We describe a new extension to ScaLAPACK [2] for computing with symmetric (Hermitian) matrices stored in a packed form. The new code is built upon the ScaLAPACK routines for full dense storage for a high degree of software reuse. The original ScaLAPACK stores a symmetric matrix as a full matrix but accesses only the lower or upper triangular part. The new code enables more efficient use of memory by storing only the lower or upper triangular part of a symmetric (Hermitian) matrix. The packed storage scheme distributes the matrix by block column panels. Within each panel, the matrix is stored as a regular ScaLAPACK matrix. This storage arrangement simplifies the subroutine interface and code reuse. Routines PxPPTRF/PxPPTRS implement the Chol...
We present subroutines for the Cholesky factorization of a positive-definite symmetric matrix and fo...
Abstract. The sequential algorithm of Multiple Relatively Robust Representations, MRRR, can compute ...
In this dissertation we have identified vector processing shortcomings related to the efficient stor...
The authors describe a new extension to ScaLAPACK for computing with symmetric (Hermitian) matrices ...
ABSTRACT: Recently codes have been developed for computing the Cholesky factorization with complete ...
The irregular nature of sparse matrix-vector multiplication, Ax = y, has led to the development of a...
The irregular nature of sparse matrix-vector multiplication, Ax = y, has led to the development of a...
The handling of the sparse matrix vector product(SMVP) is a common kernel in many scientific applica...
An important kernel of scientific software is the multiplication of a sparse matrix by a vector. The...
The handling of the sparse matrix vector product(SMVP) