and lengthy in runtime. Parallelization has the potential to solve the issue but faces non-trivial challenges. In this work we introduce Megrez that uses strictly-ordered partitioning to explore the parallelism on GPU. Experimental results show that Megrez achieves an average of 15.13× speedup on GPU with negligible influence on the routing quality.\",\"PeriodicalId\":124631,\"journal\":{\"name\":\"2017 IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FCCM.2017.18\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FCCM.2017.18","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Megrez: Parallelizing FPGA Routing with Strictly-Ordered Partitioning
FPGAs play a crucial role in the space of customizable accelerators over the next few years. A chief limiting factor is that FPGA CAD tools are cumbersome and time-consuming to most application developers. Routing is the most complex step in FPGA design flow and NP-complete problem. The PathFinder routing algorithm is in dominant use in FPGA CAD research. However, PathFinder is sequential in nature and lengthy in runtime. Parallelization has the potential to solve the issue but faces non-trivial challenges. In this work we introduce Megrez that uses strictly-ordered partitioning to explore the parallelism on GPU. Experimental results show that Megrez achieves an average of 15.13× speedup on GPU with negligible influence on the routing quality.