The Julia Programming Language

Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.

Multi-dimensional arrays (tensors) and numerical definitions for Elixir

Python interface to GPU-powered libraries

Fixed point math C# library

Pandas port for C# and F#, data analysis tool, process multi-dim array in DataFrame.

Wide-Integer implements a generic C++ template for uint128_t, uint256_t, uint512_t, uint1024_t, etc.

开源Go语言数值算法库(An open numerical library purely based on Go programming language)

Repository for the Parallel Ice Sheet Model (PISM)

NRPy+, BlackHoles@Home, SENRv2, and the NRPy+ Jupyter Tutorial: Python-Based Code Generation for Numerical Relativity... and Beyond!

☔ Implementations of mathematical functions, formulas and concepts

Solve Fractional Differential Equations using high performance numerical methods

String helper methods and an inflector

Setuptools-based `setup.py` template for Cython projects

Numerical signals based Log To Graph Converter

FractionalCalculus.jl: A Julia package for high performance, comprehensive and high precision numerical fractional calculus computing.

Forlab is a Fortran module that provides a lot of functions for scientific computing mostly inspired by Matlab and Python's package NumPy.

A numerical integrator written in Elixir for the solution of sets of non-stiff ordinary differential equations (ODEs).

NLA course in OZON Masters

.NET bindings for native numerical computing