Deliver to your Kindle or other device

 
 
 

Try it free

Sample the beginning of this book for free

Deliver to your Kindle or other device

Sorry, this item is not available in
Image not available for
Colour:
Image not available
 

CUDA Fortran for Scientists and Engineers: Best Practices for Efficient CUDA Fortran Programming [Kindle Edition]

Gregory Ruetsch , Massimiliano Fatica
4.5 out of 5 stars  See all reviews (2 customer reviews)

Print List Price: £42.99
Kindle Price: £36.76 includes VAT* & free wireless delivery via Amazon Whispernet
You Save: £6.23 (14%)
* Unlike print books, digital books are subject to VAT.

Free Kindle Reading App Anybody can read Kindle books—even without a Kindle device—with the FREE Kindle app for smartphones, tablets and computers.

To get the free app, enter your e-mail address or mobile phone number.

Formats

Amazon Price New from Used from
Kindle Edition £36.76  
Paperback £38.69  
Kindle Books Summer Sale
Kindle Summer Sale: Books from 99p
Browse over 600 titles from best-selling authors, including Neil Gaiman, John Grisham, Jeffrey Archer, Veronica Roth and Sylvia Day. >Shop now

Book Description

CUDA Fortran for Scientists and Engineers shows how high-performance application developers can leverage the power of GPUs using Fortran, the familiar language of scientific computing and supercomputer performance benchmarking. The authors presume no prior parallel computing experience, and cover the basics along with best practices for efficient GPU computing using CUDA Fortran.

To help you add CUDA Fortran to existing Fortran codes, the book explains how to understand the target GPU architecture, identify computationally intensive parts of the code, and modify the code to manage the data and parallelism and optimize performance. All of this is done in Fortran, without having to rewrite in another language. Each concept is illustrated with actual examples so you can immediately evaluate the performance of your code in comparison.



  • Leverage the power of GPU computing with PGI’s CUDA Fortran compiler
  • Gain insights from members of the CUDA Fortran language development team
  • Includes multi-GPU programming in CUDA Fortran, covering both peer-to-peer and message passing interface (MPI) approaches
  • Includes full source code for all the examples and several case studies
  • Download source code and slides from the book's companion website

Customers Who Bought This Item Also Bought

Page of Start over
This shopping feature will continue to load items. In order to navigate out of this carousel please use your heading shortcut key to navigate to the next or previous heading.

Product Description

Review

"This book is written for the Fortran programmer who wants to do real work on GPUs, not just stunts or demonstrations. The book has many examples, and includes introductory material on GPU programming as well as advanced topics such as data optimization, instruction optimization and multiple GPU programming. Placing the performance measurement chapter before performance optimization is key, since measurement drives the tuning and optimization process. All Fortran programmers interested in GPU programming should read this book."--Michael Wolfe, PGI Compiler Engineer

About the Author

Greg Ruetsch is a Senior Applied Engineer at NVIDIA, where he works on CUDA Fortran and performance optimization of HPC codes. He holds a Bachelor's degree in mechanical and aerospace engineering from Rutgers University and a Ph.D. in applied mathematics from Brown University. Prior to joining NVIDIA he has held research positions at Stanford University's Center for Turbulence Research and Sun Microsystems Laboratories. Massimiliano Fatica is the manager of the Tesla HPC Group at NVIDIA where he works in the area of GPU computing (high-performance computing and clusters). He holds a laurea in Aeronautical Engineering and a Phd in Theoretical and Applied Mechanics from the University of Rome "La Sapienza . Prior to joining NVIDIA, he was a research staff member at Stanford University where he worked at the Center for Turbulence Research and Center for Integrated Turbulent Simulations on applications for the Stanford Streaming Supercomputer.

Product details


More About the Authors

Discover books, learn about writers, and more.

Customer Reviews

3 star
0
2 star
0
1 star
0
4.5 out of 5 stars
4.5 out of 5 stars
Most Helpful Customer Reviews
4.0 out of 5 stars Almost accessible to a non-computer scientist 26 Jan. 2014
Format:Paperback|Verified Purchase
I was very excited to see PGI had brought Fortran to the new generation of GPU devices (well the Nvidia ones), but the PGI compiler did not prove to be very easy to use and I was especially frustrated when some of PGIs own example codes did not run on my Alienware with its two GTX560M cards.

Then out can this book and my enthusiasm is reborne!

The examples in this book, that I have tried so far, do work! The level of explanation works for me, but I fear it may be just out of reach for, say, an undergraduate interested in using GPU cards to execute code for a research project.

I applaud this book, but I have not yet worked my way through to the final sections. Well done so far!
Comment | 
Was this review helpful to you?
By S B.
Format:Kindle Edition|Verified Purchase
Make the most of CUDA on your graphics card with this great little book!
Comment | 
Was this review helpful to you?
Most Helpful Customer Reviews on Amazon.com (beta)
Amazon.com: 5.0 out of 5 stars  1 review
2 of 2 people found the following review helpful
5.0 out of 5 stars Must have book for CUDA Fortran 16 Feb. 2014
By Daniel Savage - Published on Amazon.com
Format:Paperback|Verified Purchase
I have a few thousand hours of experience working with CUDA Fortran and can say that this book is perfect for the advance and beginner CUDA Fortran programmers alike. The concepts are laid out succinctly and clearly. The book includes codes written for tests and performance feedback related to each topic with detailed discussion that will be very helpful for learning CUDA Fortran and fully understanding the CUDA GPU architectures. The book is helpful also in that it includes methods for using CUDA cards up through the Tesla K20. This was important for me as the Tesla K20 has, up until the past couple of months, had poor literature describing best practices and how to take advantage of the card's capabilities. The biggest offering this book brings to the table is that you won't have to waste time searching around online trying to find half-baked information in forums and/or papers.

I also recommend "The CUDA Handbook" as another resource to understand programming with GPUs.
Was this review helpful?   Let us know
Search Customer Reviews
Only search this product's reviews

Customer Discussions

This product's forum
Discussion Replies Latest Post
No discussions yet

Ask questions, Share opinions, Gain insight
Start a new discussion
Topic:
First post:
Prompts for sign-in
 

Search Customer Discussions
Search all Amazon discussions
   


Look for similar items by category