2020
Accelerating Distributed Deep Learning By Adaptive Gradient Quantization
ICASSP 2020accepted
To accelerate distributed deep learning, gradient quantization technique is widely used to reduce the communication cost. However, the existing quantization schemes suffer from either model accuracy degradation or low compression ratio (arisen from a redundant setting of quantization level or high o…