research
∙
02/05/2023
Quantized Distributed Training of Large Models with Convergence Guarantees
Communication-reduction techniques are a popular way to improve scalabil...
share
research
∙
10/31/2022
L-GreCo: An Efficient and General Framework for Layerwise-Adaptive Gradient Compression
Data-parallel distributed training of deep neural networks (DNN) has gai...
research
∙
11/16/2021
Project CGX: Scalable Deep Learning on Commodity GPUs
The ability to scale out training workloads has been one of the key perf...
research
∙
10/23/2020
Adaptive Gradient Quantization for Data-Parallel SGD
Many communication-efficient variants of SGD use gradient quantization s...
research
∙
10/27/2019
