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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Linear algebra, eigenvalues, FFT, Bessel, elliptic, orthogonal polys, geometry, NURBS, numerical quadrature, 3D transfinite interpolation, random numbers, Mersenne twister, probability distributions, optimisation, differential equations.
| Date | Stars |
|---|---|
| 2026-07-24 | 1877 |
| 2026-07-25 | 1877 |
| 2026-07-28 | 1876 |
| 2026-07-30 | 1876 |
| 2026-08-06 | 1876 |
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# Gosl - Go scientific library [](https://pkg.go.dev/github.com/cpmech/gosl) [](https://goreportcard.com/report/github.com/cpmech/gosl) [](https://github.com/avelino/awesome-go) Gosl is a set of tools for developing scientific simulations using the Go language. We mainly consider the development of numerical methods and solvers for differential equations. We also present some functions for fast Fourier transforms, the generation of random numbers, probability distributions, and computational geometry. This library contains essential functions for linear algebra computations (operations between all combinations of vectors and matrices, eigenvalues and eigenvectors, linear solvers) and the development of numerical methods (e.g., numerical quadrature). We link Gosl with existing libraries written in C and Fortran, such as OpenBLAS, LAPACK, UMFPACK, MUMPS, QUADPACK, and FFTW3. These libraries have been fundamental for the development of high-performant simulations over many years. We believe that it is nearly impossible to rewrite these libraries in native Go and achieve the same speed delivered by them. For reference, a naive implementation of matrix-matrix multiplication in Go is more than 100 times slower than OpenBLAS. ## Installation Because of the other libraries, Docker is the easiest way to work with Gosl. Having Docker and VS Code installed, you can start developing powerful numerical simulations using Gosl in a matter of minutes. Furthermore, it works out of the box on Windows, Linux, and MacOS. ### Containerized 1. Install Docker 2. Install Visual Studio Code 3. Install the Remote Development extension for VS Code 4. Clone https://github.com/cpmech/hello-gosl 5. Create your application within a container (see gif below) Done. And your system will "remain clean."  ### Debian/Ubuntu GNU Linux First, install Go as explained in https://golang.org/doc/install Second, install some libraries: ``` sudo apt-get install \ gcc \ gfortran \ libfftw3-dev \ liblapacke-dev \ libmetis-dev \ libmumps-seq-dev \ libopenblas-dev \ libsuitesparse-dev ``` Finally, download and compile Gosl: ``` git clone https://github.com/cpmech/gosl.git cd gosl ./all.bash ``` Done. Installation completed. ## Documentation Gosl includes the following _essential_ packages: - [chk](https://github.com/cpmech/gosl/tree/master/chk). To check numerical results and for unit testing - [io](https://github.com/cpmech/gosl/tree/master/io). Input/output, including printing to the terminal and handling files - [utl](https://github.com/cpmech/gosl/tree/master/utl). To generate series (e.g., linspace) and other functions as in pylab/matlab/octave - [la](https://github.com/cpmech/gosl/tree/master/la). Linear Algebra: vector, matrix, efficient sparse solvers, eigenvalues, decompositions Gosl includes the following _main_ packages: - [fun](https://github.com/cpmech/gosl/tree/master/fun). Special functions, DFT, FFT, Bessel, elliptical integrals, orthogonal polynomials, interpolators - [gm](https://github.com/cpmech/gosl/tree/master/gm). Geometry algorithms and structures - [hb](https://github.com/cpmech/gosl/tree/master/hb). Pseudo hierarchical binary (hb) data file format - [num](https://github.com/cpmech/gosl/tree/master/num). Fundamental numerical methods such as root solvers, non-linear solvers, numerical derivatives, and quadrature - [ode](https://github.com/cpmech/gosl/tree/master/ode). Solvers for ordinary differential equations - [opt](https://github.com/cpmech/gosl/tree/master/opt). Numerical optimization: Interior Point, Conjugate Gradients, Powell, Grad Descent - [pde](https://github.com/cpmech/gosl/tree/master/pde). Solvers for partial diff
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guoguangwu · China
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:d5c3a8457e025ed5, topic:scientific-computing