Environmental enquiry function that returns values for tuning algorithmic performance.
This section describes the ScaLAPACK routines for solving systems of linear equations. Before calling most of these routines, you need to factorize the matrix of your system of equations (see Routines for Matrix Factorization in this chapter). However, the factorization is not necessary if your system of equations has a triangular matrix.
Provides error bounds and backward error estimates for the solution to a system of linear equations with a distributed triangular coefficient matrix.
Generates the real orthogonal matrix Q of the LQ factorization formed by p?gelqf.
Reduces the upper trapezoidal matrix A to upper triangular form.
Computes the eigenvectors of a tridiagonal matrix using inverse iteration.
Computes the solution to the system of linear equations with a square distributed matrix and multiple right-hand sides.
Computes selected eigenvalues and, optionally, eigenvectors of a Hermitian matrix using Relatively Robust Representation.
Computes an LU factorization of a general triangular matrix with no pivoting. The routine is called by p?dbtrs.