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Illinois ECE 498AL: Programming Massively Parallel Processors, Lecture 15: Kernel and Algorithm Patterns for CUDA

By Wen-Mei W Hwu

University of Illinois at Urbana-Champaign

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Abstract

Kernel and Algorithm Patterns for CUDA

Topics:

  • Reductions and Memory Patterns
  • Reduction Patterns in CUDA
  • Mapping Data into CUDA's Memories
  • Input/Output Convolution
  • Generic Algorithm Description
  • What could each thread be assigned?
  • Thread Assignment Trade-offs
  • What memory Space does the Data use?
  • Stencil Computation: Fluid Dynamics, Image Convolution
  • Bonded Input/Output Convolutions

Credits

These lecture were breezed by Carl Pearson and Daniel Borup and then reviewed, edited ,and Uploaded by Omar Sobh.

Sponsored by

NCN@illinois

Cite this work

Researchers should cite this work as follows:

  • Wen-Mei W Hwu (2009), "Illinois ECE 498AL: Programming Massively Parallel Processors, Lecture 15: Kernel and Algorithm Patterns for CUDA," http://nanohub.org/resources/7442.

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