Parallel cross validation & memory overflow

Hi,

I'm trying to tune six forecasts using a parameter grid (with a total of ~100 combinations) in a straightforward for loop. I'm using the parallel processing option while cross validating, but for some reason the loop takes up more and more memory as it progresses through the parameter grid, eventually leading to memory overflow.
This seems odd to me since all variables are being replaced after each sequantial run. I suspect this has something to do with how parallel processes are (not) being terminated and thus eating up more and more of the server's RAM? It doesn't matter whether I use the 'processes' or 'threads' option.

I have no idea how this parallelization works on the backend; is there some kind of progress I need to terminate after each run?

Thanks!