Fine-sorting One-dimensional Particle-In-Cell Algorithm with Monte-Carlo Collisions on a Graphics Processing Unit

TL;DR

This paper presents a GPU-accelerated one-dimensional particle-in-cell simulation with a novel fine-sorting algorithm that significantly reduces computation time for plasma kinetic studies.

Contribution

It introduces a fine-sorting PIC algorithm optimized for Nvidia GPUs, improving simulation speed over traditional CPU methods.

Findings

Achieved substantial speed-up on Nvidia GPUs using CUDA.

Demonstrated effective parallelization of PIC simulations with Monte-Carlo collisions.

Provided implementation details and optimization strategies for GPU-based PIC codes.

Abstract

Particle-in-cell (PIC) simulations with Monte-Carlo collisions are used in plasma science to explore a variety of kinetic effects. One major problem is the long run-time of such simulations. Even on modern computer systems, PIC codes take a considerable amount of time for convergence. Most of the computations can be massively parallelized, since particles behave independently of each other within one time step. Current graphics processing units (GPUs) offer an attractive means for execution of the parallelized code. In this contribution we show a one-dimensional PIC code running on Nvidia GPUs using the CUDA environment. A distinctive feature of the code is that size of the cells that the code uses to sort the particles with respect to their coordinates is comparable to size of the grid cells used for discretization of the electric field. Hence, we call the corresponding algorithm "fine-sorting". Implementation details and optimization of the code are discussed and the speed-up compared to classical CPU approaches is computed.