Items related to Designing NVIDIA AI Infrastructure: GPU compute, networking,...
Designing NVIDIA AI Infrastructure: GPU compute, networking, orchestration, and security in NVIDIA's stack, explained - Softcover
Synopsis
Navigate NVIDIA's enterprise AI infrastructure with confidence, from GPUs and data movement to orchestration, security, monitoring, edge systems, and model serving.
Key Features
- Build career-relevant knowledge of the NVIDIA AI infrastructure stack
- Make informed architecture decisions for performance, scalability, security, and cost
- Learn through practical configurations, deployment patterns, and enterprise case studies
Book Description
Designing NVIDIA AI Infrastructure is a concise reference guide for professionals who want to develop career-relevant knowledge of GPU-powered platforms without working through a lengthy manual.
The book explains how CPUs, GPUs, DPUs, storage, networking, software, and orchestration combine to support AI workloads. You will explore MIG and vGPU resource models, Kubernetes and Slurm scheduling, data pipelines, performance profiling, monitoring, TensorRT optimization, multi-tenant security, and governance. You will also learn how NVIDIA Jetson and Orin support edge AI and how NGC and Triton Inference Server contribute to model deployment and scalable serving.
Selected commands, configuration examples, architecture diagrams, and enterprise scenarios connect these technologies to operational contexts. By the end, you will be able to discuss the NVIDIA AI infrastructure stack with greater confidence, evaluate common design choices and bottlenecks, and use the book as a quick reference when planning cloud, on-premises, hybrid, and edge AI environments.
What you will learn
- Understand what MIG and vGPU isolate and what they don't
- Distinguish RBAC, network policy, and encryption's separate roles
- See how storage, NVLink, and InfiniBand affect GPU utilization
- Recognize where Kubernetes tools' responsibilities stop
- Understand how GDPR, HIPAA, and FedRAMP shape AI infrastructure controls and evidence
- Use GPU profiling and telemetry data to investigate bottlenecks
- Learn how NGC, Triton, and ensembles fit a serving pipeline
- Compare on-prem, cloud, and hybrid AI cluster trade-offs
Who this book is for
This book is for infrastructure engineers, ML and MLOps engineers, solutions architects, and technical leads who need a reliable mental model of NVIDIA’s AI infrastructure stack before designing, evaluating, or securing a GPU platform. It also suits professionals moving into AI infrastructure roles. Familiarity with Linux, containers, networking, cloud computing, or Kubernetes is helpful; advanced model-development knowledge and access to enterprise GPU hardware are not required.
Table of Contents
- Foundations of AI Infrastructure
- GPU Resource Management and Virtualization
- Storage, Networking, and Data Pipelines for AI
- AI Cluster Orchestration and Scalability
- Performance Optimization and Monitoring
- Security, Compliance, and Data Governance
- Edge AI Infrastructure and Integration
- NGC, Triton Inference Server, and Deployment
- Real-World AI Infrastructure and Enterprise Workflows
"synopsis" may belong to another edition of this title.
About the Author
Vivian Aranha is an AI educator, technology leader, and founder of School of AI, with over 20 years of industry experience. He earned a Bachelor's degree in Information Technology in 2004 and a Master's degree in Computer Science in 2006. His career spans web technologies, mobile app development for iOS and Android, blockchain solutions, and AI systems and applications. Vivian has worked with Fortune 500 organizations, including The Washington Post, Delta Air Lines, and IBM. An instructor since 2009, he has trained professionals worldwide and now teaches AI globally. His courses have attracted over 2.5 million enrollments, with more than 500,000 students learning through School of AI, Udemy, Skool, and Maven.
"About this title" may belong to another edition of this title.
Search results for Designing NVIDIA AI Infrastructure: GPU compute, networking,...
