A multi-GPU accelerated Vlasov-Poisson solver for microturbulence studies

Microphysics plays a critical role in collisionless plasma transport and affects macroscopic properties like resistivity.

A kinetic description is required to model these anomalous transport phenomena.

The challenge of using kinetic simulations is the immense computational cost associated with accurately modeling the evolution of the species distribution functions in position-velocity phase space.

To address this challenge, new algorithms and techniques are developed to extend the CPU-based VCK continuum kinetic Vlasov-Poisson solver to utilize multiple GPUs.

This code uses a finite-volume discretization to facilitate noise-free fourth-order accurate solutions with robust convergence properties and portable performance across a wide variety of GPU architectures.

Key algorithmic advances include efficient moment integration and techniques for minimizing data communication costs.

In this talk we present the capabilities of the multi-GPU code and include performance metrics on a wide set of problem sizes.

The order of magnitude speedup from the multi-GPU accelerated code enables the study of parameter regimes that are practically inaccessible to the CPU-based version. These advances facilitate more comprehensive studies of microturbulence, including capturing dynamics for realistic electron-proton mass ratios.

The new capabilities from GPU acceleration are leveraged to characterize collisionless resistivity induced by the lower hybrid drift instability in pulsed power inertial confinement fusion experiments.