GPU Programming with C++ and CUDA
Language: English
Published by Packt Publishing, 2025
- Softcover
- New
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
AbeBooks seller since June 11, 1999
Condition: New
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New Book. Shipped from UK. Established seller since 2000.
Seller Inventory # L2-9781805124542
- Title
- GPU Programming with C++ and CUDA
- Author
- Paulo Motta
- Publisher
- Packt Publishing
- Publication year
- 2025
- Condition
- New
- Binding
- PAP
- Language
- English
- ISBN 10
- 1805124544
- ISBN 13
- 9781805124542
- Item weight
- 558 grams
Learn to solve parallel problems with GPU-accelerated C++ code and create reusable libraries that can be accessed from other programming languages
Key Features
- Harness the power of GPU parallelism to accelerate real-world tasks
- Utilize CUDA streams and scale performance with custom C++ solutions
- Create reusable GPU libraries and expose them to Python seamlessly
Book Description
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.
What you will learn
- Manage GPU devices and accelerate your applications
- Apply parallelism effectively using CUDA and C++
- Choose between existing libraries and custom GPU solutions
- Package GPU code into libraries for use with Python
- Explore advanced topics such as CUDA streams
- Implement optimization strategies for resource-efficient execution
Who this book is for
C++ developers and programmers interested in accelerating applications using GPU programming will benefit from this book. It is suitable for those with solid C++ experience who want to explore high-performance computing techniques. Familiarity with operating system fundamentals will help when dealing with device memory and communication in advanced chapters.
Table of Contents
- Introduction to Parallel Programming
- Getting Started
- Hello CUDA
- Hello again, but in parallel
- A closer look into the GPU world
- Data Management and Persistence
- Performance strategies
- Using multiple GPUs
- Exposing your code as a Python Library
- Exploring the existing GPU models
"Synopsis" may belong to another edition of this title.
About the Author
Paulo Motta completed the PhD in Computer Science with an emphasis in parallel systems at PUC-Rio in 2011. Currently, Paulo Motta is a Senior Research Software Development Engineer at Microsoft and a postdoctoral researcher on quantum walks simulations with Hiperwalk at the National Scientific Computing Laboratory in Brazil. Paulo is a senior member of IEEE Computer Society with over 25 years' experience in software development and 9 years experience as a university professor.
"About the title" may belong to another edition of this title.
PBShop.store UK
Fairford, GLOS, United Kingdom
AbeBooks seller since June 11, 1999
Shipping rates from United Kingdom to U.S.A.
| Item | 10 to 20 business days | 10 to 20 business days |
|---|---|---|
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