This is the function that takes most of the time. As you can see it it a single nested for loop that calculates a value from Matrix ui and stores it in Matrix u. Because the first matrix is never changed in each step, the result can therefore be calculated in independent threads safely. this means that this code should be relatively simple to parallelize and should see large speed increases.

Data decomposition uses nested loops to break down a large chunk of data into smaller sections. Then perform a process to the smaller section. I could not find an

==== Chadd's Example ====