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April 15-18, 2019
New York, NY
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Distributed TensorFlow with Distribution Strategies

Magnus Hyttsten (Google)
2:40pm3:20pm Thursday, April 18, 2019
Implementing AI
Location: Mercury Rotunda
Secondary topics:  Deep Learning and Machine Learning tools

Who is this presentation for?

Developers, software engineers

Level

Intermediate

Prerequisite knowledge

TensorFlow user Some experience with running some distributed training in any framework

What you'll learn

How to run distributed TF on CPUs, GPUs, and TPUs with keras and estimator apis

Description

We have altered the basic way to do distributed training on TensorFlow. Changes include:
-Using TensorFlow 2.0, which turns on eager execution by default
-Refactoring some of the core functionality out of Estimators, and
-Packing up algorithms for distributing computation into slottable objects called “DistributionStrategies”.

We’ll go over basic DistributionStrategy use, explore some of the underlying algorithms (like Allreduce), and show how this can accelerate your training in various hardware configurations.

This discussion will also talk about how we measure performance, and ways we can consistently show and reproduce performance.

Photo of Magnus Hyttsten

Magnus Hyttsten

Google

Magnus Hyttsten is a developer advocate for TensorFlow at Google, where he works on developing the TensorFlow product. A developer fanatic, Magnus is an appreciated speaker at major industry events such as Google I/O, the AI Summit, AI Conference, ODSC, GTC, QCon, and others on machine learning and mobile development. Right now, he’s focusing on reinforcement learning models and making model inference effective on mobile.

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