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

Jiajian Xiao, G. Kilinç, Philipp Andelfinger, D. Eckhoff, Wentong Cai, A. Knoll
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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.
踏板到裸金属:使用高级合成的fpga道路交通模拟
基于代理的交通模拟(ABTS)的性能已经被证明从卸载到诸如gpu之类的加速器中受益匪浅。在寻找最合适的硬件平台时,可重构硬件是一个自然的选择。最近的一些工作考虑了现场可编程门阵列(fpga)上的ABTS,但只实现了简化的基于元胞自动机的模型。最近在FPGA工具链中引入了对来自C、c++和OpenCL的高级合成的支持,这使得FPGA设计能够以软件开发人员熟悉的形式表示。然而,这种方法在模拟环境中所能达到的性能还没有得到很好的理解。在这项工作中,据我们所知,我们提出了第一个基于广泛接受的微观交通模拟模型的fpga加速ABTS,也是第一个由高级代码生成的ABTS。通过基于cpu的顺序执行实现的高达24.3的加速表明,最近的FPGA工具链允许仿真人员解锁可重构硬件的性能优势,而无需用低级硬件描述语言表达仿真模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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