I'm tuning my xgboost model with Tune of Tidymodels, running in 6 parallel processes on doFuture. However, it is still going to take a week to finish the tuning. Therefore, I'm considering adding more CPU cores to speed the tuning. However, I noticed that each tuning process would consume like 6GB of RAM (I guess every process own a copy of the training data?). If I'm going to spawn 1 process each core on a CPU of 68 cores, that is like 408GB of RAM needed, which is impossible for me. So how should I utilize more computation power regarding the memory usage? Maybe I should increase the thread number of xgboost engine and reduce the tuning process number?