{"title":"通过分区并行化FPGA技术映射","authors":"Chuyu Shen, Zili Lin, Ping Fan, X. Meng, Weikang Qian","doi":"10.1109/FCCM.2016.48","DOIUrl":null,"url":null,"abstract":"The traditional FPGA technology mapping flow is very time-consuming as modern FPGA designs become larger. To speed up this procedure, this paper proposes a new approach based on circuit partition to parallelize it. The idea is to split the original circuit into several sub-circuits and assign each one to a core of a multi-core processor for simultaneous technology mapping. Compared to other existing parallelization methods, our method has the benefit of being independent of the detailed mapping algorithm. Our proposed partition method is able to minimize the quality loss caused by the partitioning. We have successfully integrated the proposed approach into an industrial FPGA mapping platform. The proposed flow gains a speed-up of 1.6X on average on a quad-core processor with negligible influence on the LUT count and the critical path length.","PeriodicalId":113498,"journal":{"name":"2016 IEEE 24th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)","volume":"168 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Parallelizing FPGA Technology Mapping through Partitioning\",\"authors\":\"Chuyu Shen, Zili Lin, Ping Fan, X. Meng, Weikang Qian\",\"doi\":\"10.1109/FCCM.2016.48\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The traditional FPGA technology mapping flow is very time-consuming as modern FPGA designs become larger. To speed up this procedure, this paper proposes a new approach based on circuit partition to parallelize it. The idea is to split the original circuit into several sub-circuits and assign each one to a core of a multi-core processor for simultaneous technology mapping. Compared to other existing parallelization methods, our method has the benefit of being independent of the detailed mapping algorithm. Our proposed partition method is able to minimize the quality loss caused by the partitioning. We have successfully integrated the proposed approach into an industrial FPGA mapping platform. The proposed flow gains a speed-up of 1.6X on average on a quad-core processor with negligible influence on the LUT count and the critical path length.\",\"PeriodicalId\":113498,\"journal\":{\"name\":\"2016 IEEE 24th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)\",\"volume\":\"168 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"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.2016.48\",\"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.2016.48","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Parallelizing FPGA Technology Mapping through Partitioning
The traditional FPGA technology mapping flow is very time-consuming as modern FPGA designs become larger. To speed up this procedure, this paper proposes a new approach based on circuit partition to parallelize it. The idea is to split the original circuit into several sub-circuits and assign each one to a core of a multi-core processor for simultaneous technology mapping. Compared to other existing parallelization methods, our method has the benefit of being independent of the detailed mapping algorithm. Our proposed partition method is able to minimize the quality loss caused by the partitioning. We have successfully integrated the proposed approach into an industrial FPGA mapping platform. The proposed flow gains a speed-up of 1.6X on average on a quad-core processor with negligible influence on the LUT count and the critical path length.