Topic: 97th NIA CFD Seminar: Development and Implementation of Reconstructed Discontinuous Galerkin Methods for Computational Fluid Dynamics on GPUs
Date: Tuesday, January 30, 2018
Time: 11am-noon (EST)
Room: NIA, Rm137
Speaker: Jialin Lou
Abstract: The objective of the effort presented in this work is to port an unstructured CFD solver, reconstructed discontinuous Galerkin flow solver (RDGFLO), onto GPU platform using OpenACC. The solver is based on a third-order hierarchical Weighted Essentially Non-Oscillatory (WENO) reconstructed DG methods. By taking advantages of the OpenACC parallel programming model, the presented scheme requires the minimum code intrusion and algorithm alteration to upgrade a legacy CFD solver without much extra time and effort in programming, resulting in a unified portable code for both CPU and GPU platforms. A number of inviscid and viscous flow problems are presented to verify the implementation of the developed schemes on the GPU. Strong scaling tests are carried out to compare the unit running time on single GPU and single CPU to obtain the speedup factor of the developed methods. Also, weak scaling tests are used for several cases to test the parallel efficiency for multi-GPU computing by comparing the unit running time with different number of GPU cards for an approximately fixed problem size per GPU card. The results of timing measurements indicate that this OpenACC-based parallel scheme is able to significantly accelerate the solving procedure for the equivalent legacy CPU code.
Bio: Dr. Jialin Lou earned his B.S. degree in Engineering Mechanics at Beijing Institute of Technology and M.S. and Ph.D. degree from North Carolina State University under Dr. Hong Luo’s advice. He recently joined Old Dominion University Research Foundation as a post-doctoral research associate, working with Dr. Nail Yamaleev in Mathematics and Statistics Department. His research interest lies in high order numerical methods, hyperbolic diffusion schemes, and High Performance Computer (HPC) parallel computing in both CPU and GPU platforms.