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# DISCONTINUATION OF PROJECT # This project will no longer be maintained by Intel. Intel has ceased development and contributions including, but not limited to, maintenance, bug fixes, new releases, or updates, to this project. Intel no longer accepts patches to this project. ******************************* Numba with patches for numba-dppy*******************************

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Patches for numba-dppy

See https://github.com/IntelPython/numba-dppy. If numba-dppy package is installed this version of Numba provides additional features. Without numba-dppy package this version of Numba works like original Numba.

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: https://numba.pydata.org

Supported Platforms

  • Operating systems and CPUs:
    • Linux: x86 (32-bit), x86_64, ppc64le (POWER8 and 9), ARMv7 (32-bit), ARMv8 (64-bit)
    • Windows: x86, x86_64
    • macOS: x86_64, (M1/Arm64, unofficial support only)
    • *BSD: (unofficial support only)
  • (Optional) Accelerators and GPUs:
    • NVIDIA GPUs (Kepler architecture or later) via CUDA driver on Linux, Windows, macOS (< 10.14)
    • AMD GPUs via ROCm driver on Linux

Dependencies

  • Python versions: 3.7-3.9
  • llvmlite 0.36.*
  • NumPy >=1.15 (can build with 1.11 for ABI compatibility)

Optionally:

  • SciPy >=1.0.0 (for numpy.linalg support)

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: https://numba.readthedocs.io/en/stable/user/installing.html

Documentation

https://numba.readthedocs.io/en/stable/index.html

Mailing Lists

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

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

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NumPy aware dynamic Python compiler using LLVM

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