OK, first off with hyperthreading the two virtual cores are fighting for the real core: that tends to slow the process down. We generally try and turn hyperthreading off on office PCs.Â
The other part of parallel processing is data transfer. Ie how much data is passed between how many cores when running in parallel. As the number of cells on a core decreases the proportion of compute spent on data transfer increases relative to that used for solving the equations. Eventually the data transfer slows the whole model down. It's very physics and model dependent but also how much hardware you have. Running under 50k nodes per real core tends not to give much speed up, but may prevent someone else working if you're hogging cores.Â
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