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[중고] DESIGNING SCIENTIFIC APPLICATIONS ON GPUS (HARDCOVER)
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    · 제목 : Designing Scientific Applications on Gpus (Hardcover) 
    · ISBN : 9781466571624
    · 쪽수 : 498쪽
    · 출판일 : 2013-11-21

    목차

    PRESENTATION OF GPUs
    Presentation of the GPU Architecture and the Cuda Environment Raphael Couturier
    Introduction
    Brief history of video card
    GPGPU
    Architecture of current GPUs
    Kinds of parallelism
    Cuda multithreading
    Memory hierarchy

    Introduction to Cuda

    Raphael Couturier
    Introduction
    First example
    Second example: using CUBLAS
    Third example: matrix-matrix multiplication

    IMAGE PROCESSING
    Setting up the Environment

    Gilles Perrot
    Data transfers, memory management
    Performance measurements

    Implementing a Fast Median Filter

    Gilles Perrot
    Introduction
    Median filtering
    NVidia GPU tuning recipes
    A 3x3 median filter: using registers
    A 5x5 and more median filter

    Implementing an Efficient Convolution Operation on GPU

    Gilles Perrot
    Overview
    Definition
    Implementation
    Separable convolution

    SOFTWARE DEVELOPMENT


    Development of Software Components for Heterogeneous Many-Core Architectures Stefan L. Glimberg, Allan P. Engsig-Karup, Allan S. Nielsen, and Bernd Dammann
    Software development for heterogeneous
    Heterogeneous library design for PDE solvers
    Model problems
    Optimization strategies for multi-GPU systems

    Development Methodologies for GPU and Cluster of GPUs

    Sylvain Contassot-Vivier, Stephane Vialle, and Jens Gustedt
    Introduction
    General scheme of synchronous code with computation/communication overlapping in GPU clusters
    General scheme of asynchronous parallel code with computation/communication overlapping
    Perspective: A unifying programming model

    OPTIMIZATION
    GPU-Accelerated Tree-Based Exact Optimization Methods

    Imen Chakroun and Nouredine Melab
    Introduction
    Branch-and-bound (B&B) algorithm
    Parallel B&B algorithms
    The flowshop scheduling problem
    GPU-accelerated B&B based on the parallel tree exploration (GPU-PTE-BB)
    GPU-accelerated B&B based on the parallel evaluation of bounds (GPU-PEB-BB)
    Thread divergence
    Memory access optimization
    Experiments

    Parallel GPU-Accelerated Metaheuristics

    Malika Mehdi, Ahcene Bendjoudi, Lakhdar Loukil, and Nouredine Melab
    Introduction
    Combinatorial optimization
    Parallel models for metaheuristics
    Challenges for the design of GPU-based metaheuristics
    State-of-the-art parallel metaheuristics on GPUs
    Frameworks for metaheuristics on GPUs
    Case study: Accelerating large neighborhood LS method on GPUs for solving the Q3AP

    Linear Programming on a GPU: A Case Study

     Xavier Meyer, Bastien Chopard, and Paul Albuquerque
    Introduction
    Simplex algorithm
    B&B algorithm
    CUDA considerations
    Implementations
    Performance model
    Measurements and analysis

    NUMERICAL APPLICATIONS
    Fast Hydrodynamics on Heterogeneous Many-Core Hardware

    Allan P. Engsig-Karup, Stefan L. Glimberg, Allan S. Nielsen, and Ole Lindberg
    On hardware trends and challenges in scientific applications
    On modeling paradigms for highly nonlinear and dispersive water waves
    Governing equations
    The numerical model
    Properties of the numerical model
    Numerical experiments

    Parallel Monotone Spline Interpolation and Approximation on GPUs

    Gleb Beliakov and Shaowu Liu
    Introduction
    Monotone splines
    Smoothing noisy data via parallel isotone regression

    Solving Linear Systems with GMRES and CG Methods on GPU Clusters

    Lilia Ziane Khodja, Raphael Couturier, and Jacques Bahi
    Introduction
    Krylov iterative methods
    Parallel implementation on a GPU cluster
    Experimental results

    Solving Sparse Nonlinear Systems of Obstacle Problems on GPU Clusters

    Lilia Ziane Khodja, Raphael Couturier, Jacques Bahi, Ming Chau, and Pierre Spiteri
    Introduction
    Obstacle problems
    Parallel iterative method
    Parallel implementation on a GPU cluster
    Experimental tests on a GPU cluster
    Red-black ordering technique

    Ludwig: Multiple GPUs for a Fluid Lattice Boltzmann Application

    Alan Gray and Kevin Stratford
    Introduction
    Background
    Single GPU implementation
    Multiple GPU implementation
    Moving solid particles

    Numerical Validation and GPU Performance in Atomic Physics

    Rachid Habel, Pierre Fortin, Fabienne Jezequel, Jean-Luc Lamotte, and Stan Scott
    Introduction
    2DRMP and the PROP program
    Numerical validation of PROP in single precision
    Toward a complete deployment of PROP on GPUs
    Performance results
    Propagation of multiple concurrent energies on GPU

    GPU-Accelerated Envelope-Following Method

    Xuexin Liu, Sheldon Xiang-Dong Tan, Hai Wang, and Hao Yu
    Introduction
    The envelope-following method in a nutshell
    New parallel envelope-following method
    Numerical examples

    OTHER
    Implementing Multi-Agent Systems on GPU

    Guillaume Laville, Christophe Lang, Benedicte Herrmann, Laurent Philippe, Kamel Mazouzi, and Nicolas Marilleau
    Introduction
    Running agent-based simulations
    A first practical example
    Second example
    Analysis and recommendations

    Pseudorandom Number Generator on GPU

    Raphael Couturier and Christophe Guyeux
    Introduction
    Basic reminders
    Toward efficiency and improvement for CI PRNG
    Experiments

    Solving Large Sparse Linear Systems for Integer Factorization on GPUs

    Bertil Schmidt and Hoang-Vu Dang
    Introduction
    Block Wiedemann algorithm
    SpMV OVER GF(2) for NFS matrices using existing formats on GPUs
    A hybrid format for SpMV on GPUs
    SCOO for single-precision floating-point matrices
    Performance evaluation

    Index

    A Bibliography appears at the end of each chapter.

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