Analysis of impact of general-purpose graphics processor units in supersonic flow modeling

被引:10
|
作者
Emelyanov, V. N. [1 ]
Karpenko, A. G. [2 ]
Kozelkov, A. S. [3 ]
Teterina, I. V. [1 ]
Volkov, K. N. [4 ]
Yalozo, A. V. [3 ]
机构
[1] Balt State Tech Univ, Fac Rocket & Space Engn, St Petersburg 190005, Russia
[2] St Petersburg State Univ, Fac Math & Mech, St Petersburg 198504, Russia
[3] Russian Fed Nucl Ctr, Russian Res Inst Expt Phys, Sarov 607188, Russia
[4] Kingston Univ, Fac Sci Engn & Comp, London SW15 3DW, England
基金
俄罗斯基础研究基金会;
关键词
Supersonic flow; Shock tube; Boundary layer; CFD; High-performance computing; Parallel algorithm; Speedup; PRANDTL-MEYER WAVE; GAS-DYNAMICS; LOGOS CODE; SIMULATIONS; COMBUSTION; ENGINES; DETONATION; HARDWARE; SCHEMES; GPUS;
D O I
10.1016/j.actaastro.2016.10.039
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
Computational methods are widely used in prediction of complex flowfields associated with off-normal situations in aerospace engineering. Modern graphics processing units (GPU) provide architectures and new programming models that enable to harness their large processing power and to design computational fluid dynamics (CFD) simulations at both high performance and low cost. Possibilities of the use of GPUs for the simulation of external and internal flows on unstructured meshes are discussed. The finite volume method is applied to solve three-dimensional unsteady compressible Euler and Navier Stokes equations on unstructured meshes with high resolution numerical schemes. CUDA technology is used for programming implementation of parallel computational algorithms. Solutions of some benchmark test cases on GPUs are reported, and the results computed are compared with experimental and computational data. Approaches to optimization of the CFD code related to the use of different types of memory are considered. Speedup of solution on GPUs with respect to the solution on central processor unit (CPU) is compared. Performance measurements show that numerical schemes developed achieve 20-50 speedup on GPU hardware compared to CPU reference implementation. The results obtained provide promising perspective for designing a GPU-based software framework for applications in CFD.
引用
收藏
页码:198 / 207
页数:10
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