000 03581cam a22003375i 4500
003 EG-CaNGU
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008 231214t2023 maua frb 001 0 eng d
020 _a9780323912310
040 _aDLC
_beng
_erda
_cDLC
_dDLC
_dEG-CaNGU
082 0 4 _a004.35
_bHWP
_223
100 1 _aHwu, Wen-mei,
_eauthor.
_95975
245 1 0 _aProgramming massively parallel processors :
_ba hands-on approach /
250 _aFourth edition.
264 1 _aCambridge, Massachusetts :
_bMorgan Kauffmann, Elsevier Inc.,
_c[2023]
264 4 _c©2023
300 _axxviii, 551 pages :
_billustrations ;
_c24 cm
336 _atext
_btxt
_2rdacontent
337 _aunmediated
_bn
_2rdamedia
338 _avolume
_bnc
_2rdacarrier
504 _aIncludes bibliographical references and index.
505 0 0 _aChapter 1. Introduction -- Part I: Fundamental Concepts -- Chapter 2. Heterogeneous data parallel computing -- Chapter 3. Multidimensional grids and data -- Chapter 4. Compute architecture and scheduling -- Chapter 5. Memory architecture and data locality -- Chapter 6. Performance considerations -- Part II: Parallel Patterns -- Chapter 7. Convolution: An introduction to constant memory and caching -- Chapter 8. Stencil -- Chapter 9. Parallel histogram: An introduction to atomic operations and privatization -- Chapter 10. Reduction: And minimizing divergence -- Chapter 11. Prefix sum (scan): An introduction to work efficiency in parallel algorithms -- Chapter 12. Merge: An introduction to dynamic input data identification -- Part III: Advanced Patterns and Applications -- Chapter 13. Sorting -- Chapter 14. Sparse matrix computation -- Chapter 15. Graph traversal -- Chapter 16. Deep learning -- Chapter 17. Iterative magnetic resonance imaging reconstruction -- Chapter 18. Electrostatic potential map -- Chapter 19. Parallel programming and computational thinking -- Chapter 20. Programming a heterogeneous computing cluster: An introduction to CUDA streams -- Chapter 21. CUDA dynamic parallelism -- Chapter 22. Advanced practices and future evolution -- Chapter 23. Conclusion and outlook.
520 _aProgramming Massively Parallel Processors: A Hands-on Approach shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Various techniques for constructing parallel programs are explored in detail. Case studies demonstrate the development process, which begins with computational thinking and ends 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 are updating their coverage of CUDA, including the concept of unified memory, and expanding content in areas such as threads, while still retaining its concise, intuitive, practical approach based on years of road-testing in the authors' own parallel computing courses.--
_cSource other than the Library of Congess.
650 7 _aParallel programming (Computer science).
_2NGU-sh
_95976
650 7 _aParallel processing (Electronic computers).
_2NGU-sh
_95977
650 7 _aMultiprocessors.
_2NGU-sh
_95978
650 7 _aComputer architecture.
_2NGU-sh
_94432
700 1 _aKirk, David,
_d1960-,
_eauthor.
_95979
700 1 _aEl Hajj, Izzat,
_eauthor.
_95980
999 _c1995
_d1995