Intro to CUDA programming

This code is designed to walk you through optimizing an example GPU application, starting from the basic CPU version. The accompanying slides are available here.

OpenCV is required in the example code simply to load and save an image file.

Description of source files

• avg_filter.cu is the main code, which demonstrates several different ways to implement a 3x3 image smoothing (averaging) filter on the GPU.
• helper_cuda.h and helper_string.h are from the CUDA samples. They provide handy functions like gpuGetMaxGflopsDeviceId() and checkCudaErrors().
• lib_example/ contains a CUDA source file, hypot.cu, which is compiled into a shared library and then used in hypot.py.

TODO

• Finish slides
• Make pthreads example?
• Libraries (how to use e.g. cuBLAS)