Relexi — A scalable open source reinforcement learning framework for high-performance computing
Marius Kurz, Philipp Offenhäuser, Dominic Viola, Michael Resch, Andrea Beck · Software Impacts · 2022
Relexi is an open source reinforcement learning (RL) framework written in Python and based on TensorFlow’s RL library TF-Agents. Relexi allows to employ RL for environments that require computationally intensive simulations like applications in computational fluid dynamics. For this, Relexi couples legacy simulation codes with the RL library TF-Agents at scale on modern high-performance computing (HPC) hardware using the SmartSim library. Relexi thus provides an easy way to explore the potential of RL for HPC applications.