Topic
Basic Linear Algebra Subprograms
About: Basic Linear Algebra Subprograms is a research topic. Over the lifetime, 388 publications have been published within this topic receiving 19103 citations. The topic is also known as: BLAS.
Papers published on a yearly basis
Papers
TL;DR: This paper describes an extension to the set of Basic Linear Algebra Subprograms targeted at matrix-vector operations that should provide for efficient and portable implementations of algorithms for high-performance computers.
Abstract: This paper describes an extension to the set of Basic Linear Algebra Subprograms. The extensions are targeted at matrix-vector operations that should provide for efficient and portable implementations of algorithms for high-performance computers
2,110 citations
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1 Jan 1987
TL;DR: General matrices Band matrices positive definite matrices Positive definite band matrices Symmetric Indefinite Matrices Triangular matrices Tridiagonal matrices The Cholesky decomposition The QR decomposition up to and including the singular value decomposition is studied.
Abstract: General matrices Band matrices Positive definite matrices Positive definite band matrices Symmetric Indefinite Matrices Triangular matrices Tridiagonal matrices The Cholesky decomposition The QR decomposition Updating QR and Cholesky decompositions The singular value decomposition References Basic linear algebra subprograms Timing data Program listings BLA Listings.
1,763 citations
1 Jan 2001
TL;DR: The automatically tuned linear algebra software (ATLAS) project is described, as well as the fundamental principles that underly it, with the present emphasis on the basic linear algebra subprograms (BLAS), a widely used, performance-critical, linear algebra kernel library.
Abstract: This paper describes the automatically tuned linear algebra software (ATLAS) project, as well as the fundamental principles that underly it. ATLAS is an instantiation of a new paradigm in high performance library production and maintenance, which we term automated empirical optimization of software (AEOS); this style of library management has been created in order to allow software to keep pace with the incredible rate of hardware advancement inherent in Moore's Law. ATLAS is the application of this new paradigm to linear algebra software, with the present emphasis on the basic linear algebra subprograms (BLAS), a widely used, performance-critical, linear algebra kernel library.
1,416 citations
1 Jan 1987
TL;DR: In this article, a model implementation and test software for Level 2 Basic Linear Algebra Subprograms (Level 2 BLAS) is described, targeted at matrix-vector operations with the aim of providing more efficient, but portable, implementations of algorithms on high-performance computers.
Abstract: This paper describes a model implementation and test software for the Level 2 Basic Linear Algebra Subprograms (Level 2 BLAS). The Level 2 BLAS are targeted at matrix-vector operations with the aim of providing more efficient, but portable, implementations of algorithms on high-performance computers. The model implementation provides a portable set of Fortran 77 Level 2 BLAS for machines where specialized implementations do not exist or are not required. The test software aims to verify that specialized implementations meet the specification of the Level 2 BLAS and that implementations are correctly installed.
942 citations
TL;DR: The basic principles that underlie the high-performance implementation of the matrix-matrix multiplication that is part of the widely used GotoBLAS library are presented.
Abstract: We present the basic principles that underlie the high-performance implementation of the matrix-matrix multiplication that is part of the widely used GotoBLAS library. Design decisions are justified by successively refining a model of architectures with multilevel memories. A simple but effective algorithm for executing this operation results. Implementations on a broad selection of architectures are shown to achieve near-peak performance.
885 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2022 | 1 |
| 2021 | 11 |
| 2020 | 14 |
| 2019 | 11 |
| 2018 | 11 |
| 2017 | 13 |