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GX: a GPU-native gyrokinetic turbulence code for tokamak and stellarator design
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GX: a GPU-native gyrokinetic turbulence code for tokamak and stellarator design
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GX is a code for solving the nonlinear gyrokinetic system for low-frequency turbulence in magnetized plasmas, particularly tokamaks and stellarators. In GX, our primary motivation and target is a fast gyrokinetic solver that can be used for fusion reactor design and optimization along with wide-ranging physics exploration. This has led to several code and algorithm design decisions, specifically chosen to prioritize time to solution. First, we have used a discretization algorithm that is pseudo-spectral in the entire phase-space, including a Laguerre-Hermite pseudo-spectral formulation of velocity space, which allows for smooth interpolation between coarse gyrofluid-like resolutions and finer conventional gyrokinetic resolutions and efficient evaluation of a model collision operator. Additionally, we have built GX to natively target graphics processors (GPUs), which are among the fastest computational platforms available today. Finally, we have taken advantage of the reactor-relevant limit of small $\rho_*$ by using the radially-local flux-tube approach. In this paper we present details about the gyrokinetic system and the numerical algorithms used in GX to solve the system. We then present several numerical benchmarks against established gyrokinetic codes in both tokamak and stellarator magnetic geometries to verify that GX correctly simulates gyrokinetic turbulence in the small $\rho_*$ limit. Moreover, we show that the convergence properties of the Laguerre-Hermite spectral velocity formulation are quite favorable for nonlinear problems of interest. Coupled with GPU acceleration, which we also investigate with scaling studies, this enables GX to be able to produce useful turbulence simulations in minutes on one (or a few) GPUs. GX is open-source software that is ready for fusion reactor design studies.
Forward citations
Cited by 2 Pith papers
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MAESTRO couples surrogate optimization transport modeling with external solvers to enable efficient full-physics steady-state plasma predictions in fusion devices.
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