Abstract
In this work, numerical algebraic operations are performed by using several libraries whose algorithm are optimized to drain resources from hardware architecture. In particular, dot product of two vectors and the matrix-matrix product of two dense matrices are computed. In addition, the Cholesky decomposition on a real, symmetric, and positive definite matrix is performed through routines for band and sparse matrix storage. The involved CPU time is used as an indicator of the performance of the employed numerical tool. Results are compared to naive implementations of the same numerical algorithm, highlighting the speed-up due to the usage of optimized routines.
© 2015 by Walter de Gruyter Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- A multipoint Birkhoff type boundary value problem
- Performance estimation of linear algebra numerical libraries
- Finite element analysis of the stationary power-law Stokes equations driven by friction boundary conditions
- Chebyshev polynomials and best approximation of some classes of functions
- Multigrid methods for Hdiv-conforming discontinuous Galerkin methods for the Stokes equations
- Unified error bounds for all Newton–Cotes quadrature rules
- Optimal bilinear control of eddy current equations with grad–div regularization
Artikel in diesem Heft
- Frontmatter
- A multipoint Birkhoff type boundary value problem
- Performance estimation of linear algebra numerical libraries
- Finite element analysis of the stationary power-law Stokes equations driven by friction boundary conditions
- Chebyshev polynomials and best approximation of some classes of functions
- Multigrid methods for Hdiv-conforming discontinuous Galerkin methods for the Stokes equations
- Unified error bounds for all Newton–Cotes quadrature rules
- Optimal bilinear control of eddy current equations with grad–div regularization