[Brajeshwar]

Well, I'm surprised he has the time/intention to do that in between for us mere mortals. Here are a few references;

- https://en.wikipedia.org/wiki/Bellard%27s_formula

- https://en.wikipedia.org/wiki/Fabrice_Bellard

``` In April 2021 his Artificial Neural Network based data compressor, NNCP, took first place out of hundreds in the Large Text Compression Benchmark. To write the compressor, Bellard wrote his own Artificial Neural Network library, LibNC ("C Library for Tensor Manipulation"), publicly available. ```

[intelVISA]

One glance upon the majesty of Bellard's works is enough to give even a 10x SWE imposter syndrome.

[wazoox]

Not only that, but he's a heck of a nice guy. Back in 2003 I discovered qemu (I was using Bochs at the time) and it was a huge boost for my work building emulated environments. My colleague sent an email to Fabrice Bellard to thank him for his work, and he replied very nicely that he was happy that his software was actually useful to others.

[ninjin]

Since I teach a fair amount of machine learning, I have been pondering on what a “minimal”, low-level implementation of a library would look like and got very excited hearing about LibNC. Sadly it seems like Bellard is keeping the source for this one: “The LibNC library is free to use as a binary shared library. Contact the author if access to its source code is required.” [1]. Not that you can every accuse the man of being greedy after all the code he has shared, but dang I wanted to read it. '^^

[1]: https://bellard.org/libnc/libnc.html#License

[e12e]

Seems that it would be worth your time to contact Bellard and ask about making it available for teaching (and/or under an open license of some kind)?

[ninjin]

Thank you, I will try to gather the courage. Partially I guess I suspect that he chose to do what he did for a (good?) reason and I do not really think it is my place to question it. Partially I guess I am somewhat reluctant to poke a borderline god of our discipline with a beggar’s request. '^^

No promises, but I will try to gather the courage and thank you for the encouragement.

[mhh__]

TinyGrad is basically that and is open source, albeit not in C

[ninjin]

Yes, kind of, but it depends on NumPy which is fairly big if your goal is for students to grasp and demystify the whole way down to the hardware. Other candidates would be torch7 [1], but it is somewhat married to the Lua API which drives it.

[1]: https://github.com/torch/torch7

[hansworst]

You might like micrograd: https://github.com/karpathy/micrograd. There's also this video where the author explains how he built it: https://www.youtube.com/watch?v=VMj-3S1tku0