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Bandyopadhyay - Hands-On GPU Computing with Python

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Explore the capabilities of GPUs for solving high performance computational problems Key Features Understand effective synchronization strategies for faster processing using GPUs Write parallel processing scripts with PyCuda and PyOpenCL Learn to use CUDA libraries such as CuDNN for deep learning on GPUs Book Description GPUs are proving to be excellent general purpose-parallel computing solutions for high-performance tasks such as deep learning and scientific computing. This book will be your guide to getting started with GPU computing. It begins by introducing GPU computing and explaining the GPU architecture and programming models. You will learn, by example, how to perform GPU programming with Python, and look at using integrations such as PyCUDA, PyOpenCL, CuPy, and Numba with Anaconda for various tasks such as machine learning and data mining. In addition to this, you will get to grips with GPU workflows, management, and deployment using modern containerization solutions. Toward the end of the book, you will get familiar with the principles of distributed computing for training machine learning models and enhancing efficiency and performance. By the end of this book, you will be able to set up a GPU ecosystem for running complex applications and data models that demand great processing capabilities, and be able to efficiently manage memory to compute your application effectively and quickly. What you will learn Utilize Python libraries and frameworks for GPU acceleration Set up a GPU-enabled programmable machine learning environment on your system with Anaconda Deploy your machine learning system on cloud containers with illustrated examples Explore PyCUDA and PyOpenCL and compare them with platforms such as CUDA, OpenCL, and ROCm. Perform data mining tasks with machine learning models on GPUs Extend your knowledge of GPU computing in scientific applications Who this book is for Data scientists, machine learning enthusiasts, or professionals who want to get started with GPU computation and perform the complex tasks with low-latency will find this book useful. Intermediate knowledge of Python programming is assumed.

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Bandyopadhyay
Hands-On GPU Computing with Python

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Hands-On GPU Computing with Python Explore the capabilities of GPUs for - photo 1
Hands-On GPU Computing with Python
Explore the capabilities of GPUs for solving high performance
computational problems
Avimanyu Bandyopadhyay

BIRMINGHAM - MUMBAI Hands-On GPU Computing with Python Copyright 2019 Packt - photo 2

BIRMINGHAM - MUMBAI
Hands-On GPU Computing with Python

Copyright 2019 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

Commissioning Editor: Pavan Ramchandani
Acquisition Editor: Heramb Bhavsar
Content Development Editor: Shubham Bhattacharya
Technical Editor: Rudolph Almeida
Copy Editor: Safis Editing
Project Coordinator: Nusaiba Ansari
Proofreader: Safis Editing
Indexer: Pratik Shirodkar
Graphics: Jisha Chirayil
Production Coordinator: Arvindkumar Gupta

First published: May 2019

Production reference: 1130519

Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham
B3 2PB, UK.

ISBN 978-1-78934-107-2

www.packtpub.com


I dedicate this book to my late maternal grandfather, Shri Sudhir Kumar Halder.
He was a great human being at heart and an amazing trigonometrician. I wouldn't have been able to write this book without his constant encouragement in the early days of my life, especially in mathematics, which is the foundation of computing.
I extend my love and thanks to my mother, Smt Uma Bandyopadhyay, who has been so constantly supportive throughout my journey of life, and also now as a researcher. I also extend my love and thanks to my father, Shri Amitava Bandyopadhyay, for being so supportive while
I was writing this book, and for my new lab, which was very helpful during the book's development. I'm forever indebted to my alma mater, PVP Siddhartha Institute of Technology.
I would especially like to thank Christel Pilz, a loving grandma who has always been by my side to encourage and support me so selflessly during all my creative endeavors, especially when deploying the AMD Radeon VII GPU at my lab, which contributed to the book.
I would also like to thank my fellow tech enthusiasts, Siddhant Pati and Amlan Madhab Panigrahi, for being so supportive throughout my journey in PhD research. I would also like to thank my researcher friend from Peru, Antony Brayan Campos Salazar.
Finally, I extend my sincere gratitude and thanks to my PhD mentor and advisor, Professor
Dr. Dipankar Chaudhuri, for being so continuously supportive throughout the development of this book and all of my research endeavors. I'm really very grateful to him for providing a flexible framework for writing this book while pursuing my PhD.
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Contributors
About the author

Avimanyu Bandyopadhyay is currently pursuing a PhD degree in Bioinformatics based on applied GPU computing in Computational Biology at Heritage Institute of Technology, Kolkata, India. Since 2014, he developed a keen interest in GPU computing, and used CUDA for his master's thesis. He has experience as a systems administrator as well, particularly on the Linux platform.

Avimanyu is also a scientific writer, technology communicator, and a passionate gamer. He has published technical writing on open source computing and has actively participated in NVIDIA's GPU computing conferences since 2016. A big-time Linux fan, he strongly believes in the significance of Linux and an open source approach in scientific research. Deep learning with GPUs is his new passion!

I'm very thankful to Professor Rumpa Hazra, Teacher and Master's thesis mentor for her kind guidance, Mainak Bhattacharjee, Technical Assistant at my academic laboratory for his creative microbiology inputs and Argha Mandal, my co-researcher. Thank you Jithu Nair, Yumlembam Rupert Anand, Nilanjan Mukherjee, and Rakhi Chatterjee, for your constant support while I was building my own GPU Computing Laboratory. I would also like to thank Shubham Bhattacharya, my content editor, and the entire team at Packt, for providing the opportunity to create this book and bring the author out of me.
About the reviewer

Amlan Madhab Panigrahi is a BTech graduate who has just recently ventured into the IT industry. An experienced gaming/tech blogger by heart, he also happens to be a GPU computing and machine learning enthusiast. He loves and promotes community-driven learning by organizing technical events and workshops. Cosplaying as popular gaming characters also happens to be one of his interests.

When not gaming or developing something, you will find him sampling wonderful delicacies or traveling. This technical nerd is currently working at Accenture as an Application Development Associate.

I am thankful for Mr. Avimanyu's innovative and authentic work in educating the community about GPU computing and its advantages. The author has put a lot of effort and care into making the content simple and understandable. It was purely due to him that I was able to delve into the world of GPU computing. I would like to thank both him and Packt for making me a part of such an amazing project.
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