If youre actually doing HPC, say, on a cluster, the startup time will be amortized, or else, you're doing something wrong.
Using Julia in this case basically means having to rewrite all of the other programs into it and getting rid of eg snakemake or gnu parallel or any number of other very common HPC workflows.
In fact I'd venture that doing a sequence of things many times is just as common an HPC workload than single jobs running for very long times.
Julia itself is not even reproducible: https://github.com/JuliaLang/julia/issues/25900 https://github.com/JuliaLang/julia/issues/34753
Not at all. The issue is that the default sysimage distributed with Julia cannot be reproduced across machines, e.g. there is no proof that it hasn't been tampered with. This is an open issue in Guix and Nix, though it affects all platforms.
> One of the places Julia really excels with reproducibility is inter OS
There really is no such thing as reproducibility in Windows, at least not in the sense outlined in bootstrappable.org . If you care about reproducibility, you've chosen the wrong platform.
This is not to say that the boot time is always a problem, there are plenty of applications in which it doesn't matter at all (as you point out). However that's not always the case (by a long shot) which is why tools like GNU Parallel and snakemake exist.