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Programming massively parallel processors : a hands-on approach / Wen-mei Hwu, David B. Kirk, Izzat El Hajj.

Por: Colaborador(es): Lenguaje original: Inglés United States : Elsevier , 2023Edición: Primera ediciónDescripción: xxviii, 551 páginasTipo de contenido:
  • text
Tipo de medio:
  • unmediated
Tipo de soporte:
  • volume
ISBN:
  • 9780323912310
Tema(s): Clasificación CDD:
  • 004.35 H991p 2023
Contenidos:
PART I. FUNDAMENTAL CONCEPTS. Chaper 1. Introduction. - Chaper 2. Heterogeneous data parallel computing. - Chaper 3. Multidimensional grids and data. - Chaper 4. Compute architecture and scheduling. - Chaper 5. Memory architecture and data locality. - Chaper 6. Performance consiredations.
PART II. PARALLEL PATTERNS. Chaper 7. Convolution. - Chaper 8. Stencil. - Chaper 9. Parallel histogram. - Chaper 10. Reduction. - Chaper 11. Prefix sum (scan). - Chaper 12. Merge.
PART III. ADVENCED PATTERNS AND APPLICATIONS. Chaper 13. Sorting. - Chaper 14. Sparse matrix computation. - Chaper 15. Graph traversal. - Chaper 16. Deep learning. - Chaper 17. Iterative magnetic resonance imaging reconstruction. - Chaper 18. Electrostatic potential map. - Chaper 19. Parallel programming and computacional thinking.
PART IV. ADVANCES PRACTICES. Chaper 20. Programming a heterogeneous computing cluster. - Chaper 21. CUDA dynamic parallel. - Chaper 22. Advanced practices and future evolution. - Chaper 23. Comclusion and outlook.
Existencias
Tipo de ítem Biblioteca actual Colección Signatura topográfica Copia número Estado Fecha de vencimiento Código de barras
Libros Biblioteca Central Estantería General 004.35 H991p 2023 (Navegar estantería(Abre debajo)) c.1 Disponible 015580

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PART I. FUNDAMENTAL CONCEPTS. Chaper 1. Introduction. - Chaper 2. Heterogeneous data parallel computing. - Chaper 3. Multidimensional grids and data. - Chaper 4. Compute architecture and scheduling. - Chaper 5. Memory architecture and data locality. - Chaper 6. Performance consiredations.

PART II. PARALLEL PATTERNS. Chaper 7. Convolution. - Chaper 8. Stencil. - Chaper 9. Parallel histogram. - Chaper 10. Reduction. - Chaper 11. Prefix sum (scan). - Chaper 12. Merge.

PART III. ADVENCED PATTERNS AND APPLICATIONS. Chaper 13. Sorting. - Chaper 14. Sparse matrix computation. - Chaper 15. Graph traversal. - Chaper 16. Deep learning. - Chaper 17. Iterative magnetic resonance imaging reconstruction. - Chaper 18. Electrostatic potential map. - Chaper 19. Parallel programming and computacional thinking.

PART IV. ADVANCES PRACTICES. Chaper 20. Programming a heterogeneous computing cluster. - Chaper 21. CUDA dynamic parallel. - Chaper 22. Advanced practices and future evolution. - Chaper 23. Comclusion and outlook.