LAPACK ("Linear Algebra Package") is a standard software library for numerical linear algebra. It provides routines for solving systems of linear equations and linear least squares, eigenvalue problems, and singular value decomposition. It also includes routines to implement the associated matrix factorizations such as LU, QR, Cholesky and Schur decomposition. LAPACK was originally written in FORTRAN 77, but moved to Fortran 90 in version 3.2 (2008). The routines handle both real and complex matrices in both single and double precision. LAPACK relies on an underlying BLAS implementation to pro
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LAPACK is a library of Fortran subroutines for solving the most commonly occurring problems in numerical linear algebra. LAPACK is a freely-available software package. It can be included in commercial software packages (and has been). We only ask that that proper credit be given to the authors, for example by citing the LAPACK Users' Guide. The license used for the software is the modified BSD license. LAPACK is available from GitHub. LAPACK releases are also available on netlib. Installation LAPACK can be installed with make . The configuration must be set in the make.inc file. A make.inc.example for a Linux machine running GNU compilers is given in the main directory. Some specific make.inc are also available in the INSTALL directory. LAPACK includes also the CMake build. You will need to have CMake installed on your machine. CMake will allow an easy installation on a Windows Machine. An example CMake build to install the LAPACK library under $HOME/.local/lapack/ is: LAPACK can be built and installed using vcpkg dependency manager: LAPACK has been thoroughly tested, on many different types of computers. The LAPACK project supports the package in the sense that reports of errors or poor performance will gain immediate attention from the developers. Such reports, descriptions of interesting applications, and other comments should be sent by email to the LAPACK team. A list of known problems, bugs, and compiler errors for LAPACK is maintained on netlib. Please see as well the GitHub issue tracker. For further information on LAPACK please read our FAQ and Users' Guide. A user forum and specific information for running LAPACK under Windows are also available to help you with the LAPACK library. LAPACK includes a thorough test suite. We recommend that, after compilation, you run the test suite. For complete information on the LAPACK Testing please consult LAPACK Working Note 41 "Installation Guide for LAPACK". LAPACK now includes the LAPACKE package. LAPACKE is a Standard C language API for LAPACK that was born from a collaboration of the LAPACK and INTEL Math Kernel Library teams.
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LAPACK ("Linear Algebra Package") is a standard software library for numerical linear algebra. It provides routines for solving systems of linear equations and linear least squares, eigenvalue problems, and singular value decomposition. It also includes routines to implement the associated matrix factorizations such as LU, QR, Cholesky and Schur decomposition. LAPACK was originally written in FORTRAN 77, but moved to Fortran 90 in version 3.2 (2008). The routines handle both real and complex matrices in both single and double precision. LAPACK relies on an underlying BLAS implementation to provide efficient and portable computational building blocks for its routines.
LAPACK was designed as the successor to the linear equations and linear least-squares routines of LINPACK and the eigenvalue routines of EISPACK. LINPACK, written in the 1970s and 1980s, was designed to run on the then-modern vector computers with shared memory. LAPACK, in contrast, was designed to effectively exploit the caches on modern cache-based architectures and the instruction-level parallelism of modern superscalar processors, and thus can run orders of magnitude faster than LINPACK on such machines, given a well-tuned BLAS implementation. LAPACK has also been extended to run on distributed memory systems in later packages such as ScaLAPACK and PLAPACK.
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Discovered by embedding cosine similarity (sentence-transformers MiniLM, 384-dim).