CUDA Fortran for Scientists and Engineers: Best Practices for Efficient CUDA Fortran Programming

by Gregory Ruetsch, Massimiliano Fatica

Overview

CUDA Fortran for Scientists and Engineers: Best Practices for Efficient CUDA Fortran Programming 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. In order to add CUDA Fortran to existing Fortran codes, they explain 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 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.

This second edition provides much needed updates on how to efficiently program GPUs in CUDA Fortran. It can be used either as a tutorial on GPU programming in CUDA Fortran as well as a reference text.

Product Details

ISBN-13:	9780443219771
Publisher:	Elsevier Science
Publication date:	07/16/2024
Edition description:	2nd ed.
Pages:	350
Product dimensions:	7.50(w) x 9.25(h) x (d)

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 Director of the HPC Benchmarking 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.

Table of Contents

PART I: CUDA Fortran Programming
1. Introduction
2. Correctness, Accuracy, and Debugging
3. Performance Measurements and Metrics
4. Synchronization
5. Optimization
6. Multi-GPU Programming
7. Porting Tips and Techniques
8. Interfacing with CUDA C, OpenACC, and CUDA Libraries

PART II Case Studies
9. Monte Carlo Method
10. Finite Difference Method
11. Applications of the Fast Fourier TransformRay Tracing

What People are Saying About This

From the Publisher

An insider’s guide to CUDA Fortran from key members of the development team.

Editorial Reviews

"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

From the Publisher