Multi-GPU acceleration of direct pore-scale modeling of fluid flow in natural porous media
- 作者：Saeed Ovaysi ; sovaysi@uwyo.edu ; Mohammad Piri mpiri@uwyo.edu
- 关键词：GPU computing ; Parallel programming ; Moving Particle Semi-implicit ; Particle-based methods ; Porous media ; MMPS
- 刊名：Computer Physics Communications
- 出版年：2012
- 期刊代码：30_00104655
- 类别：cp
- 出版时间：September, 2012
- 卷：183
- 期：9
- 页码：1890-1898
- 文件大小：1745 K
摘要
Modified Moving Particle Semi-implicit (MMPS) is a particle-based method used to simulate pore-scale fluid flow through disordered porous media. We present a multi-GPU implementation of MMPS for hybrid CPU-GPU clusters using NVIDIA鈥檚 Compute Unified Device Architecture (CUDA). Message Passing Interface (MPI) functions are used to communicate between different nodes of the cluster and hence their respective GPUs. The accuracy and stability of the GPU implementation of MMPS are verified through careful comparison with the results obtained on conventional CPU-only clusters. We then examine the speedup and scalability of the GPU implementation for pore-scale flow simulations in samples with various sizes taken from the same natural porous system. We achieve a speedup with 60 graphics cards compared to 6 CPU cores while maintaining a linear scalability. Incompressible fluid flow simulation to reach steady-state through a 1聽mm脳1聽mm脳8聽mm microtomography image of Bentheimer sandstone is also performed in less than 1聽h.