Subtitled "A beginner's guide to GPU programming and parallel computing with CUDA 10.x and C/C++",  in this book authors Jaegeun Han and Bharatkumar Sharma explore different GPU programming methods using libraries and directives, such as OpenACC, with extension to languages such as C, C++, and Python. The book also looks at optimizing the performance of apps using CUDA programming platforms with various libraries, compiler directives (OpenACC), and other languages.

Authors: Jaegeun Han and Bharatkumar Sharma
Publisher: Packt
Date: September 2019
Pages: 508
ISBN: 978-1788996242
Print: 1788996240
Kindle: B07PTBDWV4
Audience: developers interested in Cuda
Level: Introductory/Intermediate
Category: Graphics & Games

• Understand general GPU operations and programming patterns in CUDA
• Uncover the difference between GPU programming and CPU programming
• Analyze GPU application performance and implement optimization strategies
• Explore GPU programming, profiling, and debugging tools
• Grasp parallel programming algorithms and how to implement them
• Scale GPU-accelerated applications with multi-GPU and multi-nodes
• Delve into GPU programming platforms with accelerated libraries, Python, and OpenACC
• Gain insights into deep learning accelerators in CNNs and RNNs using GPUs

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