Overview

Full Product Details

Author:   Volodymyr Kindratenko
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   Softcover reprint of the original 1st ed. 2014
Dimensions:   Width: 15.50cm , Height: 2.20cm , Length: 23.50cm
Weight:   6.263kg
ISBN:  

9783319379944

ISBN 10:   3319379941
Pages:   405
Publication Date:   17 September 2016
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

Accelerating Numerical Dense Linear Algebra Calculations with GPUs.- A Guide to Implement Tridiagonal Solvers on GPUs.- Batch Matrix Exponentiation.- Efficient Batch LU and QR Decomposition on GPU.- A Flexible CUDA LU-Based Solver for Small, Batched Linear Systems.- Sparse Matrix-Vector Product.- Solving Ordinary Differential Equations on GPUs.- GPU-based integration of large numbers of independent ODE systems.- Finite and spectral element methods on unstructured grids for flow and wave propagation problems.- A GPU implementation for solving the Convection Diffusion equation using the Local Modified SOR method.- Pseudorandom numbers generation for Monte Carlo simulations on GPUs: Open CL approach.- Monte Carlo Automatic Integration with Dynamic Parallelism in CUDA.- GPU-Accelerated computation routines for quantum trajectories method.- Monte Carlo Simulation of Dynamic Systems on GPUs.- Fast Fourier Transform (FFT) on GPUs.- A Highly Efficient FFT Using Shared-Memory Multiplexing.- Increasing parallelism and reducing thread contentions in mapping localized N-body simulations to GPUs.

Reviews

From the book reviews: This book attempts to provide some guidance for researchers who develop HPC codes and want to run them on GPU-based systems. ... The intended readership consists of people who already have a certain amount of experience in working with GPUs ... . For readers with such a background, it will prove to be useful reading. (Kai Diethelm, Computing Reviews, November, 2014)

From the book reviews: This book attempts to provide some guidance for researchers who develop HPC codes and want to run them on GPU-based systems. ... The intended readership consists of people who already have a certain amount of experience in working with GPUs ... . For readers with such a background, it will prove to be useful reading. (Kai Diethelm, Computing Reviews, November, 2014)

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