I am using the indicspecies R package to run an indicator species analysis on a large dataset to see what species are indicators for 3 different regions over the years 2001 to 2021. My matrix is ~550 columns (one for each species in the dataset) and has 21 rows for each year. I am currently running the analysis at nperm=999 and it has been running for over 24 hours.

indval <- multipatt(Species_matrix_df, Combined_data_2001onward$Group,
control = how(nperm=999))

Should I reduce the nperm to see if it runs faster that way? Or should I to break up my dataset somehow and it is not running due to its large size? If I should break up my dataset, I suppose I could break it up for each of the 3 regions and run the analysis for each region?