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Kimad: Adaptive Gradient Compression with Bandwidth Awareness

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arxiv 2312.08053 v1 pith:MJF57WSD submitted 2023-12-13 cs.LG cs.DCcs.ITmath.IT

Kimad: Adaptive Gradient Compression with Bandwidth Awareness

Jihao Xin , Ivan Ilin , Shunkang Zhang , Marco Canini , Peter Richt\'arik This is my paper
classification cs.LG cs.DCcs.ITmath.IT
keywords compressionkimadadaptivebandwidthdistributedgradientawarenessbenchmark
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In distributed training, communication often emerges as a bottleneck. In response, we introduce Kimad, a solution that offers adaptive gradient compression. By consistently monitoring bandwidth, Kimad refines compression ratios to match specific neural network layer requirements. Our exhaustive tests and proofs confirm Kimad's outstanding performance, establishing it as a benchmark in adaptive compression for distributed deep learning.

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