Efficient GPU implementation of the Particle-in-Cell/Monte-Carlo collisions method for 1D simulation of low-pressure capacitively coupled plasmas
| Autor: | Zoltan Juhasz, Štefan Matejčík, Zoltan Donko, Aranka Derzsi, Ján Ďurian, Peter Hartmann |
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| Rok vydání: | 2021 |
| Předmět: |
Correctness
Speedup Computer science Reference data (financial markets) Monte Carlo method General Physics and Astronomy 01 natural sciences 010305 fluids & plasmas Computational science CUDA Hardware and Architecture 0103 physical sciences Computer Science::Mathematical Software Benchmark (computing) Particle-in-cell 010306 general physics Massively parallel |
| Zdroj: | Computer Physics Communications. 263:107913 |
| ISSN: | 0010-4655 |
| DOI: | 10.1016/j.cpc.2021.107913 |
| Popis: | In this paper, we describe an efficient, massively parallel GPU implementation strategy for speeding up one-dimensional electrostatic plasma simulations based on the Particle-in-Cell method with Monte-Carlo collisions. Relying on the Roofline performance model, we identify performance-critical points of the program and provide optimised solutions. We use four benchmark cases to verify the correctness of the CUDA and OpenCL implementations and analyse their performance properties on a number of NVIDIA and AMD cards. Plasma parameters computed with both GPU implementations differ not more than 2% from each other and respective literature reference data. Our final implementations reach over 2.6 Tflop/s sustained performance on a single card, and show speed up factors of up to 200 (when using 10 million particles). We demonstrate that GPUs can be very efficiently used for simulating collisional plasmas and argue that their further use will enable performing more accurate simulations in shorter time, increase research productivity and help in advancing the science of plasma simulation. |
| Databáze: | OpenAIRE |
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