PX4/eigen

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1140 stars · 188 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

PX4/eigen is a fork of Eigen, a C++ template library for linear algebra providing matrices, vectors, numerical solvers, and related algorithms. It supports dense and sparse matrices of all sizes, multiple numeric types, matrix decompositions, and SIMD vectorization across x86, ARM, and PowerPC instruction sets.

Use cases

• do matrix and vector math in C++
• solve linear systems and least squares in C++
• perform matrix decompositions like SVD, QR, LU
• work with sparse matrices efficiently
• write SIMD-optimized numerical code without assembly
• port MATLAB linear algebra code to C++
• use linear algebra in robotics flight control software

When to choose

• you need a mature, header-only C++ linear algebra library with no heavy dependencies
• you need high performance via expression templates and explicit SIMD vectorization
• you need both dense and sparse matrix support with many decompositions
• you are working in the PX4/robotics ecosystem and need compatibility with its fork

When to avoid

• you need GPU-accelerated linear algebra at large scale (consider cuBLAS or similar)
• you want a high-level interactive numerical environment (use NumPy or MATLAB)
• you need a permissively-licensed library and cannot accept Eigen's MPL2/custom licensing terms
• you need deep learning tensor operations with autodiff (use PyTorch or TensorFlow)

Facets

library · maturity stable

math robotics developer-tools cpp cross-platform linear-algebra matrices sparse-matrices simd header-only eigen-fork numerical-solvers algorithms

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