ZEFR: A GPU-accelerated high-order solver for compressible viscous flows using the flux reconstruction method

In this work we present ZEFR, a GPU accelerated flow solver based around the high-order accurate flux reconstruction (FR) approach. Written in a combination of C++ and CUDA, ZEFR is designed to perform scale resolving simulations within the vicinity of complex geometrical configurations. A unique feature of ZEFR is its support for overset grids; a feature which greatly expands the addressable problem space compared with existing high-order codes. The C++ implementation of FR in a manner which is suitable for modern hardware platforms is described in detail. Additionally, an overview of the input deck used by ZEFR is included. Validation results are presented for a range of steady and unsteady flow problems including Couette flow, the Taylor-Green vortex, and flow around an SD7003 airfoil. Single node performance on a NVIDIA V100 GPU is analyzed where it is shown that all of the kernels in ZEFR attain a high proportion of peak memory bandwidth. Moreover, multi-node performance is also assessed with strong scalability being demonstrated from 60 to 3840 NVIDIA V100 GPUs. Program summary Program title: ZEFR v1.0 Program files doi: http://dx.doi.org/10.17632/wzy83bscxd.1 Licensing provisions: BSD 3-clause Programming language: C++ and CUDA External routines/libraries: Eigen, HDF5, METIS, MPI, and TIOGA. Nature of problem: Compressible Euler and Navier-Stokes equations. Solution method: High-order direct flux reconstruction approach suitable for curved, mixed, unstructured grids. Unusual features: Code incorporates support for overset grids. (C) 2020 Elsevier B.V. All rights reserved.