Accelerated Generic Numerical Library for Science and Machine Learning (see other projects at https://github.com/libmir)
D Makefile
Latest commit 95ce39b Dec 18, 2016 @9il 9il committed on GitHub Update README.md

README.md

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Latest version

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Benchmarks

❗️ Mir GLAS was moved to https://github.com/libmir/mir-glas.

Mir

Generic Numerical Library for Science and Machine Learning.

Other Mir Projects
Open Source Projects based on Mir

Documentation

Documentation API can be found here. Read also the Mir blog.

Contents

  • mir.glas - Generic Linear Algebra Subroutines
  • mir.ndslice Multidimensional Random Access Ranges and Arrays
  • mir.sparse Sparse Tensors
    • Sparse - DOK format
    • Different ranges for COO format
    • CompressedTensor - CSR/CSC formats
  • mir.sparse.blas - Sparse BLAS for CompressedTensor
  • mir.model.lda.hoffman - Online variational Bayes for latent Dirichlet allocation (Online VB LDA) for sparse documents. LDA is used for topic modeling.
  • mir.combinatorics Combinations, combinations with repeats, cartesian power, permutations.

Compatibility

LDC (LLVM D Compiler)
  • >=1.1.0-beta6
DMD
  • >=2.072
Linux Mac OS X Windows
64-bit Build Status Build Status Build status
32-bit Build Status N/A N/A

Fast setup with the dub package manager

Latest version

Dub is the D's package manager. You can create a new project with:

dub init <project-name>

Now you need to edit the dub.json add mir as dependency.

{
    ...
    "dependencies": {
        "mir": "~><current-version>"
    },
    "dflags-ldc": ["-mcpu=native"]
}

Now you can create an app.d file in the source folder and run your code with

dub --compiler=ldmd2

Flag --build=release and can be added for a performance boost:

dub --compiler=ldmd2 --build=release

ldmd2 is a shell on top of LDC (LLVM D Compiler).

"dflags-ldc": ["-mcpu=native"] allows LDC to optimize Mir for your CPU.

Contributing

See our TODO List. Mir is very young and we are open for contributing to source code, documentation, examples and benchmarks.

Notes