Title: The prospect for molecular dynamics at the exascale

Molecular dynamics (MD) is one of the most powerful tools in the arsenal of computational materials scientists. While the exponential growth in available computing power has translated into proportional gains in terms of accessible simulation sizes and accuracies, similar gains have not been realized regarding simulation times, due to the breakdown of conventional domain decomposition approaches. I will review the main challenges facing the community with respect to fully realizing the promising of exascale computers and describe the progress made by the EXAALT project, funded under the DOE’s Exascale Computing Project. I will discuss advances in optimizing modern ML-based potentials for exascale architectures, in long-time simulations using parallel-in-time algorithm, and in the integration of ML workflows at scale.