SELF
fpm
SELF | fpm | |
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4 | 12 | |
43 | 812 | |
- | 1.4% | |
8.9 | 8.8 | |
14 days ago | 21 days ago | |
Fortran | Fortran | |
GNU General Public License v3.0 or later | MIT License |
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SELF
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[RANT] I really, really wish working with compiled languages is as easy as working with Python.
Could you go into more detail? If you're referring to https://github.com/FluidNumerics/SELF, I've just taken a look and it does seem like their documentation on how to build is lacking. Usually if that's the case, you can dig for whatever their CI configuration is and manually follow those steps, but it's not clear here: they have a mechanism to build Singularity containers (ci/run_tests) but everything else in ci seems unrelated. Their CONTRIBUTING.md is out of date and incomplete, and as you've already seen their build system (Makefile, install.sh, test.sh) is a total mess. Pretty much all modern scientific codes are using at least CMake now. (It's either that or hacked-up and hardcoded recursive make, rather than autoconf.)
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The "F" Word - GPU Programming in Fortran : Building the Shallow Water Equation Solver
You can freely download SELF source code online at https://github.com/fluidnumerics/self
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Joe's Live Coding Sessions - GPU Programming in Fortran : Verifying Spectral Accuracy in the Advection-Diffusion Solvers
SELF Github Repository : https://github.com/fluidnumerics/self
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[February] Programming languages for CFD
I'm definitely a fan of Fortran for writing CFD and numerical PDE solvers (https://github.com/FluidNumerics/SELF) in general. Fortran was my first programming language, and I'm not a "geezer geek" (I'm 30 years old). While I also program in C and C++ on some projects, Fortran is my go-to. As others have already mentioned, the array syntax in Fortran is fantastic. It really helps to be able to work out algorithms on paper and translate cleanly into multi-dimensional arrays.
fpm
- Fortran Package Manager (FPM): Package Manager and Build System for Fortran
- Fortran Package Manager
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How do I use fortran github package.
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
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SciPy: Interested in adopting PRIMA, but little appetite for more Fortran code
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.
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The Skills Gap for Fortran Looms Large in HPC
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.
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[RANT] I really, really wish working with compiled languages is as easy as working with Python.
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.
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Toward Modern Fortran Tooling and a Thriving Developer Community
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.
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Fortran Web Framework
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.
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Assembly of course!
FPM has entered the chat https://github.com/fortran-lang/fpm
What are some alternatives?
stdlib - Fortran Standard Library
shenfun - High performance computational platform in Python for the spectral Galerkin method
json-fortran - A Modern Fortran JSON API
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).
OpenCoarrays - A parallel application binary interface for Fortran 2018 compilers.
focal - A modern Fortran abstraction layer for OpenCL
NASTRAN-95
hipfort - Fortran interfaces for ROCm libraries
neural-fortran - A parallel framework for deep learning
sdk - The Dart SDK, including the VM, dart2js, core libraries, and more.
pyplot-fortran - For generating plots from Fortran using Python's matplotlib.pyplot 📈