CUDA Performance & Optimization For Beginners: A Practical Guide to Profiling, Memory Optimization, Kernel Performance, and GPU Acceleration* (CUDA Programming Series)
Language: English
Published by Independently published, 2026
- Softcover
- New
Seller: California Books, Miami, FL, U.S.A.California Books
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Condition: New
£ 19.11
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- Title
- CUDA Performance & Optimization For Beginners: A Practical Guide to Profiling, Memory Optimization, Kernel Performance, and GPU Acceleration* (CUDA Programming Series)
- Author
- Marsh, Alvin
- Publisher
- Independently published
- Publication year
- 2026
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 13
- 9798171913724
- Series
- Book 2 of 2: CUDA Programming Series
CUDA Performance & Optimization For Beginners provides a practical introduction to the principles and techniques used to analyze and improve CUDA application performance.
Building on fundamental CUDA programming concepts, the book introduces a systematic approach to performance optimization. You will learn how to measure GPU workloads, interpret profiling information, identify common performance bottlenecks, understand memory behavior, improve kernel execution, and evaluate whether an optimization actually produces meaningful results.
You will explore how to:
- Understand the fundamentals of CUDA performance
- Measure and establish meaningful performance baselines
- Profile CUDA applications and investigate bottlenecks
- Analyze kernel execution and GPU utilization
- Understand memory-access behavior and its effect on performance
- Improve global, shared, and other forms of GPU memory usage
- Reduce unnecessary data movement between CPU and GPU
- Improve kernel organization and execution efficiency
- Understand occupancy and resource utilization
- Identify common causes of CUDA performance problems
- Benchmark and validate optimization changes
- Develop a repeatable approach to CUDA performance tuning
Whether you are learning CUDA optimization for the first time, improving existing GPU applications, or developing a stronger understanding of GPU performance engineering, this book provides a practical foundation for making CUDA workloads more efficient.
Learn how to stop guessing about GPU performance—and start optimizing based on evidence.
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California Books
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