Abstract
A novel high-performance computing algorithm, developed in response to the next generation of computational challenges associated with burning plasma regimes in ITER-scale tokamak devices, has been tested and is described herein. The Lorentz-orbit code for use in stellarators and tokamaks (LOCUST) is designed for computationally scalable modelling of fast-ion dynamics, in the presence of detailed first wall geometries and fine 3D magnetic field structures. It achieves this through multiple levels of single instruction, multiple thread parallelism and by leveraging general-purpose graphics processing units. This enables LOCUST to rapidly track the full-orbit trajectories of kinetic Monte Carlo markers to deliver high-resolution fast-ion distribution functions and plasma-facing component power loads. LOCUST has been tested against the prominent NUBEAM and ASCOT fast-ion codes. All codes were compared for collisional plasmas in both high and low-aspect ratio toroidal geometries, with full-orbit and guiding-centre tracking. LOCUST produces statistically consistent results in line with acceptable theoretical and Monte Carlo uncertainties. Synthetic fast-ion D-α diagnostics produced by LOCUST are also compared to experiment using FIDASIM and show good agreement.
Highlights
The size, power and performance of the ITER tokamak represents a paradigm shift in both experimental and computational fusion science
There are multiple ways to advance computational capabilities, and adapting to novel or specialised hardware is one. This approach is advantageous for a number of reasons other than an immediate speed boost: the lower cost, energy consumption and space required can make specialised hardware more efficient for specific tasks; specialised hardware can be more accessible at the hardware level, for example interfacing with workstation devices directly via PCIe buses to avoid the need for remote data centres; minimal adaptation is required for modular or encapsulated code; and future hardware generations bring passive performance improvements more rapidly, depending on the type of hardware market [5]
The co-current NBI confines the fast ions to the plasma core, where discrepancies are hard to distinguish and there is a systematic shift in spatial density due to the finite Larmor radius (FLR) displacement, so instead we examine f ( ), the distribution function integrated over all dimensions except energy, which still encodes some real-space information through the effects of the steep temperature and density gradients on the fast-ion diffusion rate
Summary
The size, power and performance of the ITER tokamak represents a paradigm shift in both experimental and computational fusion science. There are multiple ways to advance computational capabilities, and adapting to novel or specialised hardware is one This approach is advantageous for a number of reasons other than an immediate speed boost: the lower cost, energy consumption and space required can make specialised hardware more efficient for specific tasks; specialised hardware can be more accessible at the hardware level, for example interfacing with workstation devices directly via PCIe buses to avoid the need for remote data centres; minimal adaptation is required for modular or encapsulated code; and future hardware generations bring passive performance improvements more rapidly, depending on the type of hardware market [5].
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