The Maastricht Optimization Toolbox, MOT, is a library for parallel optimization and sampling using the graphics card for the computations. It is meant to optimize, in parallel, a large number of smaller problems, in contrast to optimizing one big problem with parallelized parts. For example, in diffusion MRI the brain is scanned in a 3D grid where each grid element, a voxel, represents its own optimization problem. The number of data points per voxel is generally small, ranging from 30 to 500 datapoints, and the models fitted to that data have generally somewhere between 6 and 20 parameters. Since each of these voxels can be analyzed independently of the others, the computations can be massively parallelized and hence programming for the graphics card can allow for a large speed gain. This software toolbox was originally built for exactly this use case, yet the algorithms and data structures are generalized such that any scientific field may take advantage of this toolbox. For the diffusion MRI package MDT to which is referred in this example, please see https://github.com/cbclab/MDT.
Can MOT help me?
To recognize if MOT can help you with your use case, try to see if your computations can be parallized in some way. If you have just one big optimization problem with 10.000 variables, MOT unfortunately can not help you. On the other hand, if you find a way to split your analysis in (a lot of; >10.000) smaller sub-problems, with ~30 parameters or less each, MOT may actually be of help.
Summary
Free software: LGPL v3 license
Interface in Python, computations in OpenCL
Full documentation: https://mot.readthedocs.org
Project home: https://github.com/cbclab/MOT
PyPi package: PyPi
Uses the GitLab workflow
Tags: optimization, parallel, opencl, python
Quick installation guide
The basic requirements for MOT are:
Python 3.x (recommended) or Python 2.7
OpenCL 1.2 (or higher) support in GPU driver or CPU runtime
Linux
For Ubuntu >= 16 you can use:
sudo add-apt-repository ppa:robbert-harms/cbclab
sudo apt update
sudo apt install python3-mot
For Debian users and Ubuntu < 16 users, install MOT with:
sudo apt install python3 python3-pip python3-pyopencl python3-devel
sudo pip3 install mot
Mac
Install Python Anaconda 3.* 64bit from https://www.continuum.io/downloads>
Open a terminal and type pip install mot
Windows For Windows the short guide is:
Install Python Anaconda 3.* 64bit from https://www.continuum.io/downloads
Install or upgrade your GPU drivers
- Install PyOpenCL using one of the following methods:
Use a binary, for example from http://www.lfd.uci.edu/~gohlke/pythonlibs/#pyopencl or;
- Compile PyOpenCL with pip install pyopencl, this requires:
Visual Studio 2015 (Community edition or higher) with the Python and Common Tools for Visual C++ options enabled
OpenCL development kit (NVidia CUDA or Intel OpenCL SDK or the AMD APP SDK)
Open a Anaconda shell and type: pip install mot
For more information and for more elaborate installation instructions, please see: https://mot.readthedocs.org
Caveats
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 optimalization routines cd in MOT. Our recommendation at the moment (October 2016) is to use Ubuntu version 14 when using AMD hardware.
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 Linux on your machine directly.
1 maintainer
Release files for mot 0.2.41
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| mot-0.2.41.tar.gz | 164.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| mot-0.2.41-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Total release size: 919.3 kB
Release files / mot-0.2.41.tar.gz
| Download URL | mot-0.2.41.tar.gz |
|---|---|
| Size | 164.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
df612133c78cd3f13b38fb6fc431b6f03e8be86197029f341188573b1e664d39
|
|
BLAKE2b-256 checksum How to use checksums |
8944472e2d58ddd939a60994fb9f213171f1a3b97640d216403413082388e468
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Release files / mot-0.2.41-py2.py3-none-any.whl
| Download URL | mot-0.2.41-py2.py3-none-any.whl |
|---|---|
| Size | 755.3 kB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
219c8d6dcc42bafc2a26e7c53fb3aef4d1301c2dea074afaf9c9a3aed56d04b2
|
|
BLAKE2b-256 checksum How to use checksums |
ecd960bc2565d29dc2ac1dfea0eb4faffedddae1d2ff8f0795d8a37b8a94c74b
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
