#why does julia take so much memory?

1 messages · Page 1 of 1 (latest)

agile harbor
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when i just run the julia repl (CLI) it takes min. 80mb of RAM.
Thats not a lot but it scales very quickly.

What can i do to reduce it?

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Python IDLE/repl for instance takes only 20mb

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with all the gui

cinder sierra
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You can't reduce the footprint. Julia always loads 3 things into memory when it starts up: (1) the OpenBLAS linear algebra library, (2) the LLVM compiler backend for fast compilation and (3) the documentation for the things it is aware of at startup. Julia is a language for numerical computing, which is why the developers went with this approach. You should not expect to use it in low-performance environments.

worn socket
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Tell us what you're trying to do and maybe we'll be able to help more

frigid roost
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i guess that's the tradeoff they have to make for a fast dynamic language.

lament compass
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Isn't it just the julia REPL that takes all the memory? Try checking it when just running julia <your_script>

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what possible device would there be that doesn't have 80mb of ram but you still need to use julia interactively

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if you're super short on RAM baremodule may also help for your script but I'm not positive about that and that definitely won't work in the REPL

agile harbor
agile harbor
silver axle
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Also, you can already do binary builds that strip out things like metadata and the repl. That was part of the v1.9 release

agile harbor
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oh wow thats great to hear

frigid roost
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thats great

tranquil kayak
agile harbor
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Thanks everyone here for help, my problem has been cleared

silver axle
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LLVM is mostly the reason why it takes 80 MBs of RAM ^^
Yeah LLVM is like 80, BLAS is like 30, and then you get to like 120 because of what's left. The good thing is that it's clear what the main contributors are.

agile harbor
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Oh...so you are the director of modelling and simulation. thats awesome

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I will be there one day