Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs)

A framework for high-performance domain decomposition methods.

Decomposed Optimization Time Integration (DOT) is a domain-decomposed optimization method for fast, reliable simulation of deformation dynamics. DOT efficiently converges with frame-rate time-steps across a wide range of extreme conditions.

DDC is a discrete domain computation library.

Code for training and inferring acoustic wave propagation in 3D

bzCompute is a computation graph library with built-in support for domain-decomposition and prallel computation. The library can be used for expressing and executing large number of mathematical and text-processing operations using Data-Flow graphs, (Educational version of tensorflow), written in pure python code with numpy support.

Python Library for rectangular decomposition of 2D binary images. Useful for ARD(Adaptive Rectangular Decomposition) sound simulation. 🐍 📦

GPU-accelerated rectangular decomposition for sound propagation modeling ⚡ 📦

A Robust Algebraic Domain Decomposition Preconditioner For Sparse Normal Equations

Photoelectrochemical Solar Cell Simulator in 1D

Repository for testing asynchronous schwarz methods.

Mortar3D.jl is a Julia package to calculate discrete projections between non-conforming finite element mesheds. The resulting "mortar matrices" can be used to tie non-conforming finite element meshes together which are meshed separately to construct bigger models.

Fluid flow simulator using MFEM and multiscale space-time sub-domains.

Decompose 2D/3D structured meshes between multiple MPI processes in a pencil-like manner

Robin-type Domain Decomposition

Photoelctrochemical Solar Cell Simulator

Finite and boundary element methods on Python

A two-dimensional domain decomposition using MPI to communicate and reduce matrix & array computations in the equation y=Ax.

A Multilevel Schwarz Preconditioner Based on a Hierarchy of Coarse Spaces

Domain decomposition learning algorithms for elliptic boundary value problems, with focus on the classical Dirichlet-Neumann and Robin-Robin algorithms.