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 but 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 existent libraries written in C and Fortran, such as OpenBLAS, LAPACK, UMFPACK, MUMPS, QUADPACK and FFTW3. These existent 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 at the same time achieve the same speed delivered by them. Just for reference, a naive implementation of matrix-matrix multiplication in Go is more than 100 times slower than OpenBLAS.

Because of CGO and other libraries, the easiest way to work with Gosl is via Docker. Having Docker and VS Code installed, you can start developing powerful numerical simulations using Gosl in a matter of seconds. Furthermore, the best part of it is that it works on Windows, Linux, and macOS out of the box.

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 own application within a container (see gif below)

Done. And your system will remain "clean."

Because we use CGO for linking Gosl with many libraries, we cannot use the so convenient go get functionality for installing Gosl. Moreover, we view Gosl as the most basic set of libraries for high-performance computing and therefore prefer to install Gosl directly alongside Go. In other words, Gosl extends Go with powerful tools for scientific simulations.

Gosl is then linked to WHEREVER_GO_IS_LOCATED/src/gosl; e.g. /usr/local/go/src/gosl. We have experimented with GOPATH and the newer Go Modules approach, but both do not work well with CGO (and hence Gosl).

Download and link Gosl

Assuming that your go code is located in $HOME/mygo and that go has been installed in $HOME/go:

git clone https://github.com/cpmech/gosl.git $HOME/mygo/gosl
ln -s $HOME/mygo/gosl $HOME/go/src/gosl

Install dependencies

sudo apt-get install -y --no-install-recommends \
  gcc \
  gfortran \
  libopenmpi-dev \
  libhwloc-dev \
  liblapacke-dev \
  libopenblas-dev \
  libmetis-dev \
  libsuitesparse-dev \
  libmumps-dev \
  libfftw3-dev \
  libfftw3-mpi-dev \
  libhdf5-dev

Compile Gosl

cd $HOME/mygo/gosl
bash ./all.bash

Done.

Gosl includes the following essential packages:

• chk. To check numerical results and for unit testing
• io. Input/output including printing to the terminal and handling files
• utl. To generate series (e.g. linspace) and other functions as in pylab/matlab/octave

Gosl includes the following main packages:

• fun. Special functions, DFT, FFT, Bessel, elliptical integrals, orthogonal polynomials, interpolators
• gm. Geometry algorithms and structures
• hdf. Hierarchical Data Format for very large data storage
• la. Linear Algebra: vector, matrix, efficient sparse solvers, eigenvalues, decompositions
• mpi. Message Passing Interface for parallel computing
• num. Fundamental numerical methods such as root solvers, non-linear solvers, numerical derivatives and quadrature
• ode. Solvers for ordinary differential equations
• opt. Numerical optimization: Interior Point, Conjugate Gradients, Powell, Grad Descent
• pde. Solvers for partial differential equations (FDM, Spectral, FEM)
• rnd. Random numbers and probability distributions

(see each sub directory for more information)

Pelase check out https://github.com/cpmech/gosl-examples

Pelase check out https://github.com/cpmech/gosl-benchmarks