Pedal to the Bare Metal: Road Traffic Simulation on FPGAs Using High-Level Synthesis

Xiao, Jiajian and Kilinç, Görkem and Andelfinger, Philipp and Eckhoff, David and Cai, Wentong and Knoll, Alois (2020) Pedal to the Bare Metal: Road Traffic Simulation on FPGAs Using High-Level Synthesis. In: ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (PADS 2020), 15-17 Jun 2020, Miami, Florida, USA. Proceedings, published by ACM, New York, NY, USA, pp. 117-121.

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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.

Item Type: Conference or Workshop Item (Paper)