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Learn about innovative networking solutions in this 18-minute technical talk that explores the application of SONiC-based disaggregated scheduled fabric (DSF) for machine learning and AI workloads. Discover how backend networks support ML/AI operations, understand the fundamentals of SONiC for chassis systems, and examine the adaptation of SONiC chassis design to DSF architecture. Explore remote host IP and neighbor distribution methodologies in DSF, with a focus on Option #2 implementation. Gain valuable insights into modern networking infrastructure designed to optimize performance for demanding artificial intelligence and machine learning applications.
Syllabus
Intro
Backend Networks for ML/AI workloads
SONIC for Chassis - Recap
Adopting SONIC Chassis Design to DSF
Remote Host IP/Neighbor Distribution in DSF - Option #2
Taught by
LF Networking