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BlueFog: Make Decentralized Algorithms Practical for Optimization and Deep Learning
[article]
2021
arXiv
pre-print
Decentralized algorithm is a form of computation that achieves a global goal through local dynamics that relies on low-cost communication between directly-connected agents. On large-scale optimization tasks involving distributed datasets, decentralized algorithms have shown strong, sometimes superior, performance over distributed algorithms with a central node. Recently, developing decentralized algorithms for deep learning has attracted great attention. They are considered as
arXiv:2111.04287v1
fatcat:ei7xa3r6czfnvhyglt42sd3dca