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Comment by sampo | Hacker News Reader

> The good news for some HPC simulations and models, both inside of the National Nuclear Security Administration program at the DOE and in the HPC community at large, is that many large-scale physics codes have been rewritten or coded from scratch in C++

When C++ one day goes out of fashion, like Fortran already has, this will turn out to be bad news. Fortran is not a big language, and any programmer can learn Fortran in a matter of weeks. But if you'd need to teach people C++ just so that they'd be able to maintain a legacy code base, that will be considerably more difficult than with Fortran.

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Probably in a thousand years nobody will be writing C++. In one year, there will still be a helluva lot of C++, including new projects.

Point being, the premise of your argument isn't granted. Is C++ going away soon? Or is it holding steady and even growing? How can someone objectively know either way?

It’s hard to predict much about 10 years out, let alone 1000.

But we keep expecting languages like COBOL and MUMPS to die, and they keep living on.

I think there’s a almost 100% chance that 1000 years from now, when all that’s left of human civilization is a bunch of bots trading hustle culture spam and culture war arguments on a zombie internet, that the whole thing will still run on some mission critical code written in C. Buggy, unsafe, but mission critical and hard to replace.

And of course there will be heated bot arguments about how it should all be scrapped and rewritten in Rust++.

If AI maintains a decent rate of advancement, it will eventually become possible to just ask an AI to... rewrite it in a different language.

You can already give GPT a decent-sized chunk of C code and ask it to rewrite it in, say, Rust, and it works with some rate of success.

For the last 50 years, this was impossible to do in a generic way. In the last 6 months, we managed to move the needle from impossible to possible. Give it another 12000 months, and what are the chances this would not move towards "trivial"?

Sure. But that's not what keeps systems written in COBOL or MUMPS. It's not what's kept the US air traffic control system running on 1970s-era hardware and software until very recently. Humans are perfectly capable of rewriting these systems. AI will be, as well.

The problem with changing a mission-critical system is risk, and cost. Maybe omniscient AIs in 3023 won't have this issue, but my ghost will be entirely unsurprised if there are still mission critical systems written in C laying around because whatever benefits are rewrite would give are dwarfed by the risk, perceived or real, of what happens if the rewrite isn't 100% perfect or doesn't 100% match the current system.

> Is C++ going away soon? Or is it holding steady and even growing? How can someone objectively know either way?

No. It's not going away anytime soon, but you can look at high-performance languages that are gaining in popularity, and that may point to change in the future. TIOBE isn't perfect, but it's a good indicator of interest, and Rust and Go seem to continue to gain popularity.

Interestingly, and related to this article, Fortran has moved up from #31 to #20 on TIOBE's index, which really does speak to the importance of a math-optimized, high performance, compiled language. Another interesting change is MATLAB moving up from #20 to #14.

for contrast, tiobe also believes visual basic classic (a language which hasn't been supported since 2008) is also in the top 20

Having seen banking stacks, I'm inclined to believe TIOBE.

Most programming is not the kind programming you see talked about on HN. VB is still huge in legacy stacks.

right, but how much of that code is using a version of the language that hasn't been supported for 15 years? according to tiobe the answer is more than the amount of bash,powershell, and perl put together (and the amount is dramatically increasing)

TIOBE index is rivaled by the annual Stack Overflow Developer Survey in some regards https://survey.stackoverflow.co/2022/#technology-most-popula... :

> Most popular technologies This year, we're comparing the popular technologies across three different groups: All respondents, Professional Developers, and those that are learning to code.

Most popular technologies > Programming, scripting, and markup languages

The Top 500 Green500 (and the TechEmpower Web Framework benchmarks) are also great resources for estimating what people did this past year; what are the "BigE" of our models in terms of water, kwh of [directly or PPA-offset] sourced clean energy.

Rust and Go still have a lot to catch up in HPC though.

IMHO The biggest roadblock to use AI to rewrite code and blindly trust results is having good tests to validate results. This is mood for simulations and models.

Also, neural ODEs are already taking traction. It won't be hard to replace lots of obscure spaghetti code that deal with edge cases in models with maybe inscrutable neural networks that deliver the same results. Better tools are already developing to deal with interpretability of NN, as higher-level blocks become standard abstractions.

Do you mean to say simulations and models have good tests? In my (very limited) experience with scientific computing that's absolutely not the case. There's a decent chance the software is impossible to test because it can only be run all together and is nondeterministic.

Modern C++ is just Rust minus the borrow checker. Future high performance programmers will have no trouble with it.

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