Good idea. I'd much rather write
do concurrent (i = 1:n)
y(i) = y(i) + a*x(i)
enddo
std::transform(par, x, x+n, y, y,
[=](float x, float y){ return y + a*x; }
);
Microsoft demoed a version of their GraphRAG that translated C code to (I believe) mostly idiomatic Rust, and it ran without errors.
I tried to find reference to how they did it, does anyone know?
It sounds like this approach of translating old code could help speed up teams that are looking at rewrites. I also have some old code that's in Kotlin that I'd like to move to something else. I had a bad NullPointerException take down my application after missing a breaking change in a Kotlin update.
From the looks of [1] they have a graph DB storing the code structure and acting as the RAG for an LLM.
I'm trying to think of a reason this couldn't be done more directly with a pretty run-of-the-mill transpiler. Like I understand if this is a technical demo and there is a LOT of Fortran code, but...?
I've actually had to do this with a couple of different Fortran projects when I was in college, I translated them to C for various reasons.
Maybe it's because it was specifically code written by scientists (i.e somewhat brute force and very straightforward) but there really wasn't very many features that I can recall that didn't have a direct C counterpart, other than column major ordering and arrays staring at 1.
Was I just blissfully unaware?
What you want isn't really "output C++ code that is pedantically equivalent to this Fortran code but with the array indexing fixed up", it's usually more like "translate this Fortran module into something that I can offload to a GPU using CUDA/ROCm/etc. with the same high level semantics, but GPU-friendly low level optimizations", and the exact composition of those low level bits probably don't look exactly like a loop-by-loop translation.
CUDA supports Fortran, is one of the reasons OpenCL lost.
Doesn't CUDA handle FORTRAN as such?
I don’t know what the transpiled code would look like vs that rendered by an LLM, but maybe the hope is that latter will be more readable?
LLM as translators for Cobol code to Java or Go should be attempted. And Shut down the IBM mainframe rent seek business for good permanently.
The soon to be GCC 15 release will contain a COBOL fronted. Also other non mainframe compilers have existed for a long time, both proprietary and FOSS.
Thus, availability of a compiler is but a small piece of the puzzle. The real problem is the spider web of dependencies on the mainframe environment, as the enterprises business processes have been intertwined into the mainframe system over decades.
Which is why i think cross compiling to other dependencies and porting to other languages is a better solution. Many of these dependencies could be hardware specific. As long as core business solutions could be ported would be a win for everyone stuck in decades of vendor lockin.
There are COBOL compilers that target JVM and .NET for as long as these technologies exist.
There are also modern compilers to IBM mainframes, including Go, C++, Java, PHP,..
Also outside DevOps and CNCF application space very few people bother with Go, specially not the kind of customers that buy IBM mainframes.
This is great effort, wonder how it compares to Fortran2Cpp
A member of our community accidentally discovered that the D compiler could translate C code to D code.
D has a module system, where you import a module and it pulls the global declarations out of it. To speed up this process, there's a compiler switch to output just the global declarations to another file, a .di file, that functions much like a .h file in C.
Then there came along ImportC, where a C lexer/parser was welded onto the D compiler logic.
aaaand it wasn't long before the switch was thrown to generate a .di file, and voila, the C code got translated to D!
This resulted in making it dramatically easier to use existing C headers and source files with D.
What is the point of this? Fortran is both faster than cpp and easier to write than cpp. It's also by no means a dead or dying or whatever language. Smells like literally "your scientists were so busy they forgot to ask why".
Seems pretty obvious to me, and I’ve written my fair share of both Fortran and C++. I think it is mostly that very few people know Fortran anymore and even fewer people want to maintain it. A vast number of people in 2025 will happily work in C++ and are skilled at it.
Fortran also hasn’t been faster than C++ for a very long time. This was demonstrable even back when I worked in HPC, and Fortran can be quite a bit worse for some useful types of performance engineering. The only reason we continued to use it was that a lot of legacy numerics code was written in it. Almost all new code was written in C++ because it was easier to maintain. I actually worked in Fortran before I worked in HPC, it was already dying in HPC by the time I got there. Nothing has changed in the interim. If anything, C++ is a much stronger language today than it was back then.
Fortran is still quite modern despite its age, and relevant enough that not only has one of the success factors of CUDA, the availability of Fortran on the CUDA SDK, LLVM project also started a Fortran frontend project.
Also to me seems more likely that people that enjoy Fortran in HPC are more likely to change to Chapel than use C++.
> Almost all new code was written in C++ because it was easier to maintain.
What makes you say so? See musicale's comment above. I have a hard time seeing C++ as easier to maintain, if we are just talking about the language. The ecosystem is a different story.
For pure number crunching, Fortran is nicer. Unfortunately, performance for most codes became about optimizing memory bandwidth utilization at some point in the 2000s, and systems languages are much more effective at expressing that in a sane way. It was easier to make C/C++ do numerics code than to make Fortran do systems code. Some popular HPC workloads were also quite light on numerics code generally, being more about parallelization of data processing.
This was before modern C++ existed, so most of the code was “C with classes” style C++. If you can read C then you can read that code. I don’t consider that to be particularly maintainable by modern standards but neither is Fortran.
Modern C++ dialects, on the other hand, are much more maintainable than either. Better results with a fraction of the code. The article doesn’t say but I would expect at least idiomatic C++11, if not later dialects.
Some people at LANL seem to be on a holy crusade to replace Fortran with C++. They occasionally produce stuff like papers saying Fortran is dying and whatever. Perhaps it makes sense for their in-house applications and libraries, but one shouldn't read too much into it outside their own bubble.
I wonder if they feel that the toolchains are just rotting.
This. If someone can't correctly articulate the advantages of Fortran they shouldn't be migrating away from it. This is not to say that migrations should never happen.
Chesterton's Fence