Collaborative Routing optimizes data transfers in distributed machine learning by coordinating traffic routing. It reduces delays and congestion, speeding up synchronization and improving training efficiency in machine learning data centers.

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Accelerating Distributed Machine Learning with an Efficient AllReduce Routing Strategy

We propose an efficient routing strategy for AllReduce transfers, which compromise of the dominant traffic in machine learning-centric datacenters, to achieve fast parameter synchronization in distributed machine learning, improving the average training time by 9%.