the entries of the matrix. aaa is a one- to three-letter code describing the actual algorithm implemented in the subroutine, e.g. SV denotes a subroutine to solve linear system, while R denotes a rank-1 update. For example, the subroutine to solve a linear system with a general (non-structured) matrix using real double-precision arithmetic is called DGESV. Use with other programming languages and libraries Many programming environments today support the use of libraries with C binding, allowing LAPACK routines to be used directly so long as a few restrictions are observed. Additionally, many other software libraries and tools for scientific and numerical computing are built on top of LAPACK, such as R, MATLAB, and SciPy. Several alternative language bindings are also available: Armadillo for C++ IT++ for C++ LAPACK++ for C++ Lacaml for OCaml CLapack for C SciPy for Python Gonum for Go NLapack for .NET Implementations As with BLAS, LAPACK is sometimes forked or rewritten to provide better performance on specific systems. Some of the implementations are: Accelerate Apple's framework for macOS and iOS, which includes tuned versions of BLAS and LAPACK. Netlib LAPACK The official LAPACK. Netlib ScaLAPACK Scalable (multicore) LAPACK, built on top of PBLAS. Intel MKL Intel's Math routines for their x86 CPUs. OpenBLAS Open-source reimplementation of BLAS and LAPACK. Gonum LAPACK A partial native Go implementation. Since LAPACK typically calls underlying BLAS routines to perform the bulk of its computations, simply linking to a better-tuned BLAS implementation can be enough to significantly improve performance. As a result, LAPACK is not reimplemented as often as BLAS is. Similar projects These projects provide a similar functionality to LAPACK, but with a main interface differing from that of LAPACK: Libflame A dense linear algebra library. Has a LAPACK-compatible wrapper. Can be used with any BLAS, although BLIS is the preferred implementation. Eigen A header library for linear algebra. Has a BLAS and a partial LAPACK implementation for compatibility. MAGMA Matrix Algebra on GPU and Multicore Architectures (MAGMA) project develops a dense linear algebra library similar to LAPACK but for heterogeneous and hybrid architectures including multicore systems accelerated with GPGPUs. PLASMA The Parallel Linear Algebra for Scalable Multi-core Architectures (PLASMA) project is a modern replacement of LAPACK for multi-core architectures. PLASMA is a software framework for development of asynchronous operations and features out of order scheduling with a runtime scheduler called QUARK that may be used for any code that