Gregory Ruetsch, Massimiliano Fatica

CUDA Fortran for Scientists and Engineers (eBook, ePUB)

Best Practices for Efficient CUDA Fortran Programming

• Format: ePub

Produktbeschreibung

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

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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 338
• Erscheinungstermin: 11. September 2013
• Englisch
• ISBN-13: 9780124169722
• Artikelnr.: 39865879

Autorenporträt

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.

Inhaltsangabe

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