Multiphysics Modeling, Simulation, and Inference Software
diff-soup is a differentiable, GPU-native JAX library for solving large systems of ordinary differential equations and differential algebraic equations arising from the discretization of partial differential equations. We employ specialized numerical methods for stiff systems that utilize sparse data structures and algorithms for efficient performance.Features include:
- fully differentiable DAE solvers built on variable-step, variable-order adaptive implicit integration;
- flexible PDE domains, from structured grids for regular geometries to unstructured meshes for irregular ones;
- full compatibility with JAX’s automatic differentiation, jit compilation, and vmap batching primitives;
- sparse direct linear algebra that stays on the GPU (cuDSS), with KLU, SuperLU_MT, and dense backends on CPU;
- optimization, data assimilation, and uncertainty quantification built on the differentiable solve.
diff-soup is hosted on GitHub: https://github.com/stmorgenstern/diff-soup
(Courtesy of Sam Degnan-Morgenstern)