Using the latest advancements from TensorFlow including the Accelerated Linear Algebra (XLA) Framework, JIT/AOT Compiler, and Graph Transform Tool , I’ll demonstrate how to optimize, profile, and deploy TensorFlow Models - and the TensorFlow Runtime - in GPU-based production environment.
This talk is 100% demo based with open source tools and completely reproducible through Docker on your own GPU cluster.
Chris Fregly is Founder and Research Engineer at PipelineAI, a Streaming Machine Learning and Artificial Intelligence Startup based in San Francisco. He is also an Apache Spark Contributor, a Netflix Open Source Committer, founder of the Global Advanced Spark and TensorFlow Meetup, author of the O’Reilly Training and Video Series titled, "High Performance TensorFlow in Production."
Pipeline.AI was also the recent winner of the O'Reilly Media AI Startup Showcase at the AI conference.
Previously, Chris was a Distributed Systems Engineer at Netflix, a Data Solutions Engineer at Databricks, and a Founding Member and Principal Engineer at the IBM Spark Technology Center in San Francisco.