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Join Keysight engineers for an in-depth exploration of emulating, validating, and optimizing AI data center performance at scale. This course discusses the importance of emulating AI data center workloads and introduces the latest solutions for workload emulation and collective benchmarking. By the end of this course, you will be able to pinpoint network bottlenecks through real-world AI workload emulation and optimize system-level efficiency.
Learn:
How to reproduce network communication patterns of real-world AI training jobs
How to identify low-performing collective operations and drill down to identify bottlenecks
How to experiment to fine-tune model partitioning schemas, parameters, and algorithms
This course is ideal for network architects or component engineers looking to gain a deeper understanding of emulating and optimizing AI data center system-level performance.
