Compiler Optimizations for Industrial Unstructured Mesh CFD Applications on GPUs

Abstract

Graphical Processing Units (GPUs) have shown acceleration factors over multicores for structured mesh-based Computational Fluid Dynamics (CFD). However, the value remains unclear for dynamic and irregular applications. Our motivating example is HYDRA, an unstructured mesh application used in production at Rolls-Royce for the simulation of turbomachinery components of jet engines. We describe three techniques for GPU optimization of unstructured mesh applications: a technique able to split a highly complex loop into simpler loops, a kernel specific alternative code synthesis, and configuration parameter tuning. Using these optimizations systematically on HYDRA improves the GPU performance relative to the multicore CPU. We show how these optimizations can be automated in a compiler, through user annotations. Performance analysis of a large number of complex loops enables us to study the relationship between optimizations and resource requirements of loops, in terms of registers and shared memory, which directly affect the loop performance.

This research is partly funded by EPSRC (grant reference numbers EP/I00677X/1, EP/I006079/1), the UK Technology Strategy Board, and Rolls Royce plc through the SILOET programme. The authors gratefully acknowledge Rolls-Royce plc for providing financial support toward this research and for giving permission to publish this paper.