Starred repositories
An open source thermodynamic modeling package completed on behalf of NASA. The Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) package offers a MATLAB/Simulink toolbox that …
Solver for strain-gradient crystal (visco-)plasticity with cohesive grain boundaries
FEniCSx-based topology optimization supporting parallel computing
A modular RTOS microkernel with tutorials—built for embedded systems, teaching, and architecture research.
A python library for simulating field theories with topological defects
An electromagnetic field computation program
🦐 Electromagnetic Simulation + Automatic Differentiation
Wavelet Neural Operator for solving parametric partialdifferential equations in computational mechanics problems
Important concepts in numerical linear algebra and related areas
OpenRadioss is a powerful, industry-proven finite element solver for dynamic event analysis
🚀 One-stop solution for creating your digital avatar from chat history 💡 Fine-tune LLMs with your chat logs to capture your unique style, then bind to a chatbot to bring your digital self to life. …
A GPU-friendly materials library with a focus on crystal plasticity methods
Cellular automata code for alloy nucleation and solidification written with Kokkos
A CAD viewer component based on three.js
💿 CD Content ( Source Code ) Collection of Book <GPU Gems > 1~ 3 | 《GPU精粹》 1~ 3 随书CD（源代码）珍藏
Task-based fast multipole method, parallelized using OpenMP and StarPU. With StarPU it supports multiple GPUs (CUDA).
GPU implementation of collision detection via spatial subdivision
A 3D electromagnetic FDTD simulator written in Python with optional GPU support
PyTorch-RBniCSx-FEniCSx based open source library for deep learning based reduced order modelling
About Code Release for "Solving High-Dimensional PDEs with Latent Spectral Models" (ICML 2023), https://arxiv.org/abs/2301.12664
PyRolL rolling simulation framework - core library.
Open source lap time simulator coded in MATLAB.
Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs)