Programming Massively Parallel Processors: A Hands-On Approach, Second Edition

  • 8h 38m
  • David B. Kirk, Wen-mei W. Hwu
  • Elsevier Science and Technology Books, Inc.
  • 2013

Programming Massively Parallel Processors: A Hands-on Approach shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Various techniques for constructing parallel programs are explored in detail. Case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs.

In this Book

  • Introduction
  • History of GPU Computing
  • Introduction to Data Parallelism and CUDA C
  • Data-Parallel Execution Model
  • CUDA Memories
  • Performance Considerations
  • Floating-Point Considerations
  • Parallel Patterns: Convolution—With an Introduction to Constant Memory and Caches
  • Parallel Patterns: Prefix Sum—An Introduction to Work Efficiency in Parallel Algorithms
  • Parallel Patterns: Sparse Matrix–Vector Multiplication—An Introduction to Compaction and Regularization in Parallel Algorithms
  • Application Case Study: Advanced MRI Reconstruction
  • Application Case Study: Molecular Visualization and Analysis
  • Parallel Programming and Computational Thinking
  • An Introduction to OpenCL
  • Parallel Programming with OpenACC
  • Thrust: A Productivity-Oriented Library for CUDA
  • CUDA FORTRAN
  • An Introduction to C++ AMP
  • Programming a Heterogeneous Computing Cluster
  • CUDA Dynamic Parallelism
  • Conclusion and Future Outlook
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