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Why does the macOS version run as slow Intel code under Apple Silicon instead of native? It's just Electron, why is it not running native arm64?

I found this: https://github.com/jupyterlab/jupyterlab-desktop/issues/279

So JupyterLab Desktop is not new? I still don't understand why Electron apps can't immediately be built for arm64...



I have no idea what Jupyer is only that it’s vaguely related with machine learning

But… wild shot - lot of machine learning stuff is not on M1, because there is no free ARM compiler for FORTRAN and there is some FORTRAN code in some popular machine learning stuff. Like R, I think.


Huh? The GNU compiler collection contains a Fortran frontend, and GCC can target nearly every architecture under the sun, inluding Aarch64.


this is from 2020, maybe it was fixed.

> GCC’s GFortran supports 64-bit ARMs: … However, the Apple silicon platform uses a different application binary interface (ABI) which GFortran does not support, yet.

There was some experimental branch or whatever. I’m not sure of the state now.


I can see why you'd say it's ML, but Jupyter is a "notebook" or kind of "literate programming" environment for Python (originally) and other languages, a kind of REPL on steroids.

You see it in a lot of ML examples around the Internet because it's a pretty good way of demonstrating and documenting ML for tutorials.


Ah, okay. Then I’m totally off the mark here.


Also it's split into a frontend "client" for the UI and a backend "server" (also called a "kernel") for computation. The client doesn't need any of the Fortran BLAS stuff, only the backend, which runs in a completely separate process and communicates over network ports.




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