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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

Sorting data

When we think of sorting, the first image that comes to mind might be the orderly rearrangement of numbers into a sequence, from smallest to largest or vice versa. But in parallel programming, sorting turns out to be much more than simply lining things up. It is a problem that involves coordination, patience, and a hefty dose of synchronization. Sorting in parallel is not simply hard — it is a challenging puzzle, where each piece needs to know what the others are doing. In this exploration, we are going to dive into a parallel sorting method called odd-even sort and see what it tells us about the unique challenges of synchronization in parallel computation.

Odd-even sort gives us an elegant yet tricky solution to sorting with multiple processors. The basic idea is that rather than having each processor work on the entire array, we set processors up to work in pairs, comparing and swapping numbers in adjacent positions. In one round we compare the elements at...

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GPU Programming with C++ and CUDA
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