English

Federated Sinkhorn

Distributed, Parallel, and Cluster Computing 2026-02-09 v2 Machine Learning

Abstract

We study distributed Sinkhorn iterations for entropy-regularized optimal transport when the Gibbs kernel operator is row-partitioned across c workers and cannot be centralized. We present Federated Sinkhorn, two exact synchronous protocols that exchange only scaling-vector slices: (i) an All-to-All scheme implemented by Allgather, and (ii) a Star (parameter-server) scheme implemented by client to server sends and server to client broadcasts. For both, we derive closed-form per-iteration compute, communication, and memory costs under an alpha-beta latency--bandwidth model, and show that the distributed iterates match centralized Sinkhorn under standard positivity assumptions. Multi-node CPU/GPU experiments validate the model and show that repeated global scaling exchange quickly becomes the dominant bottleneck as c increases. We also report an optional bounded-delay asynchronous schedule and an optional privacy measurement layer for communicated log-scalings.

Keywords

Cite

@article{arxiv.2502.07021,
  title  = {Federated Sinkhorn},
  author = {Jeremy Kulcsar and Vyacheslav Kungurtsev and Georgios Korpas and Giulio Giaconi and William Shoosmith},
  journal= {arXiv preprint arXiv:2502.07021},
  year   = {2026}
}
R2 v1 2026-06-28T21:39:23.496Z