Review for NeurIPS paper: Throughput-Optimal Topology Design for Cross-Silo Federated Learning

In general the paper reads well, there are only minor details I have regarding clarity of presentation. I do appreciate being upfront about what kind of scenarios this work applies to and what not. Sec 1 I think very well grounds the rest of the work in prior research. In particular, in contrast to some related recent works, I feel this thorough grounding helps the authors to ask better questions, and in this sense I feel this work could help inspire further research. L65: I am not sure how compression plays into the preference for sychronous algorithms. It is relevant though, including for the precise topic studied here. Perhaps missing reference is Caldas et al., "Expanding the Reach of Federated Learning by Reducing Client Resource Requirements" which does both model and update compression as in the text.