Traffic- and Multi-Tenancy-Aware In-Network Aggregation Placement for Distributed Machine Learning
Distributed machine learning is an effective method to alleviate the intensive computation costs of training; however, it suffers from network bottlenecks while collecting local results. The recent advent of programmable data planes has opened a new avenue, in-network aggregation, which executes gradient aggregations i...