jaxFMM: An Adaptive, GPU-Parallel Implementation of the Fast Multipole Method in JAX

We introduce jaxFMM, an open-source, adaptive, highly parallel point-charge Fast Multipole Method implementation for the Laplace kernel written in JAX.

It is based on a non-uniform refinement strategy with on-the-fly rotation-based transforms tailored around JAX's just-in-time compiler, which results in extremely concise and simple code.

Benchmarks show that the algorithm performs well at moderate accuracies, even for highly non-uniform charge distributions.

JaxFMM already massively speeds up stray-field computations in micromagnetics and with JAX features like autodiff, novel applications such as inverse-design problems and machine-learning tasks can be tackled with ease in the future.