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Paper · arXiv 2403.07128

FAX: Scalable and Differentiable Federated Primitives in JAX

Keith Rush, Zachary Charles, Zachary Garrett

12 upvotesMarch 11, 2024arXiv 预印本
AI 摘要

FAX is a JAX-based library enabling distributed and federated computations using TPUs, XLA HLO, and native federated automatic differentiation.

TPUsXLA HLOfederated automatic differentiation

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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