AI Data Center Network and Technologies

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 environmentswhere traditional data center s simply cant keep up. AI Data Center Network and Technologies is the first comprehensive, vendor-agnostic guide to the principles, architectures, and technologies that power AI training and inference clusters. Written by leading experts in AI Data center , this book helps engineers, architects, and technology leaders understand how to and scale networks purpose-built for the AI era. INSIDE, YOULL 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 with AI/ML workload characteristics and server architectures Address challenges in cooling, power, and interconnect 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 . It empowers readers to understand not only how AI data centers workbut why they must evolve.