nimkernel VS Arraymancer

> kernel developers do not allow third party runtimes in the kernel. Even meager Rust's "panic" runtime is a contentious

Much in Linux is contentious :-) which is why the module system is nice. A kernel module for C code requires no permission from Linux-core unless you need it distributed with the kernel (which, yes, might be required for "credibility" - but critically also might not). It may require many decls to access various kernel APIs, but those can be (semi-)automated or just done as-needed. So, Linux kernel policy is not so relevant (at best) which is what I meant by "no special support" (admittedly brief). Kernel coding is always a bit trickier, and you may need to build up some support code to make integration nice, though as well as decl generators.

> Can one disable runtime in Nim completely -- no GC, no exceptions?

To answer your question, and as discussed elsewhere in this subthread, Nim has many options for memory management.. only stdlib seq/string really needs automatic methods. One can disable the runtime completely via os:standalone and statically check that no exceptions are raised with Nim's effect system (and there are also both setjmp & goto based exception impls which may/may not be workable in Linux/BSD kernel module settings). As "proof more by example", a few people have written OS kernels in Nim recently[1,2] and there was another toy kernel long ago[3].

People have also written OS kernels in Go which "has a GC and runtime".[4] So, I acknowledge it's not quite the same example, but I also see no fundamental blockers for kernel modules.

[1] https://github.com/khaledh/axiom

[2] https://prosepoetrycode.potterpcs.net/2023/01/a-barebones-ke...

[3] https://github.com/dom96/nimkernel

[4] https://github.com/mit-pdos/biscuit/

Niceness is subjective, but Nim is just as valid an addition to that group. Nim compiles to C and has had an --os=standalone mode for like 10 years from its git history, and as mentioned else-thread (https://news.ycombinator.com/item?id=36506087) can be used for Linux kernel modules. Multiple people have written "stub OSes" in it (https://github.com/dom96/nimkernel & further along https://github.com/khaledh/axiom).

While it can use clang as a backend, Nim does not rely upon LLVM support like Zig or Rust (pre-gcc-rust working). Use on embedded devices is fairly popular: https://forum.nim-lang.org/search?q=embedded (or web search).

Latency-wise, for a time, video game programming was a perceived "adoption niche" or maybe "hook" for Nim and games often have stringent frame rendering deadlines. If you are interested in video games, you might appreciate https://github.com/shish/rosettaboy which covers all but Ada in your list with Nim being fastest (on one CPU/version/compiler/etc). Note, however, that cross-PL comparisons are often done by those with much "porting energy" but limited familiarity with any but a few of the PLs. A better way to view it is that "Nim responds well to optimization effort" (like C/Ada/C++/Rust/Zig).

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!