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Beschreibung
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.
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.
Über den Autor
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.
Inhaltsverzeichnis

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

Details
Erscheinungsjahr: 2024
Fachbereich: Programmiersprachen
Genre: Importe, Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: Einband - flex.(Paperback)
ISBN-13: 9780443219771
ISBN-10: 044321977X
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Ruetsch, Gregory
Fatica, Massimiliano
Auflage: 2. Auflage
Hersteller: Elsevier Science & Technology
Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de
Maße: 232 x 192 x 25 mm
Von/Mit: Gregory Ruetsch (u. a.)
Erscheinungsdatum: 16.07.2024
Gewicht: 0,878 kg
Artikel-ID: 128602713

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