A HIGH PERFORMANCE FRAMEWORK FOR AGENT BASED PEDESTRIAN DYNAMICS ON GPU HARDWARE
A HIGH PERFORMANCE FRAMEWORK FOR AGENT BASED PEDESTRIAN DYNAMICS ON GPU HARDWARE
复制标题
GPU 硬件上基于代理的行人动力学的高性能框架
DOI：
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
D. Romano
中科院分区：
文献类型：
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作者：
P. Richmond;D. Romano
行人模拟最近集中在自上而下的实现上，忽略了更多计算密集型的基于代理的动力学。本文提出了一种基于图形处理单元(GPU)的基于代理的建模框架，用于演示大规模的行人模拟和绘制。GPU硬件为动态大规模人群模拟提供了显著的性能，但是将计算任务映射到GPU的过程并不是微不足道的，并且需要专业知识。因此，提出了一种基于代理的规范技术，它允许隐藏底层的GPU数据存储和代理通信。该框架允许使用静态地图来设置静态环境障碍，并描述了用于路径规划的分区技术。并行种群反馈例程还用于实现细节级别(LOD)渲染，这避免了任何代价高昂的CPU数据回读。。
Pedestrian simulations have recently focused on top-down implementations ignoring more computationally intensive agent based dynamics. This paper presents a framework for agent based modelling on the Graphics Processing Unit (GPU) which demonstrates large scale pedestrian simulation and rendering. GPU hardware offers significant performance for dynamic large crowd simulations, however the process of mapping computational tasks to the GPU is not trivial and expert knowledge is required. An agent based specification technique is therefore presented, which allows the underlying GPU data storage and agent communication to be hidden. The framework allows the use of static maps to set static environment obstacles and a zoning technique is described for route planning. Parallel population feedback routines are also used to implement Level of Detail (LOD) rendering which avoids any costly CPU data read-back. .