Supercharging MLOps with Composability, Automation, and Scalability

Abstract: 

The new Petuum Platform is a composable platform for automatic and scalable MLOps. Today's widespread practice of ad-hoc integration between many fragmented ML tools leaves hard-to-fill gaps in end-to-end automation, scalability, and management of AI/ML applications. With the Petuum Platform, ML applications and infrastructure can be composed quickly and flexibly from standardized and reusable building blocks, thus transforming MLOps from ad-hoc craft production into a repeatable assembly-line process. This presentation and demo will show how your team can easily compose, manage, and monitor AI/ML infrastructure across multiple systems on a single pane of glass, seamlessly scale ML pipelines from local development to batch execution and online serving, and optimize end-to-end ML pipelines in an automatic and cost-efficient way. We will discuss new innovations in Composable, Automatic, and Scalable ML (CASL), developed in collaboration with CMU, UC Berkeley, and Stanford, and how they play a pivotal role in the Petuum Platform.

Bio: 

Tong Wen is an Architect and Director of Engineering at Petuum. Tong joined Petuum from Microsoft where he was a member of the founding team of Azure Machine Learning. Tong has 10+ years of experience in building innovative and high-impact AI/ML and HPC platforms with proven track record. Before his first startup experience in 2008, Tong was a researcher in computational science and engineering at IBM Research and Lawrence Berkley National Lab. He holds a Ph.D. degree in applied mathematics from MIT.

Open Data Science

 

 

 

Open Data Science
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