ovasylenko/g6k-rs

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README

g6k-rs g6k-rs is a research-oriented Rust library for lattice reduction, enumeration, and sieving on CPUs, Apple Metal, and NVIDIA CUDA. The crate includes floating-point and arbitrary-precision reduction, exact invariant checks, deterministic examples, and optional GPU backends. It is an experimental implementation: APIs may change, and it has not been audited for use in production cryptographic systems. Try it The quickest path uses only the portable floating-point feature set: git clone https://github.com/ovasylenko/g6k-rs.git cd g6k-rs ./scripts/quickstart.sh The script runs a deterministic LLL/BKZ example and verifies its determinant invariant. The first build compiles dependencies and therefore takes longer than subsequent runs. Add the crate to a Rust project with: [dependencies] g6k-rs = "0.1" use g6k_rs::{LLLParams, LatticeBasis, lll_reduce};

let mut basis = LatticeBasis::from_rows(vec![ vec![1.0, 1.0], vec![-1.0, 2.0], ]); lll_reduce(&mut basis, &LLLParams::default()).unwrap(); The default build enables arbitrary-precision support through the mpz feature. Set default-features = false for the floating-point API only. What is implemented

Floating-point LLL, BKZ, deep insertion, slide reduction, and self-dual reduction. Babai-style CVP, pruned enumeration, rerandomized enumeration, and pruning profile optimization. BDGL, BGJ1, and HK3-style lattice sieves with deterministic CPU and parallel paths. Arbitrary-precision lattice arithmetic and reduction through rug/GMP/MPFR. Optional Metal and CUDA sieve, enumeration, and Seysen-conditioning paths. Exact or independently recomputed checks for determinant preservation, coordinate reconstruction, integral output, and returned candidate norms.

See the examples guide for task-oriented snippets and project status for maturity and limitations. Relationship to G6K and fplll The name describes the project's goal: exploring a Rust implementation of the lattice-reduction and sieving problem space associated with the General Sieve Kernel. It is not an official port, release, or drop-in replacement for fplll/G6K.

Project Primary interface Focus

g6k-rs Rust library Rust APIs, exact checks, CPU/Metal/CUDA experiments

G6K Python + C++ Established General Sieve Kernel research implementation

fplll C++ library + CLI Mature lattice reduction and enumeration tooling

No claim is made that g6k-rs is faster, more complete, or a compatible replacement. Read PROVENANCE.md before redistributing or relicensing the project. Verification

Portable floating-point build and tests

Default build, including arbitrary precision

Formatting and linting

metal-gpu (macOS): Metal sieve kernels, GPU Seysen conditioning, and Metal-backed reduction entry points. metal-fp16: experimental half-precision database storage on top of metal-gpu. cuda-gpu (Linux/NVIDIA): CUDA sieve, enumeration, and Seysen kernels. The build requires nvcc; set G6K_CUDA_ARCH to the target architecture, such as sm_89.

Use the GPU testing guide for build and validation commands. Hardware measurements and the rules for making performance claims live in BENCHMARKING.md. Documentation

Examples — how to use each major workflow. Status and limitations — what is stable, experimental, or hardware-dependent. Benchmarking — reproducible commands and historical measurements. Provenance — independent-authorship statement, research sources, and contribution policy. Algorithm and paper map — fidelity notes for research modules. Contributing — required checks and evidence standards.

License Licensed under either the Apache License 2.0 or the MIT License, at your option. Maintainer: Oleksii Vasylenko (hello@ovasylenko.com).

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