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Wenjiao Feng

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Book Open access Aug 2026

Aquavit: Ascending Quantization for Communication-Efficient Vast-Scale Distributed Training

The Noise Equivalent Hypothesis is proposed: the noise inherent to the weight quantization process plays a role functionally analogous to the stochastic gradient variance present in standard SGD optimization, and it is theoretically prove that just as a decaying learning rate is essential for convergence, an ascending...

Hong Huang, Jia-Xun Ye, Jin-Hai Yang et al. · 0 citations
Book Open access Aug 2026

Aquavit: Ascending Quantization for Communication-Efficient Vast-Scale Distributed Training

Training Large Foundation Models (LFMs), including Large Language Models and Vision-Language Models, on massive distributed GPU clusters is increasingly bottlenecked by communication overhead. While frameworks like ZeRO++ employ static quantization to reduce communication volume, they suffer from a rigid trade-off: agg...

Hong Huang, Jiaxun Ye, Jinhai Yang et al. · 0 citations

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