Book Image

Learn CUDA Programming

By : Jaegeun Han, Bharatkumar Sharma
Book Image

Learn CUDA Programming

By: Jaegeun Han, Bharatkumar Sharma

Overview of this book

<p>Compute Unified Device Architecture (CUDA) is NVIDIA's GPU computing platform and application programming interface. It's designed to work with programming languages such as C, C++, and Python. With CUDA, you can leverage a GPU's parallel computing power for a range of high-performance computing applications in the fields of science, healthcare, and deep learning. </p><p> </p><p>Learn CUDA Programming will help you learn GPU parallel programming and understand its modern applications. In this book, you'll discover CUDA programming approaches for modern GPU architectures. You'll not only be guided through GPU features, tools, and APIs, you'll also learn how to analyze performance with sample parallel programming algorithms. This book will help you optimize the performance of your apps by giving insights into CUDA programming platforms with various libraries, compiler directives (OpenACC), and other languages. As you progress, you'll learn how additional computing power can be generated using multiple GPUs in a box or in multiple boxes. Finally, you'll explore how CUDA accelerates deep learning algorithms, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs). </p><p> </p><p>By the end of this CUDA book, you'll be equipped with the skills you need to integrate the power of GPU computing in your applications.</p>
Table of Contents (18 chapters)
Title Page
Dedication

About the authors

Jaegeun Han is currently working as a solutions architect at NVIDIA, Korea. He has around 9 years' experience and he supports consumer internet companies in deep learning. Before NVIDIA, he worked in system software and parallel computing developments, and application development in medical and surgical robotics fields. He obtained a master's degree in CSE from Seoul National University.

I would like to thank my wife, Kiyeon Kim, for supporting of book writing and taking care of our child. I also thank my son, Kyeol Han, for his joy and curiosity, and my parents and parents-in-law for their support. I also appreciate Simon See (NVIDIA) for supporting me in authoring this book and I'm thankful to my co-author, Bharat, for joining this challenge with me. Thanks to all NVIDIA GPU experts for sharing their knowledge and opening the new era of computing.

 

Bharatkumar Sharma obtained a master's degree in information technology from the Indian Institute of Information Technology, Bangalore. He has around 10 years of development and research experience in the domains of software architecture and distributed and parallel computing. He is currently working with NVIDIA as a senior solutions architect, South Asia.

I would like to acknowledge my mentors who helped me at different stages in my career: Jaya Panvalkar (NVIDIA), Simon See (NVIDIA), and the one and only accelerated computing rockstar, Jensen Huang (CEO NVIDIA).