GPU-Powered Deep Learning: Mastering Parallel Computing for High-Performance AI: A Practical Guide to CUDA, Optimization, and Scalable Model Deployment - Brossura

Cortez, Zane

Brossura

ISBN 13: 9798269570686

Casa editrice: Independently published, 2025

Riassunto

GPU-Powered Deep Learning: Unlocking High-Performance AI with Parallel Computing and CUDA is a comprehensive guide for AI engineers, developers, and data scientists seeking to master GPU-accelerated deep learning. Authored by a seasoned AI expert, this book takes you on a journey from the fundamentals of CUDA programming to advanced techniques for scaling and deploying high-performance AI models. Through clear explanations, practical examples, and production-ready code, you’ll learn to harness the power of GPUs to build, optimize, and deploy cutting-edge AI systems.
The book begins with an introduction to GPU computing and CUDA, providing hands-on skills to write custom kernels and optimize memory usage. It progresses to leveraging high-level frameworks like PyTorch and TensorFlow, exploring optimization techniques such as memory coalescing and mixed-precision training. You’ll master multi-GPU and distributed systems, learning to scale models across clusters with tools like Horovod and DALI. Finally, the book covers deploying optimized models for low-latency inference, integrating with modern AI ecosystems like LangChain and vector databases.
With real-world case studies from healthcare, finance, and e-commerce, this book bridges theory and practice, offering actionable insights for building scalable, efficient AI solutions. Whether you’re training massive language models, deploying real-time vision systems, or integrating with agentic workflows, this book equips you with the expertise to excel in the fast-evolving world of AI. Packed with annotated code, architectural patterns, and ethical considerations, it’s an essential resource for professionals aiming to push the boundaries of AI performance.

Dettagli dell'edizione

• Editore: Independently published
• Data di pubblicazione: 2025
• Lingua: Inglese
• ISBN 13: 9798269570686
• Rilegatura: Copertina flessibile
• Numero di pagine: 127
• Contatto del produttore: non disponibile
• Persona responsabile: non disponibile