Maastricht Optimization Toolbox
A library for parallel optimization and sampling using Python and OpenCL.
- Free software: LGPL v3 license
- Full documentation: https://mot.readthedocs.org
- Project home: https://github.com/cbclab/MOT
- Uses the GitLab workflow
- Tags: optimization, parallel, opencl, python
For the diffusion MRI package MDT which builds on top of this, please see https://github.com/cbclab/MDT.
Quick installation guide
The basic requirements for MOT are:
- Python 3.x (recommended) or Python 2.7
- OpenCL 1.2 (or higher) supper in GPU driver or CPU runtime
For Ubuntu >= 16 you can use:
- sudo add-apt-repository ppa:robbert-harms/cbclab
- sudo apt-get update
- sudo apt-get install python3-mot
For Debian users and Ubuntu < 16 users, install MOT with:
- sudo apt-get install python3 python3-pip python3-pyopencl
- sudo pip3 install MOT
- Install Python Anaconda 3.* 64bit from https://www.continuum.io/downloads
- Open a Anaconda shell and type: pip install MOT
For more information and for more elaborate installation instructions, please see: https://mot.readthedocs.org
There are a few caveats and known issues, primarily related to OpenCL:
- Windows support is experimental due to the difficulty of installing PyOpenCL, hopefully installing PyOpenCL will get easier on Windows soon.
- For AMD users with Ubuntu >= 16, the new AMD GPU-Pro driver is still in beta and may not work with all the kernels in MOT. Our recommendation at the moment (October 2016) is to use Ubuntu version 14.
- GPU acceleration is not possible in most virtual machines due to lack of GPU or PCI-E pass-through, this will change whenever virtual machines vendors program this feature. Our recommendation is to install neurodebian on your machine and run it on that.
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