GPU Computing for Compute-Intensive Scientific Calculation

Dubey, Sandhya Parasnath; Kumar, M. Sathish; Balaji, S.

doi:10.1007/978-981-15-0184-5_12

Cited by 2 publications

(1 citation statement)

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“…Graphics processing units (GPUs) have been established in the last years as off-the-shelf, massively parallel computing platforms, usable for high-performance scientific computing [32,33]. Thanks to CUDA (Compute Unified Device Architecture) [34], significant speedups have been observed for several computational problems. Most recently, high-level languages, such as Matlab, have acquired the capability of running portions of code accelerated by GPU processing [35].…”

Section: Introductionmentioning

confidence: 99%

Numerical Aspects of Particle-in-Cell Simulations for Plasma-Motion Modeling of Electric Thrusters

et al. 2021

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The present work is focused on a detailed description of an in-house, particle-in-cell code developed by the authors, whose main aim is to perform highly accurate plasma simulations on an off-the-shelf computing platform in a relatively short computational time, despite the large number of macro-particles employed in the computation. A smart strategy to set up the code is proposed, and in particular, the parallel calculation in GPU is explored as a possible solution for the reduction in computing time. An application on a Hall-effect thruster is shown to validate the PIC numerical model and to highlight the strengths of introducing highly accurate schemes for the electric field interpolation and the macroparticle trajectory integration in the time. A further application on a helicon double-layer thruster is presented, in which the particle-in-cell (PIC) code is used as a fast tool to analyze the performance of these specific electric motors.

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Section: Introductionmentioning

confidence: 99%