A GPU–CUDA based direct simulation Monte Carlo algorithm for real gas flows

Goldsworthy, Mark

doi:10.1016/j.compfluid.2014.01.033

Cited by 28 publications

(17 citation statements)

References 10 publications

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“…Galizia et al, 2015), and to Monte Carlo simulations (e.g. Goldsworthy, 2014). Some papers have recently been published on the topic of the GPU use in heat transfer problems.…”

Section: A Brief Overview On Gpusmentioning

confidence: 99%

A rapid GPU-based heat transfer and solidification model for dynamic computer simulations of continuous steel casting

Klimeš

Stetina

2015

Journal of Materials Processing Technology

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“…Galizia et al, 2015), and to Monte Carlo simulations (e.g. Goldsworthy, 2014). Some papers have recently been published on the topic of the GPU use in heat transfer problems.…”

Section: A Brief Overview On Gpusmentioning

confidence: 99%

A rapid GPU-based heat transfer and solidification model for dynamic computer simulations of continuous steel casting

Klimeš

Stetina

2015

Journal of Materials Processing Technology

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“…Impressive acceleration and excellent multi-GPU scaling have been demonstrated by several groups using particle 25,26 and grid-based methods with structured meshes. 27,28 We have recently demonstrated double digit speedups on a single GPU 29 and good multi-GPU scaling for the DVM Boltzmann solver, the DSMC module, and the LBM solver, all using adaptive Cartesian meshes.…”

Section: Challenges Of Porting Adaptive Kinetic-fluid Codes To Cpu-gpmentioning

confidence: 99%

Adaptive kinetic-fluid solvers for heterogeneous computing architectures

Zabelok

Arslanbekov

Kolobov

2015

Journal of Computational Physics

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Abstract. We show feasibility and benefits of porting an adaptive multi-scale kinetic-fluid code to CPU-GPU systems. Challenges are due to the irregular data access for adaptive Cartesian mesh, vast difference of computational cost between kinetic and fluid cells, and desire to evenly load all CPUs and GPUs. Our Unified Flow Solver (UFS) combines Adaptive Mesh Refinement (AMR) with automatic cell-by-cell selection of kinetic or fluid solvers based on continuum breakdown criteria. Using GPUs enables hybrid simulations of mixed rarefied-continuum flows with a million of Boltzmann cells with 24x24x24 velocity mesh. We describe the implementation of CUDA kernels for three modules in UFS: the direct Boltzmann solver using discrete velocity method, the Direct Simulation Monte Carlo (DSMC) solver, and a mesoscopic solver based on Lattice Boltzmann Method, all using octree Cartesian mesh. Double digit speedups on single GPU and good scaling for multiGPUs have been demonstrated.

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“…16 The results show that DgSMC-B is in good compliance with other DSMC codes. 11,16,17 3. Simulation Case C: supersonic flow over a block A two dimensional supersonic flow over a rectangular block was investigated in this case.…”

Section: Simulation Case B: Hypersonic Flow Around a Cylinder Argonmentioning

confidence: 99%

DgSMC-B code: A robust and autonomous direct simulation Monte Carlo code for arbitrary geometries

2016

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In this paper, we describe the structure of a new Direct Simulation Monte Carlo (DSMC) code that takes advantage of combinatorial geometry (CG) to simulate any rarefied gas flows Medias. The developed code, called DgSMC-B, has been written in FORTRAN90 language with capability of parallel processing using OpenMP framework. The DgSMC-B is capable of handling 3-dimensional (3D) geometries, which is created with first-and second-order surfaces. It performs independent particle tracking for the complex geometry without the intervention of mesh. In addition, it resolves the computational domain boundary and volume computing in border grids using hexahedral mesh. The developed code is robust and selfgoverning code, which does not use any separate code such as mesh generators. The results of six test cases have been presented to indicate its ability to deal with wide range of benchmark problems with sophisticated geometries such as airfoil NACA 0012. The DgSMC-B code demonstrates its performance and accuracy in a variety of problems. The results are found to be in good agreement with references and experimental data. C 2016 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license

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A GPU–CUDA based direct simulation Monte Carlo algorithm for real gas flows

Cited by 28 publications

References 10 publications

A rapid GPU-based heat transfer and solidification model for dynamic computer simulations of continuous steel casting

A rapid GPU-based heat transfer and solidification model for dynamic computer simulations of continuous steel casting

Adaptive kinetic-fluid solvers for heterogeneous computing architectures

DgSMC-B code: A robust and autonomous direct simulation Monte Carlo code for arbitrary geometries

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