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This work deals with the CPU-GPU heterogeneous code acceleration of afinite-volume CFD solver utilizing multiple CPUs and GPUs at the same time.First, a high-level description of the CFD solver called SENSEI, thediscretization of SENSEI, and the CPU-GPU heterogeneous computing workflow inSENSEI leveraging MPI and OpenACC are given. Then, a performance model forCPU-GPU heterogeneous computing requiring ghost cell exchange is proposed tohelp estimate the performance of the heterogeneous implementation. The scalingperformance of the CPU-GPU heterogeneous computing and its comparison with thepure multi-CPU/GPU performance for a supersonic inlet test case is presented todisplay the advantages of leveraging the computational power of both the CPUand the GPU. Using CPUs and GPUs as workers together, the performance can beimproved further compared to using pure CPUs or GPUs, and the advantages can befairly estimated by the performance model proposed in this work. Finally,conclusions are drawn to provide 1) suggestions for application users who havean interest to leverage the computational power of the CPU and GPU toaccelerate their own scientific computing simulations and 2) feedback forhardware architects who have an interest to design a better CPU-GPUheterogeneous system for heterogeneous computing.

CPU-GPU Heterogeneous Code Acceleration of a Finite Volume Computational Fluid Dynamics Solver