Collection of various hardware components used for machine learning accelerator research.
## Quick Start
This project manages reproducible programming environments with:
- [uv](https://docs.astral.sh/uv/) for managing python environments.
- [nix](https://nixos.org) for managing non-python tools and benchmark designs. Follow [this guide](https://librelane.readthedocs.io/en/stable/installation/nix_installation/index.html) or [this guide](https://github.com/fossi-foundation/nix-eda/blob/main/docs/installation.md) to setup [nix-eda](https://github.com/fossi-foundation/nix-eda/tree/main) binary cache to avoid re-building EDA-related tools.
No need to clone or download this repository.
Access all synthesized hardware modules by calling: