Researchers at LLNL have achieved a milestone in accelerating and adding features to complex multi-physics simulations run on Graphics Processing Units (GPUs), a development that could advance high performance computing and engineering. As LLNL readies for El Capitan, the National Nuclear Security Administration’s first exascale supercomputer, the team’s efforts have centered around the development of MARBL, a next-generation multi-physics code, for GPUs. El Capitan is based on AMD’s cutting-edge MI300A Accelerated Processing Units (APUs), which combines Central Processing Units (CPUs) with GPUs and high-bandwidth memory into a single package, allowing for more efficient resource sharing. In a recent paper published by the Journal of Fluids Engineering, by harnessing the power of GPUs in El Capitan’s early access machines, the researchers successfully extended MARBL’s capabilities to include additional physics crucial for HED physics and fusion modeling. Researchers said the team’s use of performance portability abstraction layers, such as the LLNL-developed RAJA Portability Suite and the MFEM finite element discretization library were instrumental in enabling MARBL’s single source code to target multiple GPU/CPU architectures. Umpire, a programming interface that helped alleviate memory constraints on Sierra, also has helped improve codes for El Capitan. RAJA, MFEM, and Umpire are open source.