fpm VS prima

Make sure you have the latest fpm binary installed somewhere so that your $PATH can see it: curl -o ~/.local/bin/fpm -L https://github.com/fortran-lang/fpm/releases/download/v0.8.2/fpm-0.8.2-linux-x86_64 && chmod 0755 ~/.local/bin/fpm

Hopefully, the SciPy community can stay open-minded about modern Fortran libraries.

Modern Fortran is quite different from Fortran 77, while being as powerful, if not more.

In addition, there has been a significant community effort on improving and modernising the legacy packages, the ecosystem, and the language itself.

With projects like LFortran (https://lfortran.org/), fpm (https://github.com/fortran-lang/fpm), and stdlib (https://github.com/fortran-lang/stdlib), I believe that Fortran will enjoy prosperity again.

Anyway, first release of Fortran Package Manager was in November 2020: https://github.com/fortran-lang/fpm/releases/tag/v0.1.0 - more recently than I expected.

There is actually a Fortran Package Manager that will hopefully make things easier in the future. It's quite new, so it might not be entirely mature yet.

Author here, so I'm biased toward Fortran, though I've been enjoying learning Rust as well. I think there are a few reasons.

First, Rust's multidimensional arrays are either limited and/or difficult to use. Fast, flexible, and ergonomic multidimensional arrays and arithmetic are essential for HPC. They are possible with Rust, but my two favorite Rust books not mentioning them suggests to me that they're not the focus of the language. This may or may not change in the future.

Second, Rust may be too complex to learn for scientists who aren't paid to write software but to do research. Fortran is opposite--multidimensional whole-array arithmetic looks like you would write it as math on a whiteboard. While scientists can sure learn to program Rust effectively, I think most scientists don't think like Rust, but they do think like Fortran. For somebody not familiar with Fortran but familiar with Python, I'd say Fortran very much feels like NumPy.

Third, such ecosystem would be built in Rust from scratch. In Fortran, most of the value is already there, but needs to be made more accessible with better and more modern tooling. For example, Fortran's fpm (https://github.com/fortran-lang/fpm) is largely modeled after Rust's Cargo because we recognize the importance of good user experience when it comes to building and packaging software. With the recent Fortran-lang efforts, we study many programming language ecosystems and communities (e.g. Python, Julia, Rust, etc.) to find what could work best for modern Fortran tooling.

I recently started learning Fortran for a lark. It reminds me a lot of R, in some respects. It's clearly a very, very good language for doing the parts of one's job that are very math-centric. But it's equally underwhelming as a general purpose programming language.

Largely, I think, due to gaps in the library ecosystem. But there are other challenges. You can see from the install instructions on the linked page, for example, that Fortran still lacks a package manager.

What's interesting, though, is that that's changing. There are currently serious efforts to give it a "standard" library (https://github.com/fortran-lang/stdlib) and package manager (https://github.com/fortran-lang/fpm).

And I've been watching the new LFortran compiler (https://lfortran.org) with extreme interest.

FPM has entered the chat https://github.com/fortran-lang/fpm

The developer of PRIMA here.

If you use method "cobyla" from scipy.optimize.minimize, then PRIMA already performs far better (in terms of the number of function evaluations). See the comparison at https://github.com/libprima/prima#improvements .

The bugs are indeed only a secondary reason: they can only be triggered under special situations. They may not affect your usage at all (when it does affect you, the consequence is catastrophophic).

1. nagfor Release 7.1(Hanzomon) Build 7149 released on March 5, 2024, fixed all the bugs spotted, but introduced an ICE when compiling PRIMA ( http://www.libprima.net ). The ICE has nothing to do with half-precision real, because it occurs when PRIMA is configured to use single or double precision. It can be reproduced by

```

git clone https://github.com/libprima/prima.git && cd prima && git checkout ec42cb0 && cd fortran/examples/lincoa && make ntest

```

2. nagfor 7.2 released on 6 March, 2024 included neither the ICE nor the fixes for the bugs.

My goal is to rewrite this library for derivative-free optimization: https://github.com/libprima/prima

A native port is indeed planned. However, since we are talking about a project of about 10K lines of code, such a port will not be delivered very soon.

In fact, native implementations of PRIMA in Python, MATLAB, C++, Julia, and R will all be done in the future. See https://github.com/libprima/prima#other-languages . But it takes time. PRIMA has been a one-man project since it started three yearss ago. Community help is greatly needed.

Thanks.

GitHub repo of the project: https://github.com/libprima/prima

It sounds like this was a difficult task. The motivation to fulfill Prof. Powell's request and help the community of derivative-free optimization users must have been strong. Congratulations on your achievement!

From the GitHub README:

> In the past years, while working on PRIMA, I have spotted a dozen of bugs in reputable Fortran compilers and two bugs in MATLAB. Each of them represents days of bitter debugging, which finally led to the conclusion that it was not a problem in my code but a flaw in the Fortran compilers or in MATLAB. From a very unusual angle, this reflects how intensive the coding has been.

> The bitterness behind this "fun" fact is exactly why I work on PRIMA: I hope that all the frustrations that I have experienced will not happen to any user of Powell's methods anymore. I hope I am the last one in the world to decode a maze of 244 GOTOs in 7939 lines of Fortran 77 code — I have been doing this for three years and I do not want anyone else to do it again.

https://github.com/libprima/prima#a-fun-fact