Cuda Fortran for Scientists and Engineers: Best Practices for Efficient Cuda Fortran Programming. Questo articolo non è disponibile.
Lingua: inglese
Editore: Morgan Kaufmann Pub, 2024
- Brossura
- Nuovo

Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
Venditore AbeBooks dal 6 gennaio 2003
Condizione: Nuovo
EUR 120,63
Descrizione dell’articolo da parte del venditore
2nd edition. 350 pages. 7.10x0.60x5.20 inches. In Stock. This item is printed on demand.
Codice articolo __044321977X
- Titolo
- Cuda Fortran for Scientists and Engineers: Best Practices for Efficient Cuda Fortran Programming
- Autore
- Ruetsch, Gregory/ Fatica, Massimiliano
- Editore
- Morgan Kaufmann Pub
- Anno di pubblicazione
- 2024
- Condizione
- Brand New
- Rilegatura
- Paperback
- Lingua
- inglese
- ISBN 10
- 044321977X
- ISBN 13
- 9780443219771
- Edizione
- seconda edizione
- Peso dell'articolo
- 1,02 chilogrammi
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.
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Informazioni sull’autore
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.
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