Designing scientific applications on GPUs

Designing scientific applications on GPUs / edited by Raphaël Couturier.

"This book covers designs of scientific applications for GPUs, beginning with a review of the principles of GPU programming. It then describes various scientific applications for GPUs and presents lessons learned. Scientific applications covered include computations on matrix operations, linear...

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Bibliographic Details
Other Authors: Couturier, Raphaël
Format: eBook
Language:English
Published: Boca Raton [Florida] : CRC/Taylor & Francis, [2014]
Series:Chapman & Hall/CRC numerical analysis and scientific computing ; 21.
Subjects:
Parallel programming (Computer science)
Graphics processing units > Programming.
Science > Data processing.
Numerical analysis > Computer programs.
Application software > Development.
COMPUTERS > General.
Application software > Development
Numerical analysis > Computer programs
Science > Data processing
Online Access:Click for online access
Table of Contents:
  • Front Cover; Contents; List of Figures; List of Tables; Preface; I. Presentation of GPUs; 1. Presentation of the GPU architecture and of the CUDA environment; 2. Introduction to CUDA; II. Image processing; 3. Setting up the environment; 4. Implementing a fast median filter; 5. Implementing an efficient convolution operation on GPU; III. Software development; 6. Development of software components for heterogeneous many-core architectures; 7. Development methodologies for GPU and cluster of GPUs; IV. Optimization; 8. GPU-accelerated tree-based exact optimization methods.
  • 9. Parallel GPU-accelerated metaheuristics10. Linear programming on a GPU: a case study; V. Numerical applications; 11. Fast hydrodynamics on heterogeneous many-core hardware; 12. Parallel monotone spline interpolation and approximation on GPUs; 13. Solving sparse linear systems with GMRES and CG methods on GPU clusters; 14. Solving sparse nonlinear systems of obstacle problems on GPU clusters; 15. Ludwig: multiple GPUs for a complex fluid lattice Boltzmann application; 16. Numerical validation and performance optimization on GPUs of an application in atomic physics.
  • 17. A GPU-accelerated envelope-following method for switching power converter simulationVI. Other; 18. Implementing multi-agent systems on GPU; 19. Pseudorandom number generator on GPU; 20. Solving large sparse linear systems for integer factorization on GPUs.

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