Position Paper: Prototyping Autonomous Vehicles Applications with Heterogeneous Multi-FpgaSystems

Tarek Elouaret, Stéphane Zuckerman, L. Kessal, Yoan Espada, N. Cuperlier, Guillaume Bresson, F. Ouezdou, Olivier Romain
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引用次数: 3

Abstract

One important feature required by autonomous vehicles is the ability to perform a localization task in order to navigate in both known (urban, suburban, and highways) and unknown environments. Instead of relying on LIDAR technology, we propose to leverage a bio-inspired algorithm relying on more conventional cameras and a large neural network (NN) [2]. Yet, this approach must be able to scale. We propose to investigate the development of an FPGA-based solution. Due to the size of NN, dynamic partial reconfiguration will be required, and an efficient (software-based) scheduler must place the hardware tasks on multiple FPGA chip. We intend to implement this algorithm using a unique custom board, Wizarde, which embeds a 3 × 3 matrix of Zynq SoCs with high-end FPGAs to prototype a possible solution.
意见书:基于异构多fpga系统的自动驾驶汽车原型应用
自动驾驶汽车需要的一个重要功能是能够执行定位任务,以便在已知(城市、郊区和高速公路)和未知环境中进行导航。与依赖激光雷达技术不同,我们建议利用一种基于更传统相机和大型神经网络(NN)的生物启发算法[2]。然而,这种方法必须能够扩展。我们建议研究一种基于fpga的解决方案的开发。由于神经网络的大小,需要动态部分重新配置,并且高效的(基于软件的)调度程序必须将硬件任务放在多个FPGA芯片上。我们打算使用独特的自定义板Wizarde来实现该算法,该板将Zynq soc的3 × 3矩阵与高端fpga嵌入到原型中,以实现可能的解决方案。
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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