Why scientists are turning to Rust • Hacker News Board

Re: Why scientists are turning to Rust

#41

Post by a-nikolaev » Tue, Dec 01, 2020, 11:40 PM UTC

ThrowawayR2 wrote: post #27

st1x7 wrote: post #11

This seems like a stretch, or it seems very limited to the specific people mentioned in the article. I find it hard to believe that scientists who have specialised very narrowly in their domain will also want to be full-time software engineers too and choose one of the most complex languages on top of that. This just doesn't scale beyond the few people who are really into it. > Köster, now at the University of Duisbu…

Scientists didn't have a problem writing Fortran, back in its day. I doubt they'd have a problem with Rust or even C++ if they needed to.

And that Fortran on average was pretty bad. Any language that requires certain level of discipline will have hard time to be adopted at a large scale. And this is why Python, R, and "C/C++" are still the best friends for most people in scientific software development.

Re: Why scientists are turning to Rust

#42

Post by ironmagma » Tue, Dec 01, 2020, 11:40 PM UTC

gnusty_gnurc wrote: post #30

I don't think scientists should worry themselves with the cognitive burden of Rust. It's hard enough to figure out how to do things in any language as a full-time software developer, never mind someone that just needs a program for their research, etc.

Scientists are currently writing their code in C++ in many cases. If you have needs that require the performance benefits of C++, why not do it in a language that has a cohesive design (and is actually intuitive) instead of learning the pile of layers of decades-old debt that is C++?

Re: Why scientists are turning to Rust

#43

Post by st1x7 » Tue, Dec 01, 2020, 11:42 PM UTC

proverbialbunny wrote: post #35

7thaccount wrote: post #32

Earlier quoted context omitted.

I'm also highly sceptical. In my experience scientific software is mostly restricted to: C, C++, Fortran, Python, R, Matlab/Simulink, Mathematica, Julia, and Excel. I would think VERY few doing numerical computing or statistical or other engineering computations would have the bandwidth to really dive into Rust. I also wouldn't consider it stable enough for many projects (although I'm sure it's fine for some).

Rust is easier than C++ for this kind of work because of its packages. In some ways Rust is closer to Python for prototyping an idea to see if it works. Rust gets challenging when you have to deal with large systems, which is not a problem for research. Researchers / scientists will sometimes not even write functions. It's that small of a scope.

> Researchers / scientists will rarely even write functions. It's that small of a scope

Scientific computing can mean so many different things that if feels like some of us are talking past each other in this thread.

The person in the article talks about needing to get out every ounce of performance and writing an application that identifies genome variants at scale. You're talking code so small that it doesn't need functions. Those are completely different worlds.

Choosing Rust for something that small is a waste of time. Expecting the people who write so little code that their code doesn't require functions, to be comfortable with Rust is even a bigger stretch.

Re: Why scientists are turning to Rust

#44

Post by ur-whale » Tue, Dec 01, 2020, 11:43 PM UTC

bluenose69 wrote: post #9

I've started learning Julia lately, and it also has an appeal, especially for fortran-ish computations. (Yup, I said fortran ... it is still used in lots of scientific computations e.g. fluid-mechanical models.)

"used" as in "using existing libraries" or do you mean there are folks still writing fortran in 2020?

Re: Why scientists are turning to Rust

#45

Post by ur-whale » Tue, Dec 01, 2020, 11:44 PM UTC

jimbob45 wrote: post #33

Does anyone know why scientists aren’t just using Excel? Nothing against Python/Julia but Excel seems like it would be my first choice (paired with some CSV files).

Excel is far too slow for large scale datasets.

Re: Why scientists are turning to Rust

#46

Post by pvorb » Tue, Dec 01, 2020, 11:44 PM UTC

sida wrote: post #37

walleeee wrote: post #31

Earlier quoted context omitted.

Yes. And a lot of that software collects dust after the paper it produced is published :/ Academia needs to recognize and incentivize software (including maintenance) as a research output, and make funding available for more research software engineers.

Do these software collect dust and rust over time? ok sorry.. bad dad joke..

This just made me discover the Dust programming language[1].

[1]: https://bilalhusain.com/dust/

Re: Why scientists are turning to Rust

#47

Post by mattkrause » Tue, Dec 01, 2020, 11:47 PM UTC

walleeee wrote: post #31

whymauri wrote: post #23

Earlier quoted context omitted.

>I find it hard to believe that scientists who have specialized very narrowly in their domain will also want to be full-time software engineers too and choose one of the most complex languages on top of that. I think it's really field-dependent. I know academics/profs in the computational biology space that accumulate a looot of software over time from their colleagues/students. Also, it's not the scientists/PIs writ…

Yes. And a lot of that software collects dust after the paper it produced is published :/ Academia needs to recognize and incentivize software (including maintenance) as a research output, and make funding available for more research software engineers.

Amen! More long-term staff scientist jobs of all stripes!

One lesson I hope people take away from AlphaGo/AlphaFold (and a lot of the work coming out of the Allen Institutes, Broad, etc) is that some really amazing work can be done when big groups of experienced people can work together on a project.

Re: Why scientists are turning to Rust

#48

Post by jimbob45 » Tue, Dec 01, 2020, 11:48 PM UTC

ur-whale wrote: post #45

jimbob45 wrote: post #33

Does anyone know why scientists aren’t just using Excel? Nothing against Python/Julia but Excel seems like it would be my first choice (paired with some CSV files).

Excel is far too slow for large scale datasets.

Is that true? Python is pretty slow too. I can’t imagine many scientists would really mind leaving their work running overnight.

Re: Why scientists are turning to Rust

#49

Post by proverbialbunny » Tue, Dec 01, 2020, 11:48 PM UTC

DiabloD3 wrote: post #8

You know why I like Rust as a programmer? It's community feels a lot like how the Perl community did at the height of Perl's popularity. This is in contrast to Python's (has a friendly community, but tends to have bikeshedding), Node's (outright toxic npm-based warfare), or Java's (corporations shit out awful code when they're done with it, ie, everything donated to Eclipse or Apache, or all the dumpster fire code Go…

I'm a researcher and I loved prototyping in Perl once upon a time ago. It was so fast and easy to get an idea out. I've played with Rust too, and have done a project in it. I like it too, but as a necessity, not out of a strong love. I do love the package manager Rust has though. It's so nice to not have to worry about that kind of thing.

Once Raku has dataframes, and it is stable, I'll definitely be checking it out.

Re: Why scientists are turning to Rust

#50

Post by rudolph9 » Tue, Dec 01, 2020, 11:56 PM UTC

Rust may or may not be a good choice for research scientist needs but the biggest missing piece in my opinion is reproducibility.

I haven’t worked with it extensively (I use nix on my workstation) but I’m a big fan of what the Guix folks are doing targeting the scientific community https://hpc.guix.info/blog/2019/05/gnu-guix-1.0-foundation-f...