ROCm and Hopsworks for end-to-end deep learning pipelines





Who is this presentation for?
- Data scientists, data architects, data engineers, and CTOs
Level
IntermediateDescription
The Radeon open ecosystem (ROCm) is an open source software foundation for GPU computing on Linux. ROCm supports TensorFlow and PyTorch using MIOpen, a library of highly optimized GPU routines for deep learning.
Jim Dowling and Ajit Mathews outline how Hopsworks, an open source platform for machine learning infrastructure, enables the training and operation of deep learning models on ROCm in horizontally scalable end-to-end machine learning pipelines. He presents performance benchmarks for ROCm on new GPU hardware (AMD MI50, MI60 GPUs) and shows you how Hopsworks can enable distributed deep learning with both ROCm and Cuda on both TensorFlow and PyTorch. You’ll see a live demonstration of training and inference for an end-to-end machine learning pipeline written in a number of Jupyter notebooks orchestrated by Airflow.
Prerequisite knowledge
A basic understanding of Python and either TensorFlow or PyTorch programsWhat you'll learn
- Learn that ROCm is a viable, high-performance platform for deep learning and Hopsworks enables the development and operation of horizontally scalable deep learning pipelines using ROCm

Jim Dowling
Logical Clocks
Jim Dowling is the CEO of Logical Clocks, an associate professor at KTH Royal Institute of Technology in Stockholm, and lead architect of Hopsworks, an open source data and AI platform. He’s a regular speaker at big data industry conferences. He holds a PhD in distributed systems from Trinity College Dublin.

Ajit Mathews
AMD
Ajit Mathews is the vice president of machine learning software engineering at AMD, where he’s the engineering leader responsible for the design and development of Radeon Open Compute (ROCm) machine intelligence software spanning deep learning frameworks, compilers, language runtimes, libraries and Linux compute kernel. Ajit is also responsible for the machine learning software road map and strategy. He’s passionate about distributed machine learning and high-performance computing. Ajit holds a master’s degree in computer science and an MBA from Kellogg.
Presented by
Elite Sponsors
Strategic Sponsor
Exabyte Sponsor
Impact Sponsor
Contact us
confreg@oreilly.com
For conference registration information and customer service
partners@oreilly.com
For more information on community discounts and trade opportunities with O’Reilly conferences
aisponsorships@oreilly.com
For information on exhibiting or sponsoring a conference
pr@oreilly.com
For media/analyst press inquires