Discover the best Scientific Computing open source repositories on GitHub. Explore trending tools, live star counts, source code, and developer projects updated daily.
The fastest automatic differentiation library for C++, with Python bindings. Forward, adjoint and higher-order derivatives, checkpointing, Eigen support and JIT. Reproducible benchmarks against CppAD, Adept and autodiff.
Avogadro libraries provide 3D rendering, visualization, analysis and data processing useful in computational chemistry, molecular modeling, bioinformatics, materials science, and related areas.
MeteoInfo: GIS, scientific computation and visualization environment.
Powerful, efficient particle trajectory analysis in scientific Python.
A library that provides objects for scientific computing in PHP.
A flyweight in situ visualization and analysis runtime for multi-physics HPC simulations
Computator.NET is a special kind of numerical software that is fast and easy to use but not worse than others feature-wise. It's features include: - Real and complex functions charts - Real and complex calculator - Real functions numerical calculations including different methods - Over 107 Elementary functions - Over 141 Special functions - Over 21 Matrix functions and operations - Scripting language with power to easy computations including matrices - You can declare your own custom functions with scripting language
Insight Toolkit (ITK) -- Official Repository. ITK builds on a proven, spatially-oriented architecture for processing, segmentation, and registration of scientific images in two, three, or more dimensions.
Practical volume computation and sampling in high dimensions
Open finite element infrastructure for nonlinear computational mechanics.
High-Performance LISP-like language for Scientific Computing and AI written in C++
CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python, Matlab/Octave, Julia or Javascript
Universal components for differentiable scientific computing. :package:
GPU-capable global atmosphere model of the CliMA Earth System Model, designed for calibration with data assimilation and machine learning
GPU accelerated differentiable finite elements for solid mechanics with PyTorch
Open-source Platform for Scientific and Technical Data Processing and Visualization
RobOptim Core Layer: interface and basic mathematical tools
a rust-native Modelica compiler for fast, composable, scientific computing
Galactic Dynamics in python
:gem: Feel++: Finite Element Embedded Language and Library in C++