Astrophysical Particle Simulations on Heterogeneous CPU-GPU Systems

Abstract

A heterogeneous CPU-GPU node is getting popular in HPC clusters. We need to rethink algorithms and optimization techniques for such system depending on the relative performance of CPU vs. GPU. In this paper, we report a performance optimized particle simulation code "OTOO", that is based on the octree method, for heterogenous systems. Main applications of OTOO are astrophysical simulations such as N-body models and the evolution of a violent merger of stars. We propose optimal task split between CPU and GPU where GPU is only used to compute the calculation of the particle force. Also, we describe optimization techniques such as control of the force accuracy, vectorized tree walk, and work partitioning among multiple GPUs. We used OTOO for modeling a merger of two white dwarf stars and found that OTOO is powerful and practical to simulate the fate of the process.

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Cited by in corpus (3)

• Dark Matter Substructure in Numerical Simulations: A Tale of Discreteness Noise, Runaway Instabilities, and Artificial Disruption
• 24.77 Pflops on a Gravitational Tree-Code to Simulate the Milky Way Galaxy with 18600 GPUs
• The critical mass ratio of double white dwarf binaries for violent merger-induced Type Ia supernova explosions