Semi-Lagrangian Vlasov simulation on GPUs

In this paper, our goal is to efficiently solve the Vlasov equation on GPUs. A semi-Lagrangian discontinuous Galerkin scheme is used for the discretization. Such kinetic computations are extremely expensive due to the high-dimensional phase space. The SLDG code, which is publicly available under the...

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Vydáno v:Computer physics communications Ročník 254; s. 107351
Hlavní autor: Einkemmer, Lukas
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 01.09.2020
Témata:
General purpose computing on graphic processing units (GPGPU)
GPUs
Performance comparison
Semi-Lagrangian methods
Vlasov simulation
Vlasov simulation
General purpose computing on graphic processing units (GPGPU)
Performance comparison
Semi-Lagrangian methods
GPUs
ISSN:0010-4655, 1879-2944
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Shrnutí:In this paper, our goal is to efficiently solve the Vlasov equation on GPUs. A semi-Lagrangian discontinuous Galerkin scheme is used for the discretization. Such kinetic computations are extremely expensive due to the high-dimensional phase space. The SLDG code, which is publicly available under the MIT license, abstracts the number of dimensions and uses a shared codebase for both GPU and CPU based simulations. We investigate the performance of the implementation on a range of both Tesla (V100, Titan V, K80) and consumer (GTX 1080 Ti) GPUs. Our implementation is typically able to achieve a performance of approximately 470 GB/s on a single GPU and 1600 GB/s on four V100 GPUs connected via NVLink. This results in a speedup of about a factor of ten (comparing a single GPU with a dual socket Intel Xeon Gold node) and approximately a factor of 35 (comparing a single node with and without GPUs). In addition, we investigate the effect of single precision computation on the performance of the SLDG code and demonstrate that a template based dimension independent implementation can achieve good performance regardless of the dimensionality of the problem.
ISSN:0010-4655
1879-2944
DOI:10.1016/j.cpc.2020.107351