Read Anywhere and on Any Device!

Special Offer | $0.00

Join Today And Start a 30-Day Free Trial and Get Exclusive Member Benefits to Access Millions Books for Free!

Create Free Account

Quick and Easy Sign Up!

It takes less then 1 minute to sign up, then you can enjoy Unlimited eBooks.

Sign Up Browse

Read Anywhere and on Any Device!

  • Download on iOS
  • Download on Android
  • Download on iOS

AI Systems Performance Engineering: Optimizing Model Training and Inference Workloads with GPUs, CUDA, and PyTorch

Chris Fregly
4.9/5 (34856 ratings)
Read Now Download Now ⏭ listen AudioBook
Description:Elevate your AI system performance capabilities with this definitive guide to maximizing efficiency across every layer of your AI infrastructure. In today's era of ever-growing generative models, AI Systems Performance Engineering provides engineers, researchers, and developers with a hands-on set of actionable optimization strategies. Learn to co-optimize hardware, software, and algorithms to build resilient, scalable, and cost-effective AI systems that excel in both training and inference. Authored by Chris Fregly, a performance-focused engineering and product leader, this resource transforms complex AI systems into streamlined, high-impact AI solutions.Inside, you'll discover step-by-step methodologies for fine-tuning GPU CUDA kernels, PyTorch-based algorithms, and multinode training and inference systems. You'll also master the art of scaling GPU clusters for high performance, distributed model training jobs, and inference servers. The book ends with a 175+-item checklist of proven, ready-to-use optimizations.Codesign and optimize hardware, software, and algorithms to achieve maximum throughput and cost savingsImplement cutting-edge inference strategies that reduce latency and boost throughput in real-world settings Utilize industry-leading scalability tools and frameworksProfile, diagnose, and eliminate performance bottlenecks across complex AI pipelinesIntegrate full stack optimization techniques for robust, reliable AI system performanceWe have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with AI Systems Performance Engineering: Optimizing Model Training and Inference Workloads with GPUs, CUDA, and PyTorch. To get started finding AI Systems Performance Engineering: Optimizing Model Training and Inference Workloads with GPUs, CUDA, and PyTorch, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.
Pages
—
Format
PDF, EPUB & Kindle Edition
Publisher
—
Release
—
ISBN

AI Systems Performance Engineering: Optimizing Model Training and Inference Workloads with GPUs, CUDA, and PyTorch

Chris Fregly
4.4/5 (1290744 ratings)
Read Now Download now ⏭ listen AudioBook
Description: Elevate your AI system performance capabilities with this definitive guide to maximizing efficiency across every layer of your AI infrastructure. In today's era of ever-growing generative models, AI Systems Performance Engineering provides engineers, researchers, and developers with a hands-on set of actionable optimization strategies. Learn to co-optimize hardware, software, and algorithms to build resilient, scalable, and cost-effective AI systems that excel in both training and inference. Authored by Chris Fregly, a performance-focused engineering and product leader, this resource transforms complex AI systems into streamlined, high-impact AI solutions.Inside, you'll discover step-by-step methodologies for fine-tuning GPU CUDA kernels, PyTorch-based algorithms, and multinode training and inference systems. You'll also master the art of scaling GPU clusters for high performance, distributed model training jobs, and inference servers. The book ends with a 175+-item checklist of proven, ready-to-use optimizations.Codesign and optimize hardware, software, and algorithms to achieve maximum throughput and cost savingsImplement cutting-edge inference strategies that reduce latency and boost throughput in real-world settings Utilize industry-leading scalability tools and frameworksProfile, diagnose, and eliminate performance bottlenecks across complex AI pipelinesIntegrate full stack optimization techniques for robust, reliable AI system performanceWe have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with AI Systems Performance Engineering: Optimizing Model Training and Inference Workloads with GPUs, CUDA, and PyTorch. To get started finding AI Systems Performance Engineering: Optimizing Model Training and Inference Workloads with GPUs, CUDA, and PyTorch, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.
Pages
—
Format
PDF, EPUB & Kindle Edition
Publisher
—
Release
—
ISBN

More Books

Generative AI on AWS: Building Context-Aware Multimodal Reasoning Applications

Generative AI on AWS: Building Context-Aware Multimodal Reasoning Applications

4.4/5 (1,282,506 ratings)

Data Science on AWS

Data Science on AWS

4.2/5 (4,466 ratings)

IA generativa en AWS: Creación de aplicaciones multimodales (Spanish Edition)

IA generativa en AWS: Creación de aplicaciones multimodales (Spanish Edition)

4.1/5 (1,751 ratings)

IA generativa en AWS: Creación de aplicaciones multimodales

IA generativa en AWS: Creación de aplicaciones multimodales

4.5/5 (743 ratings)

生成式AI入门与AWS实战 (美)克里斯·弗雷格利,(德)安特耶·巴特,(美)舍尔比·艾根布罗德 著 生成式AI技术兴趣小组 译 人民邮电出版社

生成式AI入门与AWS实战 (美)克里斯·弗雷格利,(德)安特耶·巴特,(美)舍尔比·艾根布罗德 著 生成式AI技术兴趣小组 译 人民邮电出版社

4/5 (647 ratings)

Estimated Muscle Loads During Squat Exercise in Microgravity Conditions

Estimated Muscle Loads During Squat Exercise in Microgravity Conditions

4/5 (647 ratings)

4.7/5 (647 ratings)

4.6/5 (647 ratings)

4.9/5 (647 ratings)
loader