Designing Scientific Applications on GPUs (eBook, PDF)

Redaktion: Couturier, Raphael

• Format: PDF

Produktbeschreibung

General purpose graphics processing units (GPGPUs) enable researchers in a variety of fields to benefit from the computational power of all the cores available inside graphics cards. This book shows you how to use GPUs for applications in diverse scientific fields, from physics and mathematics to computer science. The book explains the methods necessary for designing or porting your scientific application on GPUs and will improve your knowledge about image processing, numerical applications, methodology to design efficient applications, optimization methods, and much more.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 498
• Erscheinungstermin: 21. November 2013
• Englisch
• ISBN-13: 9781466571648
• Artikelnr.: 40345282

Autorenporträt

Raphaël Couturier is a professor of computer science at the University of Franche-Comte and vice head of the Computer Science Department at FEMTO-ST Institute. He has co-authored over 80 articles in peer-reviewed journals and conferences. He received a Ph.D. from Henri Poincaré University. His research interests include parallel and distributed computation, numerical algorithms, GPU and FPGA computing, and asynchronous iterative algorithms.

Inhaltsangabe

PRESENTATION OF GPUs: Presentation of the GPU Architecture and the Cuda
Environment. Introduction to Cuda. IMAGE PROCESSING: Setting up the
Environment. Implementing a Fast Median Filter. Implementing an Efficient
Convolution Operation on GPU. SOFTWARE DEVELOPMENT: Development of Software
Components for Heterogeneous Many-Core Architectures. Development
Methodologies for GPU and Cluster of GPUs. OPTIMIZATION: GPU-Accelerated
Tree-Based Exact Optimization Methods. Parallel GPU-Accelerated
Metaheuristics. Linear Programming on a GPU: A Case Study. NUMERICAL
APPLICATIONS: Fast Hydrodynamics on Heterogeneous Many-Core Hardware.
Parallel Monotone Spline Interpolation and Approximation on GPUs. Solving
Linear Systems with GMRES and CG Methods on GPU Clusters. Solving Sparse
Nonlinear Systems of Obstacle Problems on GPU Clusters. Ludwig: Multiple
GPUs for a Fluid Lattice Boltzmann Application. Numerical Validation and
GPU Performance in Atomic Physics. GPU-Accelerated Envelope-Following
Method. OTHER: Implementing Multi-Agent Systems on GPU. Pseudorandom Number
Generator on GPU. Solving Large Sparse Linear Systems for Integer
Factorization on GPUs. Index.