Building a PC optimized for "time to first plot"

[Palli]

It would be highly ironic if you consider to buy a superfast computer for the high-performance language Julia, because it’s slow at compiling!

With my trick for faster recompilation, I seem to have converted one Common Lip user to use Julia: not-common-lisp-to-julia.org · GitHub

@oheil

depends on the dreams one has. Add reasonable small executable and I am with you, despite that I would still prefer the statically compiled small executable in general.

You can have 20 KB Julia executables, but those are limited (e.g. no GC), with Python most or all of the important limitations are lifted (StaticCompiler.jl doesn’t yet support Windows, so I’m not sure this works there, even if you use Python for the Windows compatibility):

Successful Static Compilation of Julia Code for use in Production

The StaticCompiler package was recently registered. This post records a successful experiment to statically compile a piece of Julia code into a small .so library on Linux, which is then loaded from Python and used in training of a deep learning model. TLDR Static compilation to a stand-alone library does work on Linux but has rather significant restrictions on the functionality available. It is mostly useful for core computational routines. Roughly speaking, if it could be implemented in plai…

I hope my PlotlyLight.jl suggestion helped, any plotting library (and more code) is likely excluded with that approach though, but if you do the plotting from the Python side, then something similar is I guess available.