Anaconda Enterprise: Documentation

# Anaconda Accelerate

High Performance Computing

Anaconda Accelerate is a package that provides the Anaconda® platform access to several numerical libraries that are optimized for performance on Intel CPUs and NVidia GPUs.

The current version, 2.3.1, was released on January 30, 2017.

Anyone can now use the functionality from Accelerate without purchasing a license!

On July 27, 2017, Accelerate was split into the Intel Distribution for Python and the open source Numba project’s sub-projects pyculib, pyculib_sorting and data_profiler. Numba and all its sub-projects are available under a BSD license.

More information is available in the post Open Sourcing Anaconda Accelerate.

## Features

- Bindings to the following CUDA libraries:
    - cuBLAS
    - cuFFT
    - cuSPARSE
    - cuRAND
    - CUDA Sorting algorithms from the CUB and Modern GPU libraries

- Speed-boosted linear algebra operations in NumPy, SciPy, scikit-learn and NumExpr libraries using Intel’s Math Kernel Library (MKL).

- Accelerated variants of Numpy’s built-in UFuncs.

- Increased-speed Fast Fourier Transformations (FFT) in NumPy.

## Installation

This section contains information related to:

- Requirements
- Installing Accelerate
- Updating Accelerate
- Updating NumbaPro
- Managing your Accelerate license

## User guide

This section contains information related to:

- CUDA libraries
- Math Kernel Library
- Profiling
- Environment variables

## License agreement

- Anaconda Accelerate End User License Agreement

## Release notes

- Release notes
- Previous versions

## Previous versions

The following documentation is provided for users who have not yet upgraded to the current version:

- Accelerate 2.2
- Accelerate 2.1
- Accelerate 2.0