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This comment overstates the current power of Julia's parallel programming model — as of now Julia has no real tools for shared-memory parallelism and probably will not for another few versions or so. For distributed memory Julia is great, but please do not use Julia if you are being hindered by the GIL.

(NB I say this as a big Julia evangelist. it has a lot of potential but is not really there yet on a number of things, this being one of them.)




This is not strictly accurate. Julia does not support multi-threaded parallelism, but there is decent (if, yes, still immature) support for multi-process shared memory parallelism - similar to Python's multiprocessing library. Not an alternative to the GIL as such, but definitely more than nothing.

One nice example using this is a shared memory, parallel sparse matrix multiplication implementation:

https://github.com/madeleineudell/ParallelSparseMatMul.jl


I take back my claim. Thanks for pointing this out!

If they can't support true multithreading without having to pack messages or use /dev/shm, fuck em.




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