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C++ API for the Basic Linear Algebra Subroutines
Innovative Computing Laboratory
University of Tennessee
The Basic Linear Algebra Subprograms (BLAS) have been around for many decades and serve as the de facto standard for performance-portable and numerically robust implementation of essential linear algebra functionality. Originally, they were written in Fortran, and later furnished with a C API (CBLAS).
The objective of BLAS++ 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.
BLAS++ is part of the project Software for Linear Algebra Targeting Exascale (SLATE), which is funded by the Department of Energy as part of its Exascale Computing Initiative (ECP). Closely related to BLAS++ is the LAPACK++ project, which provides a C++ API for LAPACK.
- BLAS++ Doxygen
- SLATE Working Note 2: C++ API for BLAS and LAPACK
- SLATE Working Note 4: C++ API for Batch BLAS
For assistance with SLATE, email firstname.lastname@example.org.
You can also join the SLATE User Google group by going to
signing in with your Google credentials, and then clicking
- Visit the LAPACK++ repository for more information about the C++ API for LAPACK.
- Visit the ECP website to find out more about the DOE Exascale Computing Initiative.
- Visit the SLATE website for more information about the SLATE project.
- Visit the SLATE Working Notes to find out more about ongoing SLATE developments.
The SLATE project welcomes contributions from new developers. Contributions can be offered through the standard Bitbucket pull request model. We ask that you complete and submit a contributor agreement. There are two versions of the agreement, one for individuals, and one for organizations. Please look at both to determine which is right for you. 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 collaborative effort of two U.S. Department of Energy organizations (Office of Science and the National Nuclear Security Administration) responsible for the planning and preparation of a capable exascale ecosystem, including software, applications, hardware, advanced system engineering and early testbed platforms, in support of 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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