Summary
Learn distributed AI through hands-on experience with training frameworks, inference engines, and orchestration tools to build production-ready training, inference, and serving systems for modern large-scale AI.
Key Features
- Understand GPU hardware, high-speed interconnects, and parallelism strategies
- Hands-on exercises at the end of every chapter
- Learn distributed training with resource-optimized techniques
- Deploy hig…
Book Details
| ISBN-13: | 9781807301712 |
|---|---|
| ISBN-10: | 1807301710 |
| Author: | Fuheng Wu, Gang Zhao |
| Publisher: | Packt Publishing Limited |
| Imprint: | Packt Publishing Limited |
| Format: | Paperback |
| Number of Pages: | 558 |
| Release Date: | 29 June 2026 |
| Dimensions: | 191mm x 235mm |
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Fuheng Wu
Henry (Fuheng) Wu
Henry (Fuheng) Wu is a Principal Machine Learning Tech Lead at Oracle’s Generative AI organization. His expertise lies in distributed training, large-scale inference, and GPU systems.
Henry has been instrumental in delivering core components of Oracle’s Vision and Document Understanding AI services. He also co-authored a blog post for Microsoft and Oracle discussing high-performance deep learning.
His contributions extend to open-source projects such as SGLang, genai-bench, pyLLaMA, chatLLaMA, and Oracle’s HiQ observability system.
With extensive practical experience in PyTorch Distributed, DeepSpeed, Kubernetes GPU clusters, and production LLM serving, Henry is dedicated to developing practical and scalable AI systems tailored for real-world enterprise workloads.
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