## Abstract

We focus on implementing and optimizing a sixth-order finite-difference solver for simulating compressible fluids on a GPU using third-order Runge-Kutta integration. Since graphics processing units perform well in data-parallel tasks, this makes them an attractive platform for fluid simulation. However, high-order stencil computation is memory-intensive with respect to both main memory and the caches of the GPU. We present two approaches for simulating compressible fluids using 55-point and 19-point stencils. We seek to reduce the requirements for memory bandwidth and cache size in our methods by using cache blocking and decomposing a latency-bound kernel into several bandwidth-bound kernels. Our fastest implementation is bandwidth-bound and integrates 343 million grid points per second on a Tesla K40t GPU, achieving a 3.6× speedup over a comparable hydrodynamics solver benchmarked on two Intel Xeon E5-2690v3 processors. Our alternative GPU implementation is latency-bound and achieves the rate of 168 million updates per second.

Original language | English |
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Pages (from-to) | 11-22 |

Journal | Computer Physics Communications |

Volume | 217 |

DOIs | |

Publication status | Published - Aug 2017 |

MoE publication type | A1 Journal article-refereed |

## Keywords

- Astrophysical applications
- Computational techniques
- Computer science and technology
- Finite difference methods in fluid dynamics
- Fluid dynamics
- Hydrodynamics