Vidyut3d: a GPU accelerated fluid solver for non-equilibrium plasmas on adaptive grids

TL;DR

This paper introduces Vidyut3d, a GPU-accelerated fluid solver for non-equilibrium plasmas that efficiently utilizes adaptive grids and demonstrates significant performance improvements on modern hardware.

Contribution

The paper presents a novel GPU-accelerated plasma fluid solver using adaptive grids, verified for accuracy and demonstrated on complex 3D plasma simulations with substantial speed-up.

Findings

Achieved 150-400X speed-up on GPU architectures.

Verified second-order accuracy with manufactured solutions.

Successfully simulated atmospheric streamer and RF reactor cases.

Abstract

We present the numerical methods, programming methodology, verification, and performance assessment of a non-equilibrium plasma fluid solver that can effectively utilize current and upcoming central processing and graphics processing unit (CPU+GPU) architectures, in this work. Our plasma fluid model solves the coupled conservation equations for species transport, electrostatic Poisson and electron temperature on adaptive Cartesian grids. Our solver is written using performance portable adaptive-grid/particle management library, AMReX, and is portable over widely available vendor specific GPU architectures. We present verification of our solver using method of manufactured solutions that indicate formal second order accuracy with central diffusion and fifth-order weighted-essentially-non-oscillatory (WENO) advection scheme. We also verify our solver with published literature on capacitive discharges and atmospheric pressure streamer propagation. We demonstrate the use of our solver on two 3D simulation cases: an atmospheric streamer propagation in Ar-H2 mixtures and a low pressure twin electrode radio frequency reactor. Our performance studies on three different CPU+GPU architectures indicate approximately 150-400X speed-up using AMD and NVIDIA GPUs per time step compared to a single CPU core for a 4 million cell simulation with 15 species.