GPU-Powered Deep Learning by Zane Cortez
Estimated delivery 3-12 business days
Format Paperback
Condition Brand New
Description 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.
Details
- ISBN-13 9798269570686
- Title GPU-Powered Deep Learning
- Author Zane Cortez
- Format Paperback
- Year 2025
- Pages 128
- Publisher Independently Published
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