Papers
arxiv:2403.07128

FAX: Scalable and Differentiable Federated Primitives in JAX

Published on Mar 11
· Featured in Daily Papers on Mar 13

Abstract

We present FAX, a JAX-based library designed to support large-scale distributed and federated computations in both data center and cross-device applications. FAX leverages JAX's sharding mechanisms to enable native targeting of TPUs and state-of-the-art JAX runtimes, including Pathways. FAX embeds building blocks for federated computations as primitives in JAX. This enables three key benefits. First, FAX computations can be translated to XLA HLO. Second, FAX provides a full implementation of federated automatic differentiation, greatly simplifying the expression of federated computations. Last, FAX computations can be interpreted out to existing production cross-device federated compute systems. We show that FAX provides an easily programmable, performant, and scalable framework for federated computations in the data center. FAX is available at https://github.com/google-research/google-research/tree/master/fax .

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FAX is on Github here, package google-fax on PyPi. FAX is, in many ways, anchored in the federated autodiff paper, which can be found here.

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