qiime2-amplicon-2023.9, miniconda3, macM2
qiime rescript evaluate-fit-classifier
question: I read that this step requires a lot of memory and and time (e.g., v3-4 takes >35 hours with 12 cores according to Step 6: Taxonomy assignment - shenjean/diversity GitHub Wiki). I've read the community plugin support post from 2021 (Is there a way to parallelize evaluate-fit-classifier?), but other than flagging --p-n-jobs I'm not sure how to best configure this on an hpc.
Any advice about how to parallelize this on an hpc to speed things up (with fairly detailed explanations/instructions for a newbie)? I've visited the help documentation and see options for --parallel-config and --parallel, but am not experienced enough to know how to make a parallel configuration and set reasonable parameters, or how many cpus, tasks, time, etc. should be allocated for the job. Or perhaps I am doomed to pay the price of 35 hours. Any experienced advice will be much appreciated.