.. Accelerate documentation master file, created by
   sphinx-quickstart on Fri Aug  7 17:43:03 2015.
   You can adapt this file completely to your liking, but it should at least
   contain the root `toctree` directive.

Anaconda Accelerate
===================
:emphasis:`High Performance Computing`

`Accelerate` provides access to numerical libraries optimized for performance on
Intel CPUs and NVidia GPUs. The current version of Accelerate 2.3 was released 
on July 5, 2016.


Features
--------

* Bindings to CUDA libraries: cuBLAS, cuFFT, cuSPARSE, cuRAND, and 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.

The Accelerate package works with the free Math Kernel Library (MKL) package
from Intel, which is included in Anaconda. MKL provides BLAS, LAPACK, and other
math routines as described on `Intel's site
<https://software.intel.com/en-us/mkl-reference-manual-for-c>`_.

Requirements
------------

* 64-bit operating system: Linux, OS X or Windows
* Supported Python and Numpy combinations:
   * Python 2.7 with Numpy 1.9, 1.10 or 1.11
   * Python 3.4 with Numpy 1.9, 1.10 or 1.11
   * Python 3.5 with Numpy 1.9, 1.10 or 1.11
* Numba 0.26

For the CUDA features:

* NVidia driver version 349.00 or later
* CUDA toolkit 7.0
* At least one CUDA GPU with compute capability 2.0 or above


Installation
------------

Accelerate is included with `Anaconda Workgroup and Anaconda Enterprise
subscriptions <https://www.continuum.io/anaconda-subscriptions>`_.

To start a 30-day free trial just download and install the Anaconda Accelerate
package.

If you already have `Anaconda <http://continuum.io/downloads.html>`_ (free
Python distribution) installed::

    conda update conda
    conda install accelerate

If you do not have Anaconda installed, you can download it `here
<http://continuum.io/downloads.html>`_.

Accelerate licenses can be installed, viewed and removed with the 
graphical Anaconda Navigator license manager or manually with your 
operating system. For more information please see the 
:doc:`License installation </anaconda/license-installation>` page.

Anaconda Accelerate can also be installed into your own (non-Anaconda) Python
environment. For more information about Accelerate please contact
`sales@continuum.io <mailto:sales@continuum.io>`_.


Update Instructions
-------------------

If you have Anaconda (free Python distribution) installed::

    conda update conda
    conda update accelerate

If you already have NumbaPro installed, you must manually upgrade NumbaPro to
install the NumbaPro compatibility layer::

    conda update conda
    conda update numbapro


.. toctree::
   :maxdepth: 3
   :hidden:

   releasenotes
   api
   cudalibs
   mkl
   profiling


License Agreement
-----------------

.. toctree::
   :maxdepth: 1

   eula

Previous Versions
-----------------

This documentation is provided for the use of our customers who have not yet upgraded 
to the current version.

.. toctree::
   :maxdepth: 1

   Accelerate 2.2 <2.2/index>
   Accelerate 2.1 <2.1/index>
   Accelerate 2.0 <2.0/index>
