vs 

Rust vs Julia in scientific computing

Why I think that Julia doesn't solve the two-language problem and when you should use Rust instead.

https://mo8it.com/blog/rust-vs-julia

The blog post is the base for my tiny talk at #RustSciComp23 which is now public:

https://youtu.be/0JkbNFpXlXc

Think of the recording as a trailer. The blog post has many more details and aspects that can not fit into 7 minutes ⏳️

I hope for discussions across both communities 🥰

#JuliaLang #RustLang

I really enjoyed the talk by Manuel Drehwald at #RustSciComp23 who drew the lines of an exciting future for #AutomaticDifferentiation in #Rust with #LLVM #Enzyme , which should be directly integrated into the compiler at an horizon of a couple of months.

If I understood correctly, the idea is to differentiate code at the LLVM IR level, *after optimization* (and to do another pass of optimization after that). This can produce faster code than the AD engines that operate at the source code level.

Really interesting approach from Paul Goulart at #RustSciComp23 mixing #julia and #rust with the takeaway (paraphrased)

"Julia is great for debugging the *math* problems, Rust is great for debugging the *code* problems, and supporting both of those at once Is a lot less work than doing all of it twice"

Followed by another great talk by @mo8it highlighting the footguns and benefits of Julia (check out his blog post https://mo8it.com/blog/rust-vs-julia/)

I wasn't expecting so much Julia but I'm loving it!

I'm watching #RustSciComp23 for the #rust, but daaaaaang if that #fortran code doesn't look cool - simple, formula-based... everything that Fortran should be.

TBF, I had to write MPI code in Fortran90 back in the day.