Wen-mei W. Hwu,
Wen-mei W. (CTO, MulticoreWare and professor specializing in compiler design, computer architecture, microarchitecture, and parallel processing, University of Illinois at Urbana-Champaign, USA) Hwu,
David B. Kirk,
David B. (NVIDIA Fellow) Kirk,
Izzat El Hajj,
Izzat (Assistant Professor, Department of Computer Science, American University of Beirut, Lebanon) El Hajj
e.a.
Programming Massively Parallel Processors
A Hands-on Approach
Paperback Engels 2026 9780443439001Levertijd ongeveer 9 werkdagen
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Samenvatting
Programming Massively Parallel Processors: A Hands-on Approach, Fifth Edition shows both students and professionals alike the basic concepts of parallel programming and GPU architecture. Concise, intuitive, and practical, it is based on years of road-testing in the authors' own parallel computing courses. Various techniques for constructing and optimizing parallel programs are explored in detail, while case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. This new edition has been updated with an expanded repertoire of optimizations, new patterns and applications, ad more coverage of important CUDA features.
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Inhoudsopgave
1. Introduction<br><br>Part I. Fundamental Concepts<br>2. Heterogeneous data parallel computing<br>3. Multidimensional grids and data<br>4. Compute architecture and scheduling<br>5. Memory architecture and data locality<br>6. Performance considerations<br><br>Part II. Parallel Patterns<br>7. Convolution<br>8. Stencil<br>9. Parallel histogram<br>10. Reduction<br>11. Prefix sum (scan)<br>12. Merge<br><br>Part III. Advanced Patterns and Applications<br>13. Sorting<br>14. Filtering (new)<br>15. Sparse matrix computation<br>16. Wavefront Algorithms (new)<br>17. Graph traversal<br>18. Deep learning<br>19. Multi-GPU API (new)<br>20. Electrostatic potential map<br>21. Parallel programming and computational thinking<br><br>Part IV. Advanced Practices<br>22. Programming a heterogeneous computing cluster<br>23. Advanced Optimizations for Matrix Multiplication (new)<br>24. Advanced practices and future evolution<br>25. Conclusion and outlook
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