Scalable Distributed Deep Learning with Hillery Hunter - TWiML Talk #77
Published:Dec 4, 2017 19:34
•1 min read
•Practical AI
Analysis
This podcast episode from Practical AI focuses on distributed deep learning, featuring Hillery Hunter from IBM. The discussion centers around the PowerAI Distributed Deep Learning Communication Library (DDL), exploring its technical architecture, synchronous training capabilities, and Multi-Ring Topology. The episode caters to a technical audience interested in the performance and hardware aspects of deep learning. The interview provides insights into IBM's research and development in the field, offering a glimpse into the practical applications of AI within an enterprise context, as discussed at the AI Summit in New York City.
Key Takeaways
- •The podcast discusses the PowerAI DDL, a library for distributed deep learning.
- •The episode explores the technical architecture and synchronous training capabilities of DDL.
- •The conversation highlights the advantages of the Multi-Ring Topology used in DDL.
Reference
“Hillery joins us to discuss her team's research into distributed deep learning, which was recently released as the PowerAI Distributed Deep Learning Communication Library or DDL.”