karax VS Arraymancer

The frontend uses Karax, which is my favorite frontend/SPA library. It is an absolute joy to use, even if it's a bit rough around the edges.

https://github.com/karaxnim/karax

I have used Nim for personal projects for 6 years now and it continues to surprise me on how well versed it is for many problem domains. I am fond of it's SPA framework, karax https://github.com/karaxnim/karax for which I wrote a translation utility https://github.com/nim-lang-cn/html2karax Latest Nimv2 release candidate has improved in the ergonomics and syntax that affect compilation to js, so I was able to cleanup my webapp's code to be less verbose. On GPU programming there has been a few projects that touch GPU programming, most notably https://github.com/treeform/shady

And it's present not only in Python but in other languages as well. Check for example https://github.com/karaxnim/karax - I don't know why people would want to hide all of their HTML in Python/whatever language. Then limit their ability to script and style it in one way or another.

> the real killer feature to me is the javascript target

Agree, this is amazing because you can share code and data structures between front and backend (for example: https://github.com/karaxnim/karax).

Also, it's really nice having high level stuff like metaprogramming and static typing spanning both targets. Things like reading a spec file and generating statically checked APIs for server/client is straightforward, which opens up a lot of possibilities.

E.g. Nim focuses on enabling what it calls "single page web apps": https://github.com/karaxnim/karax.

Karax [1] being Nim's SPA framework that also supports server side rendering.

[1]: https://github.com/karaxnim/karax

I recommend you to take a look at Karax. It's a front-end framework for Nim that can compile to regular JavaScript. If you want to know how to use it with a webserver, Joker is a good example. With the Joker config, all of the compiled .js files land in /public/views, where you can take a look at them. But keep in mind that the JS that Nim produces is often rather cumbersome and hundreds of lines long, even if it's just a simple program.

It is a small DSL written using macros at https://github.com/mratsim/Arraymancer/blob/master/src/array....

Nim has pretty great meta-programming capabilities and arraymancer employs some cool features like emitting cuda-kernels on the fly using standard templates depending on backend !

Nim has also a powerful deep learning library called Arraymancer. It's selling point is that you don't have to rewrite your code from research to production. It's used in various machine learning projects, but one recent one that caught my eye was https://github.com/amkrajewski/nimCSO "Composition Space Optimization"

https://github.com/mratsim/Arraymancer

- https://github.com/mratsim/Arraymancer/blob/master/src/array...

It's worth noting that nim async/await transformation is fully implemented as a library in macros.

https://github.com/mratsim/Arraymancer 11. « Premature optimisation is the root of all evil », Donald Knuth, The art of computer Programming It would be quite useful that someone writes one with examples for all these recommendations and more ...

In particular for deep learning as bobsyourunkl already mentioned there is arraymancer on the one hand and also flambeau on the other. The latter is a Nim wrapper around libtorch (i.e. the PyTorch C++ backend). It is missing things (to be wrapped by adding a few lines) and has some rough edges, but if one needs to get stuff done, it's possible.

how are u compiling (optimization, custom compilation flags etc.?) In my case https://github.com/mratsim/Arraymancer big project compile under your 4.2s so or you have like 10k+ lines of codes with macros or you just pass some debug flags to compiler :D

We have both raw wrappers for BLAS:

https://github.com/andreaferretti/nimblas

as well as LAPACK:

https://github.com/andreaferretti/nimlapack

For an example, consider calling the least squares routine `dgelsd` in arraymancer:

https://github.com/mratsim/Arraymancer/blob/master/src/array...

wrapped up in a nicer user facing API.

Feel free to hop onto matrix, if you have more questions!