norm VS Arraymancer

Congratulations to everyone involved and the entire Nim community!

Nim has been my language of choice for the past decade and I'm really happy with the new features in Nim 2.0. Some of them are real gamechangers for my projects. For example, default values for objects theoretically allow me to make Norm[1] work with object types along with object instances. And the new overloadable enums is something Karkas [2] wouldn't be possible at all (it's still WIP though).

[1] https://norm.nim.town

[2] https://karkas.nim.town

In the ORM field, Norm[1] is an actively maintained package that supports SQLite and Postgres. It's framework agnostic, I've used it with Jester and Prologue (it had nothing to do with Prolog btw).

Among frameworks, Prologue is the most actively developed and feature rich.

[1] https://norm.nim.town

[1] https://norm.nim.town

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!