Using Level 3 BLAS in Rotation-Based Algorithms

DOI10.1137/S1064827595280211zbMath0912.65032MaRDI QIDQ4389262

Bruno Lang

Publication date: 12 May 1998

Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)

zbMATH Keywords

convergenceQR algorithmperformance modelingBLAS 3rotation-based algorithms

Mathematics Subject Classification ID

Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Complexity and performance of numerical algorithms (65Y20)

Related Items (10)

Parallel and Heterogeneous $m$--Hessenberg--Triangular--Triangular Reduction ⋮ Increasing data locality and introducing level-3 BLAS in the neville elimination ⋮ Distributed One-Stage Hessenberg-Triangular Reduction with Wavefront Scheduling ⋮ On pole-swapping algorithms for the eigenvalue problem ⋮ Parallel reduction of four matrices to condensed form for a generalized matrix eigenvalue algorithm ⋮ Blocked algorithms for the reduction to Hessenberg-triangular form revisited ⋮ Restructuring the Tridiagonal and Bidiagonal QR Algorithms for Performance ⋮ An Input/Output Efficient Algorithm for Hessenberg Reduction ⋮ Efficient algorithm for simultaneous reduction to the \(m\)-Hessenberg-triangular-triangular form ⋮ Algorithms for Hessenberg-Triangular Reduction of Fiedler Linearization of Matrix Polynomials

Uses Software

• LAPACK
• BLAS

Cites Work

• An extended set of FORTRAN basic linear algebra subprograms
• Basic Linear Algebra Subprograms for Fortran Usage
• A set of level 3 basic linear algebra subprograms
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