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→Bruno's Findings
Like this you are able to get a nice heat dispersion calculation.
I was worried about data dependency, since, as I said, each element depends on each other to be calculated. But this solution uses 2 matrix, one old and one new, where the new matrix will receive the average value of the old matrix and, if the difference is still bigger than epsilon, then the old matrix recieves receives the values of the new matrix and the whole iteration happens again, where the new matrix is going to receive the average values of the old matrix, that now holds the most recent values.
So this is a good candidate for parallelization because we can send each iteration of the average calculation to a different GPU thread and since this is a simple average calculation, the GPU will be able to do it.
[[File:execution-NO_CUDA.JPG]]
Number of iterations x Value reached that represents the first value smaller than Epsilon.
====Carlos's Findings====