gosl
A comprehensive Go scientific library for numerical simulations, linear algebra, differential equations, and computational geometry.
What is gosl?
Gosl is a Go scientific library designed for developing numerical simulations and solvers for differential equations. It provides essential functions for linear algebra, numerical methods, special functions, and computational geometry, focusing on high performance by linking with established C and Fortran libraries like OpenBLAS and LAPACK.
Researchers, engineers, and developers working on scientific computing, numerical simulations, and differential equation solvers who want to leverage Go's simplicity while maintaining high computational performance.
Gosl offers a unique combination of Go's developer-friendly ecosystem with the raw performance of battle-tested C/Fortran numerical libraries, making it ideal for building efficient scientific simulations without sacrificing productivity.
Overview
Linear algebra, eigenvalues, FFT, Bessel, elliptic, orthogonal polys, geometry, NURBS, numerical quadrature, 3D transfinite interpolation, random numbers, Mersenne twister, probability distributions, optimisation, differential equations.
Use Cases
Best For
- Developing numerical solvers for ordinary and partial differential equations
- High-performance linear algebra computations in Go applications
- Implementing spectral methods and finite element analysis
- Scientific simulations requiring FFT, Bessel functions, or orthogonal polynomials
- Computational geometry and 3D interpolation tasks
- Generating random numbers and probability distributions for simulations
Not Ideal For
- Projects requiring simple, dependency-free installation without Docker or system-level libraries
- Teams that need pure Go solutions to avoid CGO-related build and portability issues
- Applications relying on integrated plotting or machine learning features, which were removed in recent versions
Pros & Cons
Pros
Leverages proven C and Fortran libraries like OpenBLAS and LAPACK, ensuring computational efficiency that naive Go implementations cannot match, as the README states naive Go matrix multiplication is over 100 times slower.
Provides a developer-friendly Go interface for complex numerical methods, abstracting the underlying C/Fortran libraries to simplify usage for Go programmers.
Includes essential packages for linear algebra, differential equations, FFT, and geometry, covering a wide range of scientific computing needs from the README's listed features.
Offers Docker-based setup that works out of the box on multiple platforms, as highlighted in the installation guide, making it easier to start without system-level configurations.
Cons
Native installation requires manually installing multiple system libraries like FFTW3 and MUMPS on Debian/Ubuntu, which can be error-prone and less straightforward on other operating systems.
Relies on CGO to interface with external libraries, introducing potential build issues, portability challenges, and compatibility problems compared to pure Go codebases.
Recent versions removed packages such as machine learning and plotting for maintenance, narrowing the library's focus and forcing users to seek external solutions for those features.
Frequently Asked Questions
Related Projects
gonumGonum is a set of numeric libraries for the Go programming language. It contains libraries for matrices, statistics, optimization, and more
statsA well tested and comprehensive Golang statistics library package with no dependencies.
plotA repository for plotting and visualizing data
streamtoolstools for working with streams of data
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