Heterogeneous CPU/GPU co-execution of CFD simulations on the POWER9 architecture: Application to airplane aerodynamics

Abstract

High fidelity Computational Fluid Dynamics simulations are generally associated with large computing requirements, which are progressively acute with each new generation of supercomputers. However, significant research efforts are required to unlock the computing power of leading-edge systems, currently referred to as pre-Exascale systems, based on increasingly complex architectures. In this paper, we present the approach implemented in the computational mechanics code Alya. We describe in detail the parallelization strategy implemented to fully exploit the different levels of parallelism, together with a novel co-execution method for the efficient utilization of heterogeneous CPU/GPU architectures. The latter is based on a multi-code co-execution approach with a dynamic load balancing mechanism. The assessment of the performance of all the proposed strategies has been carried out for airplane simulations on the POWER9 architecture accelerated with NVIDIA Volta V100 GPUs.

References in corpus (2)

• PT-Scotch: A tool for efficient parallel graph ordering
• MPI+X: task-based parallelization and dynamic load balance of finite element assembly

Cited by in corpus (5)

• Multi-GPU implementation of a time-explicit finite volume solver for the Shallow-Water Equations using CUDA and a CUDA-Aware version of OpenMPI
• Dynamic resource allocation for efficient parallel CFD simulations
• An FPGA cached sparse matrix vector product (SpMV) for unstructured computational fluid dynamics simulations
• Optimized thread-block arrangement in a GPU implementation of a linear solver for atmospheric chemistry mechanisms
• Performance assessment of CUDA and OpenACC in large scale combustion simulations