$\texttt{Aether.jl}$ : A High-Performance 3D MHD and Multifluid Dust Code Written in a Dynamic Language with an Interactive Human-AI Development Framework
Year: 2026
Type: preprint
Abstract: We present $\texttt{Aether}$, a new finite-volume code for compressible hydrodynamics and magnetohydrodynamics, written in Julia and primarily designed for GPU systems. The code solves the MHD equations with constrained transport in Cartesian, cylindrical, and spherical-polar coordinates, using standard high-order Godunov methods. An arbitrary number of dust fluids can be coupled to the gas through stiff mutual drag. It was developed from scratch with interactive Human-coding agent workflow; the paper documents the framework of this workflow alongside the numerical methods. Performance-critical kernel is written through $\texttt{KernelAbstractions}$, and supports runs on CPUs and GPUs from multiple vendors. $\texttt{Aether}$ can be ran either from an interactive notebook or batch scripts, keeping prototyping, production runs, and analysis in a single language. We verify the implementation through a series of hydrodynamic, MHD, and dust tests. Although written in a dynamic language, $\texttt{Aether}$ achieves comparable or even higher single-GPU throughput than C++ code on the same hardware. In weak scaling on Frontier, parallel efficiency stays above $93\%$S on 4096 GCDs. These results show that a dynamic language now supports production astrophysical MHD simulations on exascale systems. $\texttt{Aether}$ and its Jupyter notebook example suite are publicly available.
Source: arXiv (Cornell University)
Author: Ho, Ka Wai
Subfield: Hardware and Architecture
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funders: National Science Foundation, U.S. Department of Energy, National Energy Research Scientific Computing Center, Office of Science, Kavli Institute for Theoretical Physics, University of California, Santa Barbara, Advanced Scientific Computing Research, Oak Ridge National Laboratory, Los Alamos National Laboratory
Awards: G122673668, G1286236842, G1677143136, G1799333409, G1863003419, G3083819904, G3136028036, G3398237449, G3822735581, G419881185, G42916606, G4501827968, G4689434848, G498139845, G5076365615, G5833267439, G660579501, G6652958823, Kavli Institute for Theoretical Physics, G8437677540, G969889393
OpenAlex ID: W7203600947
Cites:
Cited by:
Related to: