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Armadillo download for Windows

Free download Armadillo Windows app to run online win Wine in Ubuntu online, Fedora online or Debian online

This is the Windows app named Armadillo whose latest release can be downloaded as armadillo-12.6.5.tar.xz. It can be run online in the free hosting provider OnWorks for workstations.

Download and run online this app named Armadillo with OnWorks for free.

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- 6. Download the application and install it.

- 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.




* Fast C++ library for linear algebra (matrix maths) and scientific computing
* Easy to use functions and syntax, deliberately similar to Matlab / Octave
* Uses template meta-programming techniques to increase efficiency
* Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries
* 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


  • 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 acceleration via multi-threading
  • Used for speeding up NumPy / Python via CARMA: https://github.com/RUrlus/carma
  • Used for machine learning and pattern recognition by MLPACK: https://mlpack.org/
  • Used for numerical optimisation by Ensmallen: https://ensmallen.org/


Information Technology, Science/Research, Education, Advanced End Users, Developers, Engineering

Programming Language



Algorithms, Mathematics, Machine Learning, Computer Vision Libraries

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.

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