Over the past few months, I've been building `dsc`, a tensor library from scratch in C++/CUDA. My main focus has been on getting the basics right, prioritizing a clean API, simplicity, and clear observability for running small LLMs locally.

The key features are: - C++ core with CUDA support written from scratch. - A familiar, PyTorch-like Python API. - Runs real models: it's complete enough to load a model like Qwen from HuggingFace and run inference on both CUDA and CPU with a single line change[1]. - Simple, built-in observability for both Python and C++.

Next on the roadmap is adding BF16 support and then I'll be working on visualization for GPU workloads.

The project is still early and I would be incredibly grateful for any feedback, code reviews, or questions from the HN community!

GitHub Repo: https://github.com/nirw4nna/dsc

[1]: https://github.com/nirw4nna/dsc/blob/main/examples/models/qw...