Performance Portable Gpu Acceleration of a High-Order Finite Element Multiphysics Application

The Lawrence Livermore National Laboratory (LLNL) will soon have in place the El Capitan exascale supercomputer, based on AMD GPUs. As part of a multiyear effort under the NNSA Advanced Simulation and Computing (ASC) program, we have been developing MARBL, a next generation, performance portable multiphysics application based on high-order finite elements. In previous years, we successfully ported the Arbitrary Lagrangian-Eulerian (ALE), multi-material, compressible flow capabilities of MARBL to NVIDIA GPUs as described in [1]. In this paper, we describe our ongoing effort in extending MARBL's GPU capabilities with additional physics, including multi-group radiation diffusion and thermonuclear burn for high energy density physics (HEDP) and fusion modeling. We also describe how our portability abstraction approach based on the RAJA Portability Suite and the MFEM finite element discretization library has enabled us to achieve high performance on AMD based GPUs with minimal effort in hardware-specific porting. Throughout this work, we highlight numerical and algorithmic developments that were required to achieve GPU performance.