2014年02月08日 星期六 09:01
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.
Table of Contents
Part I: CUDA Fortran Programming
Chapter 1. Introduction
Chapter 2. Performance Measurement and Metrics
Chapter 3. Optimization
Chapter 4. Multi-GPU Programming
Part II: Case Studies
Chapter 5. Monte Carlo Method
Chapter 6. Finite Difference Method
Chapter 7. Applications of Fast Fourier Transform
Part III: Appendices
Appendix A. Tesla Specifications
Appendix B. System and Environment Management
Appendix C. Calling CUDA C from CUDA Fortran
Appendix D. Source Code
2014年02月08日 星期六 09:06
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