Hands-on AI Networking by Shankar Ramanathan (.ePUB)
File Size: 10 MB
Hands-on AI Networking: Understand architecture, automation, case studies, and explore future trends by Shankar Ramanathan
Requirements: .ePUB reader, 10 MB
Overview: The building blocks of any large-scale distributed system such as an AI cluster are compute, storage, and network. The network infrastructure connects all the components enabling data transfer, communication, and coordination between compute nodes, storage devices, and AI applications. The network is also the slowest component among the three which necessitates innovative architecture, a scalable software stack, and automation tools. This book covers the fundamentals of networking, explains the nature of the AI workloads that justify the non-negotiable requirements expected of the network, and explains how those requirements are met. We start with data center architecture and the network topologies that are best suited for AI workloads. We also touch upon automation tools and look at real-world examples from Google, Meta, and OCI to see how these ideas play out. Finally, we talk about security and reliability, introduce you to future trends such as quantum computing and quantum networks, and wrap up by showing how AI and networking have a symbiotic relationship. By the end of this book, you would have a clear understanding of what kind of topology you would need to run the type of AI workloads you intend to run, and the networking stack you need to use, depending on whether you are building a network for AI training or for AI inference. This book is for network architects, cloud networking engineers, AI infrastructure builders, and network designers who possess fundamental knowledge of networking protocols, distributed systems, and basic AI/ML workflows, alongside cloud solution architects and advanced computer science students.
Genre: Non-Fiction > Tech & Devices
Free Download links: