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C API for the Linear Algebra PACKage

Innovative Computing Laboratory

University of Tennessee

[TOC]

The Linear Algebra PACKage (LAPACK) is a standard software library for numerical linear algebra. It provides routines for solving systems of linear equations and linear least squares problems, eigenvalue problems, and singular value decomposition. It also includes routines to implement the associated matrix factorizations such as LU, QR, Cholesky, etc. LAPACK was originally written in FORTRAN 77, and moved to Fortran 90 in version 3.2 (2008). LAPACK provides routines for handling both real and complex matrices in both single and double precision.

The objective of LAPACK is to provide a convenient, performance oriented API for development in the C language, that, for the most part, preserves established conventions, while, at the same time, takes advantages of modern C features, such as: namespaces, templates, exceptions, etc.

LAPACK is part of the SLATE project (Software for Linear Algebra Targeting Exascale), which is funded by the Department of Energy as part of its Exascale Computing Initiative (ECP). Closely related to LAPACK is the BLAS project, which provides a C API for BLAS and Batch BLAS.

• INSTALL.md for installation notes.
• LAPACK Doxygen
• SLATE Working Note 2: C API for BLAS and LAPACK

For assistance, visit the SLATE User Forum at https://groups.google.com/a/icl.utk.edu/forum/#!forum/slate-user. Join by signing in with your Google credentials, then clicking Join group to post.

Bug reports can be filed directly on Github's issue tracker: https://github.com/icl-utk-edu/lapackpp/issues.

• Visit the BLAS repository for more information about the C API for the standard BLAS.
• Visit the SLATE website for more information about the SLATE project.
• Visit the SLATE Working Notes to find out more about ongoing SLATE developments.
• Visit the ECP website to find out more about the DOE Exascale Computing Initiative.

The SLATE project welcomes contributions from new developers. Contributions can be offered through the standard Github pull request model. We strongly encourage you to coordinate large contributions with the SLATE development team early in the process.

This research was supported by the Exascale Computing Project (17-SC-20-SC), a joint project of the U.S. Department of Energy's Office of Science and National Nuclear Security Administration, responsible for delivering a capable exascale ecosystem, including software, applications, and hardware technology, to support the nation’s exascale computing imperative.

This research uses resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725. This research also uses resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357.

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