lapak77 - An Overview
lapak77 - An Overview
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These tasks give a similar operation to LAPACK, but by using a primary interface differing from that of LAPACK:
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LAPACK ("Linear Algebra Package") is an ordinary application library for numerical linear algebra. It provides routines for solving programs of linear equations and linear minimum squares, eigenvalue problems, and singular value decomposition. What's more, it incorporates routines to implement the linked matrix factorizations for instance LU, QR, Cholesky and Schur decomposition.
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Just like BLAS, LAPACK is sometimes forked or rewritten to offer better general performance on particular programs. A lot of the implementations are:
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mm is often a two-letter code denoting the type of matrix predicted with the algorithm. The codes for the several type of matrices are reported below; the particular details are stored in a special format dependant upon the certain type; e.
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Because LAPACK typically calls fundamental BLAS routines to carry out the bulk of its computations, simply just linking to an improved-tuned BLAS implementation may be ample to significantly increase performance. Because of this, LAPACK will not be reimplemented as normally as BLAS is. Comparable assignments[edit]
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A header library for linear algebra. Has a BLAS and also a partial LAPACK implementation for compatibility.
LAPACK was designed as being the successor to the linear equations and linear minimum-squares routines of LINPACK and the eigenvalue routines of EISPACK. LINPACK, prepared during the 1970s and eighties, was meant to run around the then-present day vector desktops with shared memory. LAPACK, in distinction, was designed to successfully exploit the caches on modern day cache-dependent architectures and the instruction-level parallelism of modern superscalar processors,[2]: "Components that Impact Overall performance" and thus can operate orders of magnitude speedier than LINPACK on these devices, provided a nicely-tuned BLAS implementation.