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The Distributed Computing Library (dislib) provides distributed algorithms ready to use as a library. So far, dislib is highly focused on machine learning algorithms, and it is greatly inspired by scikit-learn. However, other types of numerical algorithms might be added in the future. The library has been implemented on top of PyCOMPSs programming model, and it is being developed by the Workflows and Distributed Computing group of the Barcelona Supercomputing Center. dislib allows easy local development through docker. Once the code is finished, it can be run directly on any distributed platform without any further changes. This includes clusters, supercomputers, clouds, and containerized platforms. For more information on which infrastructures and architectures are supported refer to Availability.
Get started with dislib following our quickstart guide.
Currently, the following supercomputers have already PyCOMPSs installed and ready to use. If you need help configuring your own cluster or supercomputer, drop us an email and we will be pleased to help.
- Marenostrum 4 - Barcelona Supercomputing Center (BSC)
- Minotauro - Barcelona Supercomputing Center (BSC)
- Nord 3 - Barcelona Supercomputing Center (BSC)
- Cobi - Barcelona Supercomputing Center (BSC)
- Juron - Jülich Supercomputing Centre (JSC)
- Jureca - Jülich Supercomputing Centre (JSC)
- Ultraviolet - The Genome Analysis Center (TGAC)
- Archer - University of Edinburgh’s Advanced Computing Facility (ACF)
- Axiom - University of Novi Sad, Faculty of Sciences (UNSPMF)
Supported architectures:
Contributions are welcome and very much appreciated. We are also open to starting research collaborations or mentoring if you are interested in or need assistance implementing new algorithms. Please refer to our Contribution Guide for more details.
Apache License Version 2.0, see LICENSE