Learn CUDA Programming (Packt)
Friday, 25 October 2019

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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