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Setting up decentralizepy
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* Fork the repository.
* Clone and enter your local repository.
* Check if you have ``python>=3.8``. ::
python --version
* (Optional) Create and activate a virtual environment. ::
python3 -m venv [venv-name]
source [venv-name]/bin/activate
pip3 install --upgrade pip
pip install --upgrade pip
* On Mac M1, installing ``pyzmq`` fails with `pip`. Use `conda <https://conda.io>`_.
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Running the code
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* Choose and modify one of the config files in ``eval/{step,epoch}_configs``.
* Modify the dataset paths and ``addresses_filepath`` in the config file.
* In eval/run.sh, modify arguments as required.
* Execute eval/run.sh on all the machines simultaneously. There is a synchronization barrier mechanism at the start so that all processes start training together.
Node
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* The Manager. Optimizations at process level.
Dataset
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* Static
Training
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* Heterogeneity. How much do I want to work?
Graph
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* Static. Who are my neighbours? Topologies.
Mapping
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* Naming. The globally unique ids of the ``processes <-> machine_id, local_rank``
Sharing
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* Leverage Redundancy. Privacy. Optimizations in model and data sharing.
Communication
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* IPC/Network level. Compression. Privacy. Reliability