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Programming massively parallel processors : a hands-on approach /

Programming Massively Parallel Processors: A Hands-on Approach, Third Edition shows both student and professional alike the basic concepts of parallel programming and GPU architecture, exploring, in detail, various techniques for constructing parallel programs. Case studies demonstrate the developme...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Kirk, David, 1960- (Autor), Hwu, Wen-mei (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Amsterdam : Morgan Kaufmann, 2016.
Edición:Third edition.
Temas:
Acceso en línea:Texto completo

MARC

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100 1 |a Kirk, David,  |d 1960-  |e author. 
245 1 0 |a Programming massively parallel processors :  |b a hands-on approach /  |c David B. Kirk and Wen-mei W. Hwu. 
250 |a Third edition. 
264 1 |a Amsterdam :  |b Morgan Kaufmann,  |c 2016. 
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504 |a Includes bibliographical references and index. 
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520 |a Programming Massively Parallel Processors: A Hands-on Approach, Third Edition shows both student and professional alike the basic concepts of parallel programming and GPU architecture, exploring, in detail, various techniques for constructing parallel programs. Case studies demonstrate the development process, detailing computational thinking and ending with effective and efficient parallel programs. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in-depth. For this new edition, the authors have updated their coverage of CUDA, including coverage of newer libraries, such as CuDNN, moved content that has become less important to appendices, added two new chapters on parallel patterns, and updated case studies to reflect current industry practices. 
505 0 |a <P><b>Part 1 -- Basic Concepts and Skills </b>1. Introduction 2. Data-Parallel Programming 3. Data Parallel Execution Models 4. Memory Hierarchy 5. Performance Considerations</p> <p><b>Part 2 -- Parallel Algorithm Patterns </b>6. Parallel Programming and Computational Thinking 7. Parallel Patterns -- Stencil Computation 8. Parallel Patterns -- Reduction Trees and Prefix Sum with an Introduction to work efficiency of parallel algorithms 9. Parallel Patterns -- Sorting with introduction to load balance considerations 10. Parallel Patterns -- Sparse Matrix-Vector Multiplication with introduction to data compression 11. Parallel Patterns -- Parallel Histogramming with introduction to atomic operations and privatization 12. Parallel Patterns -- Parallel Graph Algorithms with introduction to dynamic parallelism 13. Computational Neural Networks 14. Numerical Issues in Parallel Algorithms -- Floating-Point Considerations 15. Conclusion and Future Outlook</p> <p>Appendix A. Introduction to OpenCL Appendix B. Parallel Programming with OpenACC Appendix C. A productivity Oriented Library for CUDA Appendix D. CUDA FORTRAN Appendix E. An Introduction to C++AMP Appendix F. Programming a Heterogeneous Cluster Appendix G. New Features in Kepler Appendix H. Matrix Multiplication Host-Only Version Source Code Appendix I. GPU Compute Capabilities</p> 
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700 1 |a Hwu, Wen-mei,  |e author. 
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856 4 0 |u https://sciencedirect.uam.elogim.com/science/book/9780128119860  |z Texto completo