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GPU Programming with C++ and CUDA

GPU Programming with C++ and CUDA

By : Paulo Motta
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GPU Programming with C++ and CUDA

GPU Programming with C++ and CUDA

By: Paulo Motta

Overview of this book

Written by Paulo Motta, a senior researcher with decades of experience, 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 and provides practical advice on how to think about and utilize it effectively. Starting with a basic GPU program, you then gain 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, and offers practical insights into optimizing resource usage for efficient execution. In the final section, you will explore advanced topics such as utilizing CUDA streams. You will also learn how to package and distribute GPU-accelerated libraries for the Python ecosystem, extending the reach and impact of your work. Combining expert insight with real-world problem solving, this book is a valuable resource for developers and researchers aiming to harness the full potential of GPU computing. The blend of theoretical foundations, practical programming techniques, and advanced optimization strategies it offers is sure to help you succeed in the fast-evolving field of GPU programming.
Table of Contents (17 chapters)
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1
Understanding Where We Are Heading
6
Bring It On!
10
Moving Forward
15
Other Books You May Enjoy
16
Index

Hello CUDA

Every programming journey starts with a simple ‘Hello World’ program, and with all the features that GPUs provide to the developer, it is the best approach to explaining how things really work. As with any intricate topic, there is a myriad of detail that complicates GPU programming. If we had to know it all before writing any code it would be tiresome and boring. To avoid this, we will adopt an incremental approach. We will learn a little about how to program our GPU devices, and we will have to believe in a little magic here and there until we grasp all the concepts.

We’ll start with a superficial understanding of what makes a GPU program, and then move on to a fully functional toy program as a milestone in terms of using our GPU device. At the end of the chapter, we will wrap up with a section on how to use the default NVIDIA example of querying a device and some discussion of the main details that can be inspected from the execution environment...

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GPU Programming with C++ and CUDA
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