Written by Paulo Motta, a senior researcher with decades of experience, the book combines expert guidance with real-world problem solving. This comprehensive GPU programming book is an essential guide for leveraging the power of parallelism to accelerate your computations. The first section introduces the concept of parallelism, offering practical insights on how to think about and effectively utilize it. You will start with a basic GPU program, gaining hands-on experience in managing the device. This foundational knowledge is then expanded by parallelizing the program to illustrate how GPUs enhance performance.
The second section explores GPU architecture and implementation strategies for parallel algorithms. It offers practical insights into optimizing resource usage for efficient execution.
In the final section, you will explore advanced topics such as utilizing multiple GPUs. You will also learn how to package and distribute your GPU-accelerated libraries for the Python ecosystem, extending the reach and impact of your work.
This book is a valuable resource for developers and researchers aiming to harness the full potential of GPU computing. It offers a blend of theoretical foundations, practical programming techniques, and advanced optimization strategies to help you succeed in the fast-evolving field of GPU programming.

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Spis treści

GPU Programming with C++ and CUDA. Uncover effective techniques for writing efficient GPU-parallel C++ applications eBook -- spis treści

• 1. Introduction to Parallel Programming
• 2. Getting Started
• 3. Hello CUDA
• 4. Hello again, but in parallel
• 5. A closer look into the GPU world
• 6. Data Management and Persistence
• 7. Performance strategies
• 8. Using multiple GPUs
• 9. Exposing your code as a Python Library
• 10. Exploring the existing GPU models