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Cuda for Engineers An Introduction to High-Performance Parallel Computing

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

12.11.2015

Verlag

Addison-Wesley

Seitenzahl

352

Maße (L/B/H)

23,1/18,7/3,2 cm

Gewicht

602 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-0-13-417741-0

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

12.11.2015

Verlag

Addison-Wesley

Seitenzahl

352

Maße (L/B/H)

23,1/18,7/3,2 cm

Gewicht

602 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-0-13-417741-0

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Cuda for Engineers

  • Acknowledgments            xvii

    About the Authors             xix

     

    Introduction          1

    What Is CUDA?     1

    What Does “Need-to-Know” Mean for Learning CUDA?     2

    What Is Meant by “for Engineers”?     3

    What Do You Need to Get Started with CUDA?      4

    How Is This Book Structured?      4

    Conventions Used in This Book      8

    Code Used in This Book      8

    User’s Guide      9

    Historical Context      10

    References      12

     

    Chapter 1: First Steps            13

    Running CUDA Samples      13

    Running Our Own Serial Apps      19

    Summary      22

    Suggested Projects      23

     

    Chapter 2: CUDA Essentials           25

    CUDA’s Model for Parallelism     25

    Need-to-Know CUDA API and C Language Extensions     28

    Summary      31

    Suggested Projects      31

    References      31

     

    Chapter 3: From Loops to Grids           33

    Parallelizing dist_v1    33

    Parallelizing dist_v2      38

    Standard Workflow      42

    Simplified Workflow      43

    Summary      47

    Suggested Projects      48

    References      48

     

    Chapter 4: 2D Grids and Interactive Graphics           49

    Launching 2D Computational Grids      50

    Live Display via Graphics Interop     56

    Application: Stability      66

    Summary      76

    Suggested Projects      76

    References      77

     

    Chapter 5: Stencils and Shared Memory           79

    Thread Interdependence      80

    Computing Derivatives on a 1D Grid      81

    Summary     117

    Suggested Projects      118

    References      119

     

    Chapter 6: Reduction and Atomic Functions          121

    Threads Interacting Globally      121

    Implementing parallel_dot      123

    Computing Integral Properties: centroid_2d      130

    Summary      138

    Suggested Projects      138

    References       138

     

    Chapter 7: Interacting with 3D Data           141

    Launching 3D Computational Grids: dist_3d     144

    Viewing and Interacting with 3D Data: vis_3d      146

    Summary      171

    Suggested Projects     171

    References     171

     

    Chapter 8: Using CUDA Libraries           173

    Custom versus Off-the-Shelf      173

    Thrust      175

    cuRAND      190

    NPP      193

    Linear Algebra Using cuSOLVER and cuBLAS      . 201

    cuDNN      207

    ArrayFire      207

    Summary      207

    Suggested       208

    References     209

     

    Chapter 9: Exploring the CUDA Ecosystem            211

    The Go-To List of Primary Sources      211

    Further Sources      217

    Summary      218

    Suggested Projects     219

     

    Appendix A: Hardware Setup           221

    Checking for an NVIDIA GPU: Windows      221

    Checking for an NVIDIA GPU: OS X     222

    Checking for an NVIDIA GPU: Linux     223

    Determining Compute Capability      223

    Upgrading Compute Capability      225

     

    Appendix B: Software Setup            229

    Windows Setup     229

    OS X Setup      238

    Linux Setup      240

     

    Appendix C: Need-to-Know C Programming          245

    Characterization of C     245

    C Language Basics      246

    Data Types, Declarations, and Assignments      248

    Defining Functions      250

    Building Apps: Create, Compile, Run, Debug      251

    Arrays, Memory Allocation, and Pointers      262

    Control Statements: for, if      263

    Sample C Programs     267

    References     277

     

    Appendix D: CUDA Practicalities: Timing, Profiling, Error Handling, and Debugging            279

    Execution Timing and Profiling      279

    Error Handling     292

    Debugging in Windows      298

    Debugging in Linux     305

    CUDA-MEMCHECK     308

    Using Visual Studio Property Pages      309

    References     312

     

    Index            313