Reference-LAPACK/lapack

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1889 stars · 512 forks observed · 2026-08-28

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

LAPACK is a reference library of Fortran subroutines for solving common numerical linear algebra problems such as linear equations, eigenvalue problems, and singular value decomposition. It includes C interfaces (CBLAS, LAPACKE) and is the standard foundation underlying most scientific computing stacks.

Use cases

• solve systems of linear equations
• compute eigenvalues and eigenvectors of matrices
• perform singular value decomposition (SVD)
• factorize matrices (LU, QR, Cholesky)
• build scientific computing libraries on a standard BLAS/LAPACK backend
• do numerical linear algebra in C via LAPACKE

When to choose

• you need a battle-tested, standard implementation of dense linear algebra routines
• you are building math/scientific software that other packages depend on
• you need C bindings to Fortran linear algebra routines

When to avoid

• you need GPU-accelerated linear algebra (consider cuSOLVER or MAGMA)
• you want a high-level ergonomic API in Python or Julia (use NumPy/SciPy instead)
• you only need simple matrix operations already covered by BLAS

Facets

library · maturity stable

math sdk mathematics developer-tools cross-platform windows cpp python linear-algebra blas lapacke eigenvalues svd matrix-factorization fortran numerical-computing algorithms linux macos

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