So folks, what package would you recommend for paralellising code in R?
I thought this would be simple based on previous experience with parallelising code but I am quickly realising it is not going to be simple. Blargh.
I have had a total turnaround and now think I do not need the paralell package.
I hope you are all enjoying this live commentary on the realities of science.
I hope you are all enjoying this live commentary on the realities of science.
I'm also so stressed about this I have managed to spell parallel wrong twice in a very short space of time.
My conundrum quite nicely illustrates the frustrations of R. I *could* open 12 R windows and run 1/12th of my runs in each. It would achieve exactly what I am trying to do. Instead I will spend the next few days wrangling with code because it will be more useful in future #rstats
So far I have managed to make my model, and whole computer run really slowly using the future package #winning #rstats
Everything is bad.
Wait I think I am getting somewhere
So I can run my function using foreach....now I need to work out how to get different runs to use different input variables
I HAVE PARALLELISED IT IN FOREACH. But I don't know how to get each run to use a different variable help?! #rstats #babysteps
I have one solution courtesy of @statsforbios who is a total hero, but am keen to get it working using foreach and doapply as well. If anyone knows about cycling through numbers using iter() let me know #rstats. It keeps telling me an argument is missing *grumble*
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