{"title":"Mapping-Aware Constrained Scheduling for LUT-Based FPGAs","authors":"Mingxing Tan, Steve Dai, Udit Gupta, Zhiru Zhang","doi":"10.1145/2684746.2689063","DOIUrl":null,"url":null,"abstract":"Scheduling plays a central role in high-level synthesis, as it inserts clock boundaries into the untimed behavioral model and greatly impacts the performance, power, and area of the synthesized circuits. While current scheduling techniques can make use of pre-characterized delay values of individual operations, it is difficult to obtain accurate timing estimation on a cluster of operations without considering technology mapping. This limitation is particularly pronounced for FPGAs where a large logic network can be mapped to only a few levels of look-up tables (LUT). In this paper, we propose MAPS, a mapping-aware constrained scheduling algorithm for LUT-based FPGAs. Instead of simply summing up the estimated delay values of individual operations, MAPS jointly performs technology mapping and scheduling, creating the opportunity for more aggressive operation chaining to minimize latency and reduce area. We show that MAPS can produce a latency-optimal solution, while supporting a variety of design timing requirements expressed in a system of difference constraints. We also present an efficient incremental scheduling technique for MAPS to effectively handle resource constraints. Experimental results with real-life benchmarks demonstrate that our proposed algorithm achieves very promising improvements in performance and resource usage when compared to a state-of-the-art commercial high-level synthesis tool targeting Xilinx FPGAs.","PeriodicalId":388546,"journal":{"name":"Proceedings of the 2015 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2015 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2684746.2689063","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
Scheduling plays a central role in high-level synthesis, as it inserts clock boundaries into the untimed behavioral model and greatly impacts the performance, power, and area of the synthesized circuits. While current scheduling techniques can make use of pre-characterized delay values of individual operations, it is difficult to obtain accurate timing estimation on a cluster of operations without considering technology mapping. This limitation is particularly pronounced for FPGAs where a large logic network can be mapped to only a few levels of look-up tables (LUT). In this paper, we propose MAPS, a mapping-aware constrained scheduling algorithm for LUT-based FPGAs. Instead of simply summing up the estimated delay values of individual operations, MAPS jointly performs technology mapping and scheduling, creating the opportunity for more aggressive operation chaining to minimize latency and reduce area. We show that MAPS can produce a latency-optimal solution, while supporting a variety of design timing requirements expressed in a system of difference constraints. We also present an efficient incremental scheduling technique for MAPS to effectively handle resource constraints. Experimental results with real-life benchmarks demonstrate that our proposed algorithm achieves very promising improvements in performance and resource usage when compared to a state-of-the-art commercial high-level synthesis tool targeting Xilinx FPGAs.