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开源软件名称:cpmech/gosl开源软件地址:https://github.com/cpmech/gosl开源编程语言:Go 79.8%开源软件介绍:Gosl - Go scientific libraryGosl 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 existing 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. InstallationBecause of the 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 minutes. Furthermore, it works on Windows, Linux, and macOS out of the box. Containerized
Done. And your system will "remain clean." Debian/Ubuntu GNU LinuxFirst, install Go as explained in https://golang.org/doc/install Second, install some libraries:
Finally, download and compile Gosl:
Done. Installation completed. DocumentationGosl includes the following essential packages:
Gosl includes the following main packages:
(see each subdirectory for more information) For the sake of maintenance (see next section), we have removed the previous Previous versionThe previous version, including more packages, is available here and can be used with the Docker image 1.1.3 as in this hello gosl example. These other packages, such as machine learning, plotting, etc., have been removed because they do not depend on CGO and may be developed independently. We can now maintain the core of Gosl more efficiently, which has a focus on the foundation for other scientific code. |
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