AI Data Center Network Design and Technologies
暫譯: AI 數據中心網路設計與技術

Subramaniam, Mahesh, Styszynski, Michal, Tambakuwala, Himanshu

AI Data Center Network Design and Technologies
  • 出版商: Addison Wesley
  • 出版日期: 2026-02-04
  • 售價: $2,440
  • 貴賓價: 9.5 折 $2,318
  • 語言: 英文
  • 頁數: 384
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 0135436281
  • ISBN-13: 9780135436288
  • 相關分類: 無人機

    • 海外代購書籍(需單獨結帳)

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商品描述

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.

商品描述(中文翻譯)

人工智慧正在重新定義現代數據中心的規模、架構和性能期望。訓練大型機器學習（ML）模型需要能夠在高度平行、計算密集的環境中移動大量數據集的基礎設施，而傳統的數據中心設計根本無法跟上這一需求。

《AI數據中心網絡設計與技術》是首本全面且不依賴於特定供應商的指南，涵蓋了驅動AI訓練和推理集群的設計原則、架構和技術。這本書由AI數據中心設計領域的專家撰寫，幫助工程師、架構師和技術領導者理解如何設計和擴展專為AI時代打造的網絡。

**在書中，您將學到如何：**
- 設計可擴展的高基數網絡架構，以支持基於xPU（GPE、TPU）的AI集群
- 整合無損以太網/IP架構，以實現高吞吐量、低延遲的數據傳輸
- 將網絡設計與AI/ML工作負載特徵和伺服器架構對齊
- 解決AI規模計算中的冷卻、電力和互連設計挑戰
- 評估超以太網聯盟（UEC）新興技術及其對未來AI數據中心的影響
- 在AI/ML環境中應用最佳實踐進行部署、驗證和性能測量

這本書廣泛涵蓋了基礎概念和新興創新，架起了網絡工程與AI基礎設施設計之間的橋樑。它使讀者不僅理解AI數據中心的運作方式，還理解它們為何必須進化。

作者簡介

Mahesh Subramaniam is a proven leader in AI data centers and next-generation networking technologies. He played a key role in defining the advanced software roadmap for AI fabrics, which are now deployed in production networks across various AI data centers worldwide. As the Senior Director of Product Management for AI Data Centers at HPE Juniper Networks, he leads cutting-edge innovations in AI infrastructure and cloud-scale solutions, optimized for both scale-up and scale-out architectures. Mahesh is also an inventor with several technology patents and a recognized speaker at global forums, including the UEC Summit, OCP, and Tokyo MPLS forum. His work has earned him accolades, including the CEO Excellence Award, the Record High Business Award, and the Star Award for the Cloud DC Reference Architecture. With a remarkable history in the networking industry, Mahesh has a strong track record of leading products and managing technical and business strategies across cross-functional teams.

Michal Styszynski is a Product Management Director in the Data Center Networks Business Unit (DC BU) at HPE Juniper Networking. Michal has been with Juniper Networks for more than 13 years. Before his current role, he was a Technical Marketing Engineer (TME) in the DC BU and a Technical Solution Consultant at Juniper. In these roles, he handled data center projects for large-scale enterprises and federal networks and worked closely with Tier 2 cloud and telco-cloud service providers. Before joining Juniper, he spent around 10 years working at Orange, FT R&D, and TPSA Polpak engineering. Michal graduated from the Electronics & Telecommunications department at Wroclaw University of Science & Technology with a master's degree in engineering. He also holds an MBA from Paris Sorbonne Business School and is a JNCIE-DC#523, as well as PEC, PLC, and PMC certified from the Product School in San Francisco.

Himanshu Tambakuwala is a highly accomplished networking expert and certified technical architect whose experience spans the entire product lifecycle[md]from hands-on engineering to product strategy. He is a JNCIE holder in Data Center and Service Provider technologies and an inventor with four granted technology patents and two additional patents currently filed. As a Product Manager at Juniper Networks, Himanshu was instrumental in defining the feature roadmap for network fabrics that power cutting-edge AI/ML data centers.

作者簡介(中文翻譯)

**Mahesh Subramaniam** 是人工智慧數據中心和下一代網路技術的領導者。他在定義人工智慧架構的先進軟體路線圖方面扮演了關鍵角色，這些架構目前已在全球各地的多個人工智慧數據中心的生產網路中部署。作為 HPE Juniper Networks 人工智慧數據中心的產品管理高級總監，他領導著針對擴展和擴展架構優化的人工智慧基礎設施和雲端規模解決方案的前沿創新。Mahesh 也是一位擁有多項技術專利的發明家，並且是全球論壇的知名演講者，包括 UEC 峰會、OCP 和東京 MPLS 論壇。他的工作為他贏得了多項榮譽，包括 CEO 卓越獎、創紀錄商業獎和雲端數據中心參考架構的星際獎。Mahesh 在網路產業擁有卓越的歷史，並在跨功能團隊中領導產品和管理技術及商業策略方面有著良好的記錄。

**Michal Styszynski** 是 HPE Juniper Networking 數據中心網路業務單位 (DC BU) 的產品管理總監。Michal 在 Juniper Networks 工作超過 13 年。在目前的職位之前，他曾擔任 DC BU 的技術行銷工程師 (TME) 和 Juniper 的技術解決方案顧問。在這些角色中，他負責大型企業和聯邦網路的數據中心專案，並與 Tier 2 雲端和電信雲服務提供商密切合作。在加入 Juniper 之前，他在 Orange、FT R&D 和 TPSA Polpak 工程部門工作了約 10 年。Michal 畢業於 Wroclaw 科學與技術大學電子與電信系，獲得工程碩士學位。他還擁有巴黎索邦商學院的 MBA，並且是 JNCIE-DC#523，還持有來自舊金山產品學校的 PEC、PLC 和 PMC 認證。

**Himanshu Tambakuwala** 是一位成就卓越的網路專家和認證技術架構師，其經驗涵蓋整個產品生命週期——從實際工程到產品策略。他是數據中心和服務提供商技術的 JNCIE 持有者，並且是一位擁有四項已授權技術專利和兩項正在申請中的專利的發明家。作為 Juniper Networks 的產品經理，Himanshu 在定義驅動尖端 AI/ML 數據中心的網路架構功能路線圖方面發揮了重要作用。

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