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Architectural Challenges in Modern AI Workloads
DescriptionLike many other hyperscalar companies, Meta heavily relies on AI in its internal systems for numerous things including recommending personalized content to the user; understanding text, speech, and visual content to recognize things such as hate speech; and generating text, image and video content for users. While these AI workloadsshare some similarities with traditional scientific computing applications, they are a lot less structured---their computational requirements, memory access patterns, data I/O approaches, and network communication, tend to be highly irregular raising tremendous challenges on modern supercomputing system architectures. In this talk, I'll discuss some of these architectural challenges and allude to some potential hardware and software solutions that Meta as well as the broader community is looking at to address these challenges.
Event Type
Workshop
TimeMonday, 18 November 202411:15am - 12pm EST
LocationB314
Tags
Artificial Intelligence/Machine Learning
Codesign
Registration Categories
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