Jiajian Xiao, G. Kilinç, Philipp Andelfinger, D. Eckhoff, Wentong Cai, A. Knoll
{"title":"Pedal to the Bare Metal: Road Traffic Simulation on FPGAs Using High-Level Synthesis","authors":"Jiajian Xiao, G. Kilinç, Philipp Andelfinger, D. Eckhoff, Wentong Cai, A. Knoll","doi":"10.1145/3384441.3395979","DOIUrl":null,"url":null,"abstract":"The performance of Agent-based Traffic Simulations (ABTS) has been shown to benefit tremendously from offloading to accelerators such as GPUs. In the search for the most suitable hardware platform, reconfigurable hardware is a natural choice. Some recent work considered ABTS on Field-Programmable Gate Arrays (FPGAs), yet only implemented simplified cellular automaton-based models. The recent introduction of support for high-level synthesis from C, C++, and OpenCL in FPGA tool chains allows FPGA designs to be expressed in a form familiar to software developers. However, the performance achievable with this approach in a simulation context is not well-understood. In this work, to the best of our knowledge, we present the first FPGA-accelerated ABTS based on widely-accepted microscopic traffic simulation models, and the first to be generated from high-level code. The achieved speedup of up to 24.3 over a sequential CPU-based execution indicates that recent FPGA toolchains allow simulationists to unlock the performance benefits of reconfigurable hardware without the need to express the simulation models in low-level hardware description languages.","PeriodicalId":422248,"journal":{"name":"Proceedings of the 2020 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2020 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3384441.3395979","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The performance of Agent-based Traffic Simulations (ABTS) has been shown to benefit tremendously from offloading to accelerators such as GPUs. In the search for the most suitable hardware platform, reconfigurable hardware is a natural choice. Some recent work considered ABTS on Field-Programmable Gate Arrays (FPGAs), yet only implemented simplified cellular automaton-based models. The recent introduction of support for high-level synthesis from C, C++, and OpenCL in FPGA tool chains allows FPGA designs to be expressed in a form familiar to software developers. However, the performance achievable with this approach in a simulation context is not well-understood. In this work, to the best of our knowledge, we present the first FPGA-accelerated ABTS based on widely-accepted microscopic traffic simulation models, and the first to be generated from high-level code. The achieved speedup of up to 24.3 over a sequential CPU-based execution indicates that recent FPGA toolchains allow simulationists to unlock the performance benefits of reconfigurable hardware without the need to express the simulation models in low-level hardware description languages.