Learning path

High Performance AI/ML Networking

Skill Level
Intermediate
Duration 1h 20m
Updated Apr 21, 2024

About this learning path

Today, network engineers, especially in the data center space, must acquire AI/ML infrastructure skills and be able to discuss the required infrastructure upgrades and the reasoning for the upgrades with upper management. At WWT, we are committing $500 million to help our customers with AI/ML, and we have launched a new series of Learning Paths to help the reader navigate complex AI topics. By mastering these areas, data center network engineers can effectively contribute to successfully implementing and managing advanced AI and HPC infrastructure, aligning technological capabilities with business objectives while maintaining a robust and secure network environment.

Your instructors

World Wide Technology

Principal Solutions Architect

World Wide Technology

Technical Solutions Architect - ACI

World Wide Technology

Technical Solutions Architect

Prerequisites

  1. A understanding of AI/ML terms and concepts from WWT AI Fundamentals Learning Path
  2. CCNA certification or a basic understanding of primary network concepts VLANs, IP address, and Gateways.

What you'll learn

  1. Why traffic patterns in a AI/ML GPU cluster is different then regular datacenter traffic
  2. The design challenges for back end high performance GPU networks
  3. Infiniband primer
  4. RMDA over Converged Ethernet (RoCE) primer
  5. Summary of OEM offerings
  6. Integration of white box switches and open networking operating systems
  7. Future of AI/ML infrastructure's
  1. 1. AI/ML Workload Challenge​
    1. Enroll in this learning path to view locked content Understanding the Unique Nature of AI/ML Datacenter Traffic
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  2. 2. Optimizing AI/ML Performance​
    1. Enroll in this learning path to view locked content AI/ML GPU Node Design Challenges for the Network Engineer​
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    2. Enroll in this learning path to view locked content RoCE primer for the Network Engineer
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    3. Enroll in this learning path to view locked content Why InfiniBand for AI Networks?
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  3. 3. OEM AI/ML Design solutions​
    1. Enroll in this learning path to view locked content AI/ML GPU Networking OEM summary
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    2. Enroll in this learning path to view locked content The Open Network Ecosystem: Integrating White Box Switches with Open NOS
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  4. 4. Future network designs and hardware​
    1. Enroll in this learning path to view locked content Future-Proofing Network Architecture: Meeting the Demands of Next-Gen GPUs
      Article
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  5. 5. Conclusion
    1. Enroll in this learning path to view locked content Quiz
      Quiz
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    2. Enroll in this learning path to view locked content Learning Path Complete
      Achievement Badge
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