Hi everyone,

I'm interested in tensors, scientific computing and ML. After trying to write a tensor library for c++, I came to the realisation that I'm starting to hate the language the more code i write. D seems like an obvious choice for my interest, a fast compiled language but the gc is putitng me off as well. I would be however very interested in contributing to mir maybe even writting examples for its use cases. I would like to write a classical machine learning library (decision trees, linear models...) in D. Are there currently any effort in the community towards this goal? I would appreciate any help or suggestions.

the gc is putitng me off as well

but the gc is putitng me off as well

Hi everyone,

I'm interested in tensors, scientific computing and ML. After trying to write a tensor library for c++, I came to the realisation that I'm starting to hate the language the more code i write. D seems like an obvious choice for my interest, a fast compiled language but the gc is putitng me off as well. I would be however very interested in contributing to mir maybe even writting examples for its use cases. I would like to write a classical machine learning library (decision trees, linear models...) in D. Are there currently any effort in the community towards this goal? I would appreciate any help or suggestions.

Hi everyone,

I'm interested in tensors, scientific computing and ML. After trying to write a tensor library for c++, I came to the realisation that I'm starting to hate the language the more code i write. D seems like an obvious choice for my interest, a fast compiled language but the gc is putitng me off as well. I would be however very interested in contributing to mir maybe even writting examples for its use cases. I would like to write a classical machine learning library (decision trees, linear models...) in D. Are there currently any effort in the community towards this goal? I would appreciate any help or suggestions.

This isn't really my area of interest or expertise, but you might find some historical interest from VectorFlow - a neural network library Netflix developed (and I feel it stopped existing after like a month, would love if someone has an interesting story to tell about it): https://github.com/Netflix/vectorflow

On Wednesday, 6 August 2025 at 17:54:27 UTC, Marc wrote:

gc only runs when you allocate; use the same big arrays c++ would use and youll be fine

On Wednesday, 6 August 2025 at 17:54:27 UTC, Marc wrote:

Then don't use it?

I do lots of statistical work with D and honestly I have found little to gain from avoiding the GC. It'll all depends on what you're doing, of course, but look at std.typecons.RefCounted if you want to avoid D's GC. I use it because I often call into C libraries that allocate memory. Just don't expect it to improve performance. YMMV.

there are some things to do in this area
most of the work is stalled now

but if you are interested join discord and we can discuss something there