SPARQ-SGD: Event-Triggered and Compressed Communication in Decentralized Stochastic Optimization

31 Oct 2019Navjot SinghDeepesh DataJemin GeorgeSuhas Diggavi

In this paper, we propose and analyze SPARQ-SGD, which is an event-triggered and compressed algorithm for decentralized training of large-scale machine learning models. Each node can locally compute a condition (event) which triggers a communication where quantized and sparsified local model parameters are sent... (read more)

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