Title
CodedReduce: A Fast and Robust Framework for Gradient Aggregation in Distributed Learning
Abstract
We focus on the commonly used synchronous Gradient Descent paradigm for large-scale distributed learning, for which there has been a growing interest to develop efficient and robust gradient aggregation strategies that overcome two key system bottlenecks: communication bandwidth and stragglers’ delays. In particular, Ring-AllReduce (RAR) design has been proposed to avoid bandwidth...
Year
DOI
Venue
2019
10.1109/TNET.2021.3109097
IEEE/ACM Transactions on Networking
Keywords
DocType
Volume
Bandwidth,Topology,Resilience,Distance learning,Computer aided instruction,Encoding,Training
Journal
30
Issue
ISSN
Citations 
1
1063-6692
0
PageRank 
References 
Authors
0.34
16
4
Name
Order
Citations
PageRank
Amirhossein Reisizadehmobarakeh1616.44
Saurav Prakash210.69
Ramtin Pedarsani317129.35
Amir Salman Avestimehr41880157.39