CPU和GPU上道路交通仿真速度的比较

Daniel Rajf, T. Potuzak
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引用次数: 1

摘要

在本文中,我们描述了在GPU和CPU上执行的微观道路交通模拟性能的公平比较。我们工作的目的是确定加速,如果使用GPU而不是(多核)CPU进行相同的模拟,则可以实现加速。为此,创建了一个能够在两个平台上运行的微观道路交通模拟器,目的是使基于gpu的模拟和基于cpu的模拟尽可能相似。采用两种不同的道路交通模型(车辆跟随模型和元胞自动机模型)、四种不同大小的道路交通网络(十字路口的规则方形网格)和三种不同的硬件配置,对基于gpu和cpu的仿真进行了性能测试。对于元胞自动机模型,使用GPU代替多核CPU实现的最大加速为12.4。对于汽车跟随模型,实现的最大加速为10.7。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of Road Traffic Simulation Speed on CPU and GPU
In this paper, we describe a fair comparison of the performance of a microscopic road traffic simulation performed on a GPU and on a CPU. The aim of our work is to determine the speedup, which can be achieved if the GPU is used for the same simulation instead of the (multi-core) CPU. A microscopic road traffic simulator capable of running on both platforms was created for this purpose with the aim to make the GPU-based and the CPU-based simulations as similar as possible. The performances of both the GPU-based and the CPU-based simulations were tested using two different road traffic models (a car-following model and a cellular automaton model), four road traffic networks (regular square grids of crossroads) of different sizes, and three different hardware configurations. The maximal achieved speedup using the GPU instead of the multi-core CPU for the cellular automaton model was 12.4. For the car-following model, the maximal achieved speedup was 10.7.
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