SpectralPlasmaSolver: a Spectral Code for Multiscale Simulations of Collisionless, Magnetized Plasmas

We present the design and implementation of a spectral code, called SpectralPlasmaSolver (SPS), for the solution of the multi-dimensional Vlasov-Maxwell equations. The method is based on a Hermite-Fourier decomposition of the particle distribution function. The code is written in Fortran and uses th...

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Vydáno v:Journal of physics. Conference series Ročník 719; číslo 1; s. 12022 - 12032
Hlavní autoři: Vencels, Juris, Delzanno, Gian Luca, Manzini, Gianmarco, Markidis, Stefano, Peng, Ivy Bo, Roytershteyn, Vadim
Médium: Journal Article
Jazyk:angličtina
Vydáno: Bristol IOP Publishing 01.05.2016
Témata:
Application programming interfaces (API) Codes (symbols) Collisionless plasmas Convolution Distribution functions Maxwell equations Multiprocessing systems Numerical models Plasma devices Plasma flow Plasma jets Vlasov equation Design and implementations Fourier decomposition Magnetized plasmas Multi-scale simulation Particle distribution functions Particle-in-cell simulations Shared memory machines Vlasov-Maxwell equations
Distribution functions
Libraries
Mathematical analysis
Maxwell's equations
Nonlinear equations
Particle in cell technique
Physics
Plasmas (physics)
Preconditioning
Simulation
Spectra
ISSN:1742-6588, 1742-6596, 1742-6596
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Popis
Shrnutí:We present the design and implementation of a spectral code, called SpectralPlasmaSolver (SPS), for the solution of the multi-dimensional Vlasov-Maxwell equations. The method is based on a Hermite-Fourier decomposition of the particle distribution function. The code is written in Fortran and uses the PETSc library for solving the non-linear equations and preconditioning and the FFTW library for the convolutions. SPS is parallelized for shared- memory machines using OpenMP. As a verification example, we discuss simulations of the two-dimensional Orszag-Tang vortex problem and successfully compare them against a fully kinetic Particle-In-Cell simulation. An assessment of the performance of the code is presented, showing a significant improvement in the code running-time achieved by preconditioning, while strong scaling tests show a factor of 10 speed-up using 16 threads.
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ISSN:1742-6588
1742-6596
1742-6596
DOI:10.1088/1742-6596/719/1/012022