We present subroutines for the Cholesky factorization of a positive-definite symmetric matrix and for solving corresponding sets of linear equations. They exploit cache memory by using the block hybrid format proposed by the authors in a companion article. The matrix is packed into n(n+1)/2 real variables, and the speed is usually better than that of the LAPACK algorithm that uses full storage (n2 variables). Included are subroutines for rearranging a matrix whose upper or lower-triangular part is packed by columns to this format and for the inverse rearrangement. Also included is a kernel subroutine that is used for the Cholesky factorization of the diagonal blocks since it is suitable for any positive-definite symmetric matrix that is sma...
Recursion leads to automatic variable blocking for dense linear‐algebra algorithms. The recursive wa...
This work studies limited memory preconditioners for linear symmetric positive definite systems of e...
The process of factorizing a symmetric matrix using the Cholesky (LLT ) or indefinite (LDLT ) factor...
This article, aimed at a general audience of computational scientists, surveys the Cholesky factoriz...
Linear systems and the solving of those is an important tool in many areas of science. The solving o...
was supported by an EPSRC Research Studentship. Abstract. Routines exist in LAPACK for computing the...
Routines exist in LAPACK for computing the Cholesky factorization of a symmetric positive definite m...
We describe a parallel algorithm for finding the Cholesky factorization of a sparse symmetric posit...
Given a symmetric and not necessarily positive definite matrix A, a modified Cholesky algorithm comp...
Cholesky factorization is a type of matrix factorization which is used for solving system of linear ...
AbstractStarting from the Strassen method for rapid matrix multiplication and inversion as well as f...
. Given a symmetric and not necessarily positive definite matrix A, a modified Cholesky algorithm co...
This note concerns the computation of the Cholesky factorization of a symmetric and positive defini...
In this paper we present a new parallel algorithm for computing the Cholesky decomposition (LL^T) of...
We develop an algorithm for computing the symbolic and numeric Cholesky factorization of a large sp...
Recursion leads to automatic variable blocking for dense linear‐algebra algorithms. The recursive wa...
This work studies limited memory preconditioners for linear symmetric positive definite systems of e...
The process of factorizing a symmetric matrix using the Cholesky (LLT ) or indefinite (LDLT ) factor...
This article, aimed at a general audience of computational scientists, surveys the Cholesky factoriz...
Linear systems and the solving of those is an important tool in many areas of science. The solving o...
was supported by an EPSRC Research Studentship. Abstract. Routines exist in LAPACK for computing the...
Routines exist in LAPACK for computing the Cholesky factorization of a symmetric positive definite m...
We describe a parallel algorithm for finding the Cholesky factorization of a sparse symmetric posit...
Given a symmetric and not necessarily positive definite matrix A, a modified Cholesky algorithm comp...
Cholesky factorization is a type of matrix factorization which is used for solving system of linear ...
AbstractStarting from the Strassen method for rapid matrix multiplication and inversion as well as f...
. Given a symmetric and not necessarily positive definite matrix A, a modified Cholesky algorithm co...
This note concerns the computation of the Cholesky factorization of a symmetric and positive defini...
In this paper we present a new parallel algorithm for computing the Cholesky decomposition (LL^T) of...
We develop an algorithm for computing the symbolic and numeric Cholesky factorization of a large sp...
Recursion leads to automatic variable blocking for dense linear‐algebra algorithms. The recursive wa...
This work studies limited memory preconditioners for linear symmetric positive definite systems of e...
The process of factorizing a symmetric matrix using the Cholesky (LLT ) or indefinite (LDLT ) factor...