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

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. 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. 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.

Price: 41.95 GBP

Location: Hillsdale, NSW

End Time: 2024-11-02T07:43:57.000Z

Shipping Cost: 130.37 GBP

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

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EAN: 9780124169708

UPC: 9780124169708

ISBN: 9780124169708

MPN: N/A

Book Title: CUDA Fortran for Scientists and Engineers: Best Pr

Item Length: 23.1 cm

Item Height: 235 mm

Item Width: 191 mm

Author: Gregory Ruetsch, Massimiliano Fatica

Publication Name: Cuda Fortran for Scientists and Engineers: Best Practices for Efficient Cuda Fortran Programming

Format: Paperback

Language: English

Publisher: Elsevier Science & Technology

Subject: Computer Science

Publication Year: 2013

Type: Textbook

Item Weight: 700 g

Number of Pages: 338 Pages

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