Start Learning CUDA for Deep Learning
Following Mesut Oezdil’s “Zero to CUDA” journey?
Get Chapter 2 of CUDA for Deep Learning, a step-by-step guide to real CUDA performance, plus a discount code for the full book.
This Is For You if you are:
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Transitioning into GPU computing or CUDA
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Working with Kubernetes, ML infrastructure, or performance systems
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Following Mesut’s learning journey
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Looking for practical, real-world explanations
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This chapter is your next step.
What You’ll Learn
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How CUDA works under the hood
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GPU execution model (threads, blocks, memory)
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How to think in parallel for deep learning
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Foundations needed before writing real CUDA code
Download the Free Chapter
About the book
CUDA for Deep Learning shows you how to work within the CUDA ecosystem, from your first kernel to implementing advanced LLM features like Flash Attention. You’ll learn to profile with Nsight Compute, identify bottlenecks, and understand why each optimization works. By solving problems at multiple levels of abstraction, you’ll develop a deep understanding of CUDA, along with a practical mastery of kernel-building skills. Written for the latest NVIDIA hardware, the book builds a deep understanding of CUDA fundamentals that will stay relevant as chips upgrade and evolve.