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Parallel parameter estimation in python and opencl.

Project description

Maastricht Optimization Toolbox

.. image::

A library for parallel optimization and sampling in python and opencl.

* Free software: LGPL v3 license
* Full documentation:
* Project home:
* Uses the `GitLab workflow <>`_
* Tags: optimization, parallel, opencl, python

.. highlight:: console

The installation is a three step procedure:

1. Installing a Python interpreter
2. Installing the PyOpenCL drivers and Python bindings
3. Install MOT

Installing Python
Since it is a Python package we need to install the Python interpreter. Considering that Python2 is soon end of life, this package focuses on installing it using Python3.

Linux (Ubuntu)
``apt-get install python3 python3-pip``

The easiest way is with Anaconda. Install the Python3.x bindings from `Anaconda <>`_.

Installing OpenCL bindings
For OpenCL you need two things, an OpenCL driver for your platform and the Python OpenCL bindings.

Linux (Ubuntu)
On Ubuntu, the easiest way to install all of this:

``apt-get install python3-pyopencl``

On Windows, make sure you install the correct OpenCL driver (Intel/AMD/NVidia). For graphics cards the drivers are normally already installed. After that, Anaconda should automatically install the Python bindings.

Installing MOT
With OpenCL and Python installed you can now install MOT.

Linux (Ubuntu)
``pip3 install MOT``

Open an Anaconda shell and use:

``pip install MOT``

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