Anaconda Accelerate

High Performance Computing

Accelerate provides access to numerical libraries optimized for performance on Intel CPUs and NVidia GPUs.

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.

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.

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

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

conda update conda
conda install accelerate

If you do not have Anaconda installed, you can download it here.

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 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.

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

Documentation for Past Versions