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.
<ASIN:1788996240>
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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