Kongming HV
Kongming is a hyperdimensional computing library implementing sparse binary hypervectors for cognitive computing applications.
The Python package of kongming-rs-hv is released under MIT license, essentially no limitation (and assumes no liability) to any use, personal or commercial.
The core engine is implemented in Go / Rust for maximum efficiency, while ergonomic APIs are open-sourced in Python, for better usability.
We do have an internal Go/Rust APIs that interacts directly with the core engine: overall all APIs maintains minimalistic abstractions and wire-identical serialization.
See Hypervectors for an introduction to hyperdimensional computing and the sparse binary representation.
License
Install
pip install kongming-rs-hv
See Installation for supported platforms and verification steps.
Published notebooks
See Notebook Platforms for all available notebooks and platform details.
Guides
| Guide | Description |
|---|---|
| Python Quick Start | Installation, examples, and walkthrough |
| Notebook Quick Start | Platform setup, interactive notebooks, cell-by-cell walkthrough |
Language Support
This documentation covers code snippets in multiple languages (if available) side by side.
- Python: bindings to the underlying Rust implementation (public
kongming-rs-hvon PyPI); - Go: canonical / reference implementation in proprietary package;
- Rust: parallel implementation, carefully maintained in feature parity;
Reference
The work was initially outlined in this arxiv paper, built on top of the work from many others, and here is the citation:
Yang, Zhonghao (2023). Cognitive modeling and learning with sparse binary hypervectors. arXiv:2310.18316v1 [cs.AI]
Feedback
Found a bug, have a question, or want to suggest an improvement? Open an issue on GitHub.