Anders Johansson
I am a PhD student in Applied Physics in the group of Boris Kozinsky at Harvard SEAS. My focus is on machine learning interatomic potentials for molecular dynamics simulations, in particular on how to make them fast on modern hardware architecture and large supercompters.
GitHub: @anjohan
Sessions
Allegro and FLARE are two very different packages for constructing machine learning potentials that are fast, accurate, and suitable for extreme-scale molecular dynamics simulations. Allegro uses PyTorch for efficient equivariant potentials with state-of-the-art accuracy, while FLARE is a sparse Gaussian process potential with an optimized C++ training backend leveraging Kokkos, OpenMP, and MPI for state-of-the-art performance, and a user-friendly Python frontend. We will compare and contrast the two methods, discuss lessons learned, and show spectacular scientific applications.