并行时空处理模型下的快速N-body算法

图形处理器(graphic processing unit,GPU)的最新发展已经能够以低廉的成本提供高性能的通用计算。基于GPU的CUDA(compute unified device architecture)和OpenCL(open computing language)编程模型为程序员提供了充足的类似于C语言的应用程序接口(application programming interface,API),便于程序员发挥GPU的并行计算能力。采用图形硬件进行加速计算,通过一种新的GPU处理模型——并行时间空间模型,对现有GPU上的N-body实现进行了分析,从而提出了一种新的GPU上快速仿真N-body问题的算法,并在AMD的HD Radeon 5850上进行了实现。实验结果表明,相对于CPU上的实现,获得了400倍左右的加速;相对于已有GPU上的实现,也获得了2至5倍的加速。

Parallel Time-Space Processing Model Based Fast N-body Simulation

With the development of graphic processing unit (GPU), the general processing with high performance can be achieved with low cost. The GPU based compute unified device architecture (CUDA) and open computing language (OpenCL) programming model provide adequate application programming interfaces (APIs) similar to C language, which can be utilized by programmer with the power of GPU parallel processing. This paper presents a novel parallel implementation algorithm of N-body gravitational simulation on GPU. The algorithm uses graphics hardware to accelerate computation, and is optimized to N-body computation based on parallel time-space processing model (PTPM) on GPUs. The paper also analyzes the current implementations of GPU, and gives a new method on implementing N-body algorithm on HD Radeon 5850 GPU of AMD. Experimental results show that this method achieves an acceleration of 400 times compared with CPU, and an acceleration up to 2-5 times compared with GPU.