Hyperfold CUDA

Hyperfold provides numerical linear algebra for Python with CPU and CUDA 13 backends. Multiply matrices, solve linear systems, compute eigenvalues, and reuse LU factorisations with NumPy arrays, CuPy arrays, or PyTorch CUDA tensors.

Installation

Requires Python 3.11 or newer, Linux x86_64, and a compatible NVIDIA driver.

python -m pip install hyperfold-cuda

The package installs its CUDA runtime dependencies. CuPy and PyTorch are optional and installed separately. For CPU-only use, install hyperfold instead; the two packages share the hyperfold import name and must not be installed together.

Quickstart

With CuPy installed:

import cupy as cp
import hyperfold as hf

a = cp.array([[4, 1], [1, 3]], dtype=cp.float64)
b = cp.array([1, 2], dtype=cp.float64)

product = hf.matmul(a, a)
solution = hf.solve(a, b)
eigenvalues, eigenvectors = hf.eigh(a)

Results remain on the GPU as CuPy arrays. The same functions accept NumPy arrays for CPU execution.

See the documentation for the Python API, supported dtypes, and CUDA interoperability.