Committing changes that should really save a lot of time doing tests in pycuda.
I pull from the database once for the largest test (only trying out small tests
for now, will try to have a multithreaded approach for the larger tests) and
then run all of the smaller configurations against that dataset. Since database
access times are not being recorded & observed and only clustering times are
being measured this *should* be fine... maybe. I can just run this multiple
times and average all of them, that's fine too.