高效的GPU实现粒子单元算法

R. Joseph, Girish Ravunnikutty, S. Ranka, E. D'Azevedo, S. Klasky
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引用次数: 14

摘要

粒子池(PIC)算法是等离子体物理学中广泛应用的一种研究带电粒子在电磁场作用下运动轨迹的方法。PIC算法计算量大,其时间要求与模拟中涉及的带电粒子数量成正比。本文的重点是在图形处理器(GPU)上并行化PIC算法。我们提出了几个与小共享内存和GPU上的原子操作相关的性能权衡,以实现高性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient GPU Implementation for Particle in Cell Algorithm
Particle in cell (PIC) algorithm is a widely used method in plasma physics to study the trajectories of charged particles under electromagnetic fields. The PIC algorithm is computationally intensive and its time requirements are proportional to the number of charged particles involved in the simulation. The focus of the paper is to parallelize the PIC algorithm on Graphics Processing Unit (GPU). We present several performance trade-offs related to small shared memory and atomic operations on the GPU to achieve high performance.
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