Abstract
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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