Gregory Ruetsch - CUDA Fortran for Scientists and Engineers Best Practices for Efficient CUDA Fortran Programming
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First Edition
Massimiliano Fatica
Gregory Ruetsch
NVIDIA Corporation, Santa Clara, CA
Acquiring Editor:Todd Green
Development Editor:Lindsay Lawrence
Project Manager:Punithavathy Govindaradjane
Designer:Matthew Limbert
Morgan Kaufmann is an imprint of Elsevier
225 Wyman Street, Waltham, MA 02451, USA
Copyright 2014 Gregory Ruetsch/NVIDIA Corporation and Massimiliano Fatica/NVIDIA Corporation. Published by Elsevier Inc. All rights reserved.
No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publishers permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions.
This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein).
Notices
Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary.
Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility.
To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein.
Library of Congress Cataloging-in-Publication Data
Ruetsch, Gregory.
CUDA Fortran for scientists and engineers : best practices for efficient CUDA Fortran programming / Gregory Ruetsch, Massimiliano Fatica.
pages cm
Includes bibliographical references and index.
ISBN 978-0-12-416970-8 (alk. paper)
1. FORTRAN (Computer program language) I. Fatica, Massimiliano. II. Title. III. Title: Best practices for efficient CUDA Fortran programming.
QA76.73.F25R833 2013
005.131--dc23
2013022226
British Library Cataloguing-in-Publication Data
A catalogue record for this book is available from the British Library
ISBN: 978-0-12-416970-8
Printed and bound in the United States of America
14 15 16 17 18 10 9 8 7 6 5 4 3 2 1
For information on all MK publications visit our website at www.mkp.com
To Fortran programmers, who know a good thing when they see it.
Writing this book has been an enjoyable and rewarding experience for us, largely due to the interactions with the people who helped shape the book into the form you have before you. There are many people who have helped with this book, both directly and indirectly, and at the risk of leaving someone out we would like to thank the following people for their assistance.
Of course, a book on CUDA Fortran would not be possible without CUDA Fortran itself, and we would like to thank The Portland Group (PGI), especially Brent Leback and Michael Wolfe, for literally giving us something to write about. Working with PGI on CUDA Fortran has been a delightful experience.
The authors often reflect on how computations used in their theses, which required many, many hours on large-vector machines of the day, can now run on an NVIDIA graphics processing unit (GPU) in less time than it takes to get a cup of coffee. We would like to thank those at NVIDIA who helped enable this technological breakthrough. We would like to thank past and present members of the CUDA software team, especially Philip Cuadra, Mark Hairgrove, Stephen Jones, Tim Murray, and Joel Sherpelz for answering the many questions we asked them.
Much of the material in this book grew out of collaborative efforts in performance-tuning applications. We would like to thank our collaborators in such efforts, including Norbert Juffa, Patrick Legresley, Paulius Micikevicius, and Everett Phillips.
Many people reviewed the manuscript for this book at various stages in its development, and we would like to thank Roberto Gomperts, Mark Harris, Norbert Juffa, Brent Leback, and Everett Phillips for their comments and suggestions.
We would like to thank Ian Buck for allowing us to spend time at work on this endeavor, and we would like to thank our families for their understanding while we also worked at home.
Finally, we would like to thank all of our teachers. They enabled us to write this book, and we hope in some way that by doing so, we have continued the chain of helping others.
This document is intended for scientists and engineers who develop or maintain computer simulations and applications in Fortran and who would like to harness the parallel processing power of graphics processing units (GPUs) to accelerate their code. The goal here is to provide the reader with the fundamentals of GPU programming using CUDA Fortran as well as some typical examples, without having the task of developing CUDA Fortran code become an end in itself.
The CUDA architecture was developed by NVIDIA to allow use of the GPU for general-purpose computing without requiring the programmer to have a background in graphics. There are many ways to access the CUDA architecture from a programmers perspective, including through C/C++ from CUDA C or through Fortran using The Portland Groups (PGIs) CUDA Fortran. This document pertains to the latter approach. PGIs CUDA Fortran should be distinguished from the PGI Accelerator and OpenACC Fortran interfaces to the CUDA architecture, which are directive-based approaches to using the GPU. CUDA Fortran is simply the Fortran analog to CUDA C.
The reader of this book should be familiar with Fortran 90 concepts, such as modules, derived types, and array operations. For those familiar with earlier versions of Fortran but looking to upgrade to a more recent version, there are several excellent books that cover this material (e.g., Metcalf, 2011). Some features introduced in Fortran 2003 are used in this book, but these concepts are explained in detail. Although this book does assume some familiarity with Fortran 90, no experience with parallel programming (on the GPU or otherwise) is required. Part of the appeal of parallel programming on GPUs using CUDA is that the programming model is simple and novices can get parallel code up and running very quickly.
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