This is the Windows app named Armadillo to run in Windows online over Linux online whose latest release can be downloaded as armadillo-9.900.1.tar.xz. It can be run online in the free hosting provider OnWorks for workstations.
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- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.
Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.
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Armadillo to run in Windows online over Linux online
DESCRIPTION
* Fast C++ library for linear algebra (matrix maths) and scientific computing* Easy to use functions and syntax, deliberately similar to Matlab
* Uses template meta-programming techniques
* Provides efficient wrappers for LAPACK, BLAS, ATLAS, ARPACK and SuperLU libraries, including high-performance versions such as OpenBLAS and Intel MKL.
* Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc.
* Downloads: http://arma.sourceforge.net/download.html
* Documentation: http://arma.sourceforge.net/docs.html
* Bug reports: http://arma.sourceforge.net/faq.html
* Git repo: https://gitlab.com/conradsnicta/armadillo-code
Features
- Easy to use - has many MATLAB like functions
- Useful for prototyping directly in C++
- Useful for conversion of research code into production environments
- Permissively licensed - can be used in proprietary software and products
- Used for machine learning, pattern recognition, computer vision, signal processing, bioinformatics, statistics, finance, etc
- Efficient classes for vectors, matrices, cubes (1st, 2nd, 3rd order tensors)
- Supports dense and sparse matrices
- Fast singular value decomposition (SVD), eigen decomposition, QR, LU, Cholesky, FFT
- Clustering using k-means and Gaussian Mixture Models (GMM)
- Automatic vectorisation of expressions (SIMD)
- Contiguous and non-contiguous submatrices
- Automatically combines several operations into one to increase speed and efficiency
- Read/write data in CSV files
- Automatically uses OpenMP for speedups
Audience
Information Technology, Science/Research, Education, Advanced End Users, Developers, Engineering
Programming Language
MATLAB, C++
This is an application that can also be fetched from https://sourceforge.net/projects/arma/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.