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About

Code for evaluating the performance of a Parallel Convolution operation on images.

The algorithm can be separated into five steps:

  • Define N as the number of available cores;
  • Slice the input image into (N^2)+2 sub-images;
  • Create the parallel instances;
  • Convolve each sub-image with the desired kernel;
  • Create the output image with the sub-images joining.

The results are available at http://jeanvitor.com/convolution-parallel-algorithm-python/

How to use

  • Download and Install Anaconda
  • Install joblib package: conda install -c anaconda joblib
  • To run: py Conv.py