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