Numba – Speed up Applications with High Performance Functions

Numba is a compiler for Python array and numerical functions that gives you the power to speed up your applications with high performance functions written directly in Python. Array-oriented and math-heavy Python code can be just-in-time optimized to performance similar as C, C++ and Fortran.

Numba uses the LLVM compiler infrastructure to compile Python to CPU and GPU machine code.

Numba needs llvmite, NumPy, and funcsigs. It’s compatible with Python 2.7 and 3.5 or later, and Numpy versions 1.7 to 1.14.

Features include:

  • Speeds up operations written in Python.
  • On-the-fly code generation (at import time or runtime, at the user’s preference).
  • Native code generation for the CPU (default) and GPU hardware. It offers an efficient GPU code reduction algorithm for faster compilation.
  • Integration with the Python scientific software stack (courtesy of NumPy).
  • Aims to offer seamless integration with NumPy.
  • It supports NumPy scalar types:
    • Integers: all integers of either signedness, and any width up to 64 bits.
    • Booleans.
    • Real numbers: single-precision (32-bit) and double-precision (64-bit) reals.
    • Complex numbers: single-precision (2×32-bit) and double-precision (2×64-bit) complex numbers.
    • Datetimes and timestamps: of any unit.
    • Character sequences (but no operations are available on them).
    • Structured scalars: structured scalars made of any of the types above and arrays of the types above.
  • Basic linear algebra is supported on 1-D and 2-D contiguous arrays of floating-point and complex numbers.
  • NumPy arrays of any of the scalar types above are supported, regardless of the shape or layout.
  • Supports top-level functions from the numpy.random module.
  • Seeks to support as much of the Python language as possible.
  • Support for Python features in CUDA Python.
  • Uses contributions from Intel, via the ParallelAccelerator project, to speed up some operations by automatically parallelizing them.
  • Supported platforms:
    • Linux x86 (32-bit and 64-bit).
    • Windows 7 and later (32-bit and 64-bit).
    • OS X 10.9 and later (64-bit).
    • NVIDIA GPUs of compute capability 2.0 and later.
    • AMD APUs supported by the HSA 1.0 final runtime (Kaveri, Carrizo).

Support: Documentation, Mailing List, GitHub
Developer: Anaconda, Inc
License: BSD 2-Clause “Simplified” License

Numba is written in Python. Learn Python with our recommended free books and free tutorials.

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