BLASLAPACK

BLASLAPACK is a term used to describe a unified approach to exposing and using the core linear algebra capabilities provided by the BLAS (Basic Linear Algebra Subprograms) and LAPACK (Linear Algebra PACKage) libraries. In this concept, a single package or interface presents both the low-level, highly optimized BLAS kernels and the higher-level LAPACK routines for factorization, solving linear systems, eigenvalue problems, singular value decompositions, and related tasks. The goal is to give developers a consistent, cross-language entry point to robust, high-performance linear algebra operations.

Typically, a BLASLAPACK implementation acts as a wrapper or abstraction layer that can dispatch routines to available backends, such as OpenBLAS, Intel MKL, ATLAS, or vendor-provided libraries. It emphasizes portability across platforms and languages while maintaining performance by leveraging optimized backends for specific hardware. Important design considerations include support for common data layouts (such as column-major and row-major formats), threading models, and error handling. Many BLASLAPACK-style projects also offer language bindings or interfaces for C, C++, Fortran, Python, and other languages, along with tutorials and documentation to facilitate integration into scientific and engineering software.

Use cases for BLASLAPACK-style libraries include numerical simulations, data analysis, and engineering computations that require reliable matrix operations, linear system solvers, eigenvalue analyses, and matrix factorizations. While BLAS and LAPACK are separate standards, BLASLAPACK represents a practical pattern for providing a single, cohesive access point to both families of routines, often through wrappers or multi-backend configurations to maximize portability and performance.