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Efficient GPU-based Smoothed Particle Hydrodynamics

Title data

Korch, Matthias ; Werner, Tim:
Efficient GPU-based Smoothed Particle Hydrodynamics.
Event: PARNUM 2017 , 19.-21. Apr. 2017 , Waischenfeld, Deutschland.
(Conference item: Workshop , Speech )

Abstract in another language

Smoothed particle hydrodynamics (SPH) is a numerical method, which simulates a fluid by dividing it into particles interacting with each other. For reducing the computational complexity, SPH simulations typically limit the interactions between particles to a short range. Still, computing those short-ranged interactions is the most computationally intensive task in SPH simulations, typically requiring more than 90 % of the total runtime. Because these interactions can also be computed in parallel, SPH is well suited for parallel processors such as GPUs. However, the performance can be enhanced further by using GPU specific optimization techniques.
In this paper, we investigate how to efficiently compute those short-ranged interactions of particles in SPH. For this purpose, starting from a basic linked cell approach, we iteratively evaluate several different optimization techniques for the kernels, namely removal of the xloop, decreasing the cell size, simplification of the cell-sphere interaction test, fast forwarding of particles, and temporary Verlet lists. Our main goals are the improvement of the data parallelism and the reduction of the overhead of the grid traversal. The final implementation achieves both goals and yields a significant speedup compared to the basic approach.

Further data

Item Type: Conference item (Speech)
Refereed: Yes
Additional notes: Book of Abstracts: doi:10.13140/RG.2.2.21647.48806
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
000 Computer Science, information, general works > 004 Computer science
Date Deposited: 10 Dec 2019 14:12
Last Modified: 10 Dec 2019 14:12
URI: https://eref.uni-bayreuth.de/id/eprint/40794