Multi-GPU thermal lattice Boltzmann simulations using OpenACC and MPI

We assess the performance of the hybrid Open Accelerator (OpenACC) and Message Passing Interface (MPI) approach for multi-graphics processing units (GPUs) accelerated thermal lattice Boltzmann (LB) simulation. The OpenACC accelerates computation on a single GPU, and the MPI synchronizes the information between multiple GPUs. With a single GPU, the two-dimension (2D) simulation achieved 1.93 billion lattice updates per second (GLUPS) with a grid number of 81932, and the three-dimension (3D) simulation achieved 1.04 GLUPS with a grid number of 3853, which is more than 76% of the theoretical maximum performance. On multi-GPUs, we adopt block partitioning, overlapping communications with computations, and concurrent computation to optimize parallel efficiency. We show that in the strong scaling test, using 16 GPUs, the 2D simulation achieved 30.42 GLUPS and the 3D simulation achieved 14.52 GLUPS. In the weak scaling test, the parallel efficiency remains above 99% up to 16 GPUs. Our results demonstrated that, with improved data and task management, the hybrid OpenACC and MPI technique is promising for thermal LB simulation on multi-GPUs. (c) 2022 Elsevier Ltd. All rights reserved.

Automated summary

This study evaluates the performance of a hybrid OpenACC and MPI approach for multi-GPUs accelerated thermal LB simulation. OpenACC is used to accelerate computation on a single GPU, while MPI synchronizes information between multiple GPUs. The results show promising performance improvement with single GPU achieving 1.93 billion GLUPS for 2D simulation and 1.04 GLUPS for 3D simulation. With 16 GPUs, the parallel efficiency remains high, reaching 30.42 GLUPS for 2D simulation and 14.52 GLUPS for 3D simulation.