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Thanks for submitting this issue. I would actually expect the RAM to increase when more cores are used because I think more or less the entire R session is copied into each fork, so more cores (=forks) -> more memory. The question is if we can find a way to reduce the memory load a bit. The first obvious attempt would be to keep the working space as small as possible when cracking a bundle list, i.e. make sure you don't have any other big objects lying around that you don't need at the moment. When I find the time I'll definetly look into this a bit more. Thanks!
when testing v2 with cracking 2600 bundles and various count of cores -> R took different amounts of RAM
e.g. ncores = 12 cracking went from 7,6 GB to 44 GB
i dont know if number of cores is related to amount of RAM taken
but so far performance is great :)
good job!
Christian
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