[D] how to parallelize optimal parameter search for DL NNs on multiple datasets?

Suppose i have 5 and 6 datasets, 11 in total. then i have a collection of 5 different deep learning networks, each having their own set of free non-DL parameters, ranging from none to 3-4. imagine i have a list of educated guesses for each parameter (5-6 values) and i wanna try all their combinations for each DL method on each dataset. i’m okay with leaving it computing overnight.