I think a new Python interpreter session might not be the closest comparison for Julia since Python loads almost nothing by default, whereas Julia imports a ton of functionality by default. R is much more like Julia in this regard. Consistent with that hypothesis, on my machine, R uses 38 MB and Julia uses 41 MB. I suspect that Julia without most of its functionality could take up much less memory.
— John On Jan 14, 2014, at 6:56 PM, Andy M <0andrewmart...@gmail.com> wrote: > Thank you all very much for your answers, they have been extremely helpful! > > In summary, it seems like there is a fairly clear answer to all but one > question, which is the question about Julia's memory usage. I am still > puzzled by what it is actually being used for. For comparison, if I start a > python interpreter it uses less than 5MB of RAM. I expected Julia's code > generation to consume more memory than an interpreter, but I did not expect > it to be anywhere near that much. > > I suppose the issue with Tuple/immutable type performance also isn't > completely clear. > > Andy, would you be willing to collect the responses you found helpful and add > them to the FAQ? > https://github.com/JuliaLang/julia/blob/master/doc/manual/faq.rst > You can just click "edit" on that page, no need to explicitly deal with git. > I've been keeping track of many questions that I have found answers to (not > just those answered here), and I've been writing it all up in a desktop wiki. > I'm not sure what would be best to add to the FAQ at this point, but I am > hoping to work out a good format for sharing my experiences soon. Either by > contributing to the FAQ, by writing a blog post, or both.
