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Implementation and Optimization of a 1D2V PIC Method for Nonlinear Kinetic Models on GPUs

Title data

Korch, Matthias ; Raithel, Philipp ; Werner, Tim:
Implementation and Optimization of a 1D2V PIC Method for Nonlinear Kinetic Models on GPUs.
In: 2020 28th Euromicro International Conference on Parallel, Distributed and Network-Based Processing : PDP 2020 ; Proceedings. - Piscataway, NJ : IEEE , 2020 . - pp. 30-37
ISBN 978-1-7281-6582-0
DOI: https://doi.org/10.1109/PDP50117.2020.00012

Project information

Project title:
Project's official titleProject's id
Optimierungstechniken für explizite Verfahren zur GPU-beschleunigten Lösung von Anfangswertproblemen gewöhnlicher Differenzialgleichungen (OTEGO)KO 2252/3-2

Project financing: Deutsche Forschungsgemeinschaft

Abstract in another language

This paper considers the parallel numerical simulation of the time evolution of galaxies and globular clusters on GPUs. The model used is the Einstein-Vlasov system, which is designed, in particular, to study the formation of black holes and spacetime singularities in a general relativistic framework. First, a reference implementation is derived using NVIDIA CUDA as programming model, which is then optimized in several steps. Bottlenecks are identified by profiling, and different approaches, namely particle sort, improved treatment of atomic operations, and kernel fusion are investigated to overcome these bottlenecks. Each optimized variant is evaluated in relation to the other variants using detailed runtime experiments and profiling results. Using in the order of 10^7 to 10^8 particles, speedups between 1.84 and 2.38 w.r.t. the reference implementation have been observed.

Further data

Item Type: Article in a book
Refereed: Yes
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science II > Chair Applied Computer Science II - Univ.-Prof. Dr. Thomas Rauber
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 23 Oct 2020 08:42
Last Modified: 23 Oct 2020 08:42
URI: https://eref.uni-bayreuth.de/id/eprint/57914