Step-Ahead Error Feedback for Distributed Training with Compressed Gradient. (arXiv:2008.05823v2 [cs.LG] UPDATED)

Although the distributed machine learning methods can speed up the training
of large deep neural networks, the communication cost has become the
non-negligible bottleneck to constrain the performance. To address this
challenge, the gradient compression based communication-efficient distributed
learning methods were designed to reduce the communication cost, and more
recently the local error feedback was incorporated to compensate for the
corresponding performance loss. However, in this paper, we will show that a new
"gradient mismatch" problem is raised by the …

arxiv distributed gradient training