AI data center network design and technologies / (Record no. 141545)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02270nam a22002417a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20260721150024.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 260721s2026 |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9780135436288 |
| 040 ## - CATALOGING SOURCE | |
| Transcribing agency | PK-LaUMT |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 004.678 |
| Item number | SUB-A |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Subramaniam, Mahesh |
| 245 10 - TITLE STATEMENT | |
| Title | AI data center network design and technologies / |
| Statement of responsibility, etc | Mahesh Subramaniam, Michal Styszynski and Himanshu Tambakuwala |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication, distribution, etc | Hoboken : |
| Name of publisher, distributor, etc | Addison-Wesley, |
| Date of publication, distribution, etc | 2026 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | xxiv, 349 p. |
| 500 ## - GENERAL NOTE | |
| General note | Index present |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | "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 designs simply cant 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. You will tearn 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"-- Back cover |
| 546 ## - LANGUAGE NOTE | |
| Language note | Eng |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Internet |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Network communication |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Styszynski, Michal |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Tambakuwala, Himanshu |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Books |
| Withdrawn status | Lost status | Damaged status | Home library | Current library | Date acquired | Full call number | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|
| UMT Main Campus | UMT Main Campus | 2026-07-21 | 004.678 SUB-A | 153743 | 2026-07-21 | 2026-07-21 | Books |