I built a tensor library from scratch in C++/CUDA
Hi HN, 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…
I built a tensor library from scratch in C++/CUDA launched on June 18, 2025 with 119 votes, #359 of 7,999 launches that month and more than 95% of that year's launches. The site was still online in September 2026, 1 year on.
In plain words
DSC is a tensor library built from scratch in C++ with CUDA support, designed for running small language models locally. It offers a PyTorch-like Python API alongside its C++ core, allowing users to load models like Qwen from HuggingFace and run inference on both GPU and CPU. The library emphasizes clean design, simplicity, and built-in observability tools for developers working with machine learning workflows on consumer hardware.
written from the facts on this page · September 2026
From the sources
Tensor library & inference framework for machine learning - nirw4nna/dsc
DSC is a PyTorch-compatible tensor library and inference framework for machine learning models. It features a C-compatible low-level API that is wrapped in a modern Python API very similar to NumPy / PyTorch but with some nice usability improvements. Intuitive API : DSC Python API closely resembles NumPy / PyTorch. Built-in neural networks support : DSC comes with nn.Module built-in. Porting a model from PyTorch to DSC is trivial (check out the examples ). Multiple backends : DSC supports both CPU and CUDA with other backends being worked on. Programs written using DSC can seamlessly switch between backends by simply adding a dsc.set_default_device('...') instruction, no changes needed.…from github.com
In the maker’s words, at launch
Hi HN, 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…
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