Stock Image
Designing NVIDIA AI Infrastructure (Paperback)
Published by
Packt Publishing Limited, Birmingham, 2026
ISBN 10: 1808080130
ISBN 13: 9781808080135
New
Paperback
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. Navigate NVIDIA's enterprise AI infrastructure with confidence, from GPUs and data movement to orchestration, security, monitoring, edge systems, and model serving.Key FeaturesBuild career-relevant knowledge of the NVIDIA AI infrastructure stackMake informed architecture decisions for performance, scalability, security, and costLearn through practical configurations, deployment patterns, and enterprise case studiesBook DescriptionDesigning NVIDIA AI Infrastructure is a concise reference guide for professionals who want to develop career-relevant knowledge of GPU-powered platforms without working through a lengthy manual.The book explains how CPUs, GPUs, DPUs, storage, networking, software, and orchestration combine to support AI workloads. You will explore MIG and vGPU resource models, Kubernetes and Slurm scheduling, data pipelines, performance profiling, monitoring, TensorRT optimization, multi-tenant security, and governance. You will also learn how NVIDIA Jetson and Orin support edge AI and how NGC and Triton Inference Server contribute to model deployment and scalable serving.Selected commands, configuration examples, architecture diagrams, and enterprise scenarios connect these technologies to operational contexts. By the end, you will be able to discuss the NVIDIA AI infrastructure stack with greater confidence, evaluate common design choices and bottlenecks, and use the book as a quick reference when planning cloud, on-premises, hybrid, and edge AI environments.What you will learnUnderstand what MIG and vGPU isolate and what they don'tDistinguish RBAC, network policy, and encryption's separate rolesSee how storage, NVLink, and InfiniBand affect GPU utilizationRecognize where Kubernetes tools' responsibilities stopUnderstand how GDPR, HIPAA, and FedRAMP shape AI infrastructure controls and evidenceUse GPU profiling and telemetry data to investigate bottlenecksLearn how NGC, Triton, and ensembles fit a serving pipelineCompare on-prem, cloud, and hybrid AI cluster trade-offsWho this book is forThis book is for infrastructure engineers, ML and MLOps engineers, solutions architects, and technical leads who need a reliable mental model of NVIDIAs AI infrastructure stack before designing, evaluating, or securing a GPU platform. It also suits professionals moving into AI infrastructure roles. Familiarity with Linux, containers, networking, cloud computing, or Kubernetes is helpful; advanced model-development knowledge and access to enterprise GPU hardware are not required. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781808080135
Stock Image
Designing NVIDIA AI Infrastructure: GPU compute, networking, orchestration, and security in NVIDIA's stack, explained
Seller: California Books, Miami, FL, U.S.A.
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # I-9781808080135
Stock Image
Designing NVIDIA AI Infrastructure
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # L2-9781808080135
Buy New
£ 43.64
£ 4.16 shipping
Ships from United Kingdom to U.S.A.
Ships from United Kingdom to U.S.A.
Quantity: Over 20 available
Stock Image
Designing NVIDIA AI Infrastructure: GPU compute, networking, orchestration, and security in NVIDIA's stack, explained
Print on DemandSeller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days. Seller Inventory # C9781808080135
Buy New
£ 49.47
£ 16.01 shipping
Ships from United Kingdom to U.S.A.
Ships from United Kingdom to U.S.A.
Quantity: Over 20 available
Stock Image
Designing NVIDIA AI Infrastructure (Paperback)
Published by
Packt Publishing Limited, Birmingham, 2026
ISBN 10: 1808080130
ISBN 13: 9781808080135
New
Paperback
Seller: CitiRetail, Stevenage, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. Navigate NVIDIA's enterprise AI infrastructure with confidence, from GPUs and data movement to orchestration, security, monitoring, edge systems, and model serving.Key FeaturesBuild career-relevant knowledge of the NVIDIA AI infrastructure stackMake informed architecture decisions for performance, scalability, security, and costLearn through practical configurations, deployment patterns, and enterprise case studiesBook DescriptionDesigning NVIDIA AI Infrastructure is a concise reference guide for professionals who want to develop career-relevant knowledge of GPU-powered platforms without working through a lengthy manual.The book explains how CPUs, GPUs, DPUs, storage, networking, software, and orchestration combine to support AI workloads. You will explore MIG and vGPU resource models, Kubernetes and Slurm scheduling, data pipelines, performance profiling, monitoring, TensorRT optimization, multi-tenant security, and governance. You will also learn how NVIDIA Jetson and Orin support edge AI and how NGC and Triton Inference Server contribute to model deployment and scalable serving.Selected commands, configuration examples, architecture diagrams, and enterprise scenarios connect these technologies to operational contexts. By the end, you will be able to discuss the NVIDIA AI infrastructure stack with greater confidence, evaluate common design choices and bottlenecks, and use the book as a quick reference when planning cloud, on-premises, hybrid, and edge AI environments.What you will learnUnderstand what MIG and vGPU isolate and what they don'tDistinguish RBAC, network policy, and encryption's separate rolesSee how storage, NVLink, and InfiniBand affect GPU utilizationRecognize where Kubernetes tools' responsibilities stopUnderstand how GDPR, HIPAA, and FedRAMP shape AI infrastructure controls and evidenceUse GPU profiling and telemetry data to investigate bottlenecksLearn how NGC, Triton, and ensembles fit a serving pipelineCompare on-prem, cloud, and hybrid AI cluster trade-offsWho this book is forThis book is for infrastructure engineers, ML and MLOps engineers, solutions architects, and technical leads who need a reliable mental model of NVIDIAs AI infrastructure stack before designing, evaluating, or securing a GPU platform. It also suits professionals moving into AI infrastructure roles. Familiarity with Linux, containers, networking, cloud computing, or Kubernetes is helpful; advanced model-development knowledge and access to enterprise GPU hardware are not required. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781808080135
Buy New
£ 47.99
£ 37 shipping
Ships from United Kingdom to U.S.A.
Ships from United Kingdom to U.S.A.
Quantity: 1 available
Stock Image
Designing NVIDIA AI Infrastructure : GPU compute, networking, orchestration, and security in NVIDIA's stack, explained
Print on DemandSeller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering. Seller Inventory # 9781808080135
Stock Image
Designing NVIDIA AI Infrastructure (Paperback)
Published by
Packt Publishing Limited, Birmingham, 2026
ISBN 10: 1808080130
ISBN 13: 9781808080135
New
Paperback
Seller: AussieBookSeller, Truganina, VIC, Australia
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. Navigate NVIDIA's enterprise AI infrastructure with confidence, from GPUs and data movement to orchestration, security, monitoring, edge systems, and model serving.Key FeaturesBuild career-relevant knowledge of the NVIDIA AI infrastructure stackMake informed architecture decisions for performance, scalability, security, and costLearn through practical configurations, deployment patterns, and enterprise case studiesBook DescriptionDesigning NVIDIA AI Infrastructure is a concise reference guide for professionals who want to develop career-relevant knowledge of GPU-powered platforms without working through a lengthy manual.The book explains how CPUs, GPUs, DPUs, storage, networking, software, and orchestration combine to support AI workloads. You will explore MIG and vGPU resource models, Kubernetes and Slurm scheduling, data pipelines, performance profiling, monitoring, TensorRT optimization, multi-tenant security, and governance. You will also learn how NVIDIA Jetson and Orin support edge AI and how NGC and Triton Inference Server contribute to model deployment and scalable serving.Selected commands, configuration examples, architecture diagrams, and enterprise scenarios connect these technologies to operational contexts. By the end, you will be able to discuss the NVIDIA AI infrastructure stack with greater confidence, evaluate common design choices and bottlenecks, and use the book as a quick reference when planning cloud, on-premises, hybrid, and edge AI environments.What you will learnUnderstand what MIG and vGPU isolate and what they don'tDistinguish RBAC, network policy, and encryption's separate rolesSee how storage, NVLink, and InfiniBand affect GPU utilizationRecognize where Kubernetes tools' responsibilities stopUnderstand how GDPR, HIPAA, and FedRAMP shape AI infrastructure controls and evidenceUse GPU profiling and telemetry data to investigate bottlenecksLearn how NGC, Triton, and ensembles fit a serving pipelineCompare on-prem, cloud, and hybrid AI cluster trade-offsWho this book is forThis book is for infrastructure engineers, ML and MLOps engineers, solutions architects, and technical leads who need a reliable mental model of NVIDIAs AI infrastructure stack before designing, evaluating, or securing a GPU platform. It also suits professionals moving into AI infrastructure roles. Familiarity with Linux, containers, networking, cloud computing, or Kubernetes is helpful; advanced model-development knowledge and access to enterprise GPU hardware are not required. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9781808080135
Seller Image
Designing NVIDIA AI Infrastructure | GPU compute, networking, orchestration, and security in NVIDIA's stack, explained
Print on DemandSeller: preigu, Osnabrück, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Designing NVIDIA AI Infrastructure | GPU compute, networking, orchestration, and security in NVIDIA's stack, explained | Vivian Aranha | Taschenbuch | Englisch | 2026 | Packt Publishing | EAN 9781808080135 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Seller Inventory # 136397360