Skip to content
/ numba Public
forked from numba/numba

NumPy aware dynamic Python compiler using LLVM

License

Notifications You must be signed in to change notification settings

shssf/numba

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Numba

Gitter

A Just-In-Time Compiler for Numerical Functions in Python

Numba is an open source, NumPy-aware optimizing compiler for Python sponsored by Anaconda, Inc. It uses the LLVM compiler project to generate machine code from Python syntax.

Numba can compile a large subset of numerically-focused Python, including many NumPy functions. Additionally, Numba has support for automatic parallelization of loops, generation of GPU-accelerated code, and creation of ufuncs and C callbacks.

For more information about Numba, see the Numba homepage: http://numba.pydata.org

Dependencies

  • llvmlite
  • NumPy (version 1.9 or higher)
  • funcsigs (for Python 2)

Supported Platforms

  • Operating systems and CPU:
    • Linux: x86 (32-bit), x86_64, ppc64le (POWER8 and 9), ARMv7 (32-bit), ARMv8 (64-bit)
    • Windows: x86, x86_64
    • macOS: x86_64
  • Python versions: 2.7, 3.5-3.7
  • NumPy: >= 1.11
  • NVIDIA GPUs (Kepler architecture or later) via CUDA driver on Linux, Windows, macOS (< 10.14)
  • AMD GPUs via ROCm driver on Linux

Installing

The easiest way to install Numba and get updates is by using the Anaconda Distribution: https://www.anaconda.com/download

$ conda install numba

For more options, see the Installation Guide: http://numba.pydata.org/numba-doc/latest/user/installing.html

Documentation

http://numba.pydata.org/numba-doc/latest/index.html

Mailing Lists

Join the Numba mailing list [email protected]: https://groups.google.com/a/continuum.io/d/forum/numba-users

Some old archives are at: http://librelist.com/browser/numba/

Continuous Integration

Travis CI Azure Pipelines

About

NumPy aware dynamic Python compiler using LLVM

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Python 89.2%
  • C 8.6%
  • Jupyter Notebook 1.4%
  • C++ 0.6%
  • Shell 0.1%
  • Batchfile 0.1%