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Full Description
Artificial intelligence is redefining the scale, architecture, and performance expectations of modern data centers. Training large ML models demand infrastructure capable of moving massive data sets through highly parallel, compute-intensive environments—where traditional data center designs simply can't keep up.
AI Data Center Network Design and Technologies is the first comprehensive, vendor-agnostic guide to the design principles, architectures, and technologies that power AI training and inference clusters. Written by leading experts in AI Data center design, this book helps engineers, architects, and technology leaders understand how to design and scale networks purpose-built for the AI era.
INSIDE, YOU'LL LEARN HOW TO
Architect scalable, high-radix network fabrics to support xPU (GPE, TPU)-based AI clusters
Integrate lossless Ethernet/IP fabrics for high-throughput, low-latency data movement
Align network design with AI/ML workload characteristics and server architectures
Address challenges in cooling, power, and interconnect design for AI-scale computing
Evaluate emerging technologies from the Ultra Ethernet Consortium (UEC) and their affect on future AI data centers
Apply best practices for deployment, validation, and performance measurement in AI/ML environments
With broad coverage of both foundational concepts and emerging innovations, this book bridges the gap between network engineering and AI infrastructure design. It empowers readers to understand not only how AI data centers work—but why they must evolve.
Contents
Part 1: AI/ML Data Center Design Workloads and Requirements
Chapter 1 Wonders in the Workload
Chapter 2 "The Common-Man View" of AI Data Center Fabrics
Part 2: AI/ML Data Center Design Concepts
Chapter 3 Network Design Considerations
Chapter 4 Optics and Cables Management
Chapter 5 Thermal and Power Efficiency Considerations
Part 3: AI/ML Data Center Technology Requirements
Chapter 6 Efficient Load Balancing
Chapter 7 RoCEv2 Transport and Congestion Management
Chapter 8 IP Routing for AI/ML Fabrics
Chapter 9 Storage Network Design and Technologies
Part 4: KPIs and Performance Monitoring
Chapter 10 AI Network Performance KPIs
Chapter 11 Monitoring and Telemetry
Part 5: UEC - Ultra Ethernet Consortium
Chapter 12 Ultra Ethernet Consortium (UEC)
CONCLUSION
Chapter 13 Scale-Up Systems
Chapter 14 Conclusion
Appendix A: Questions and Answers
Appendix B: Acronyms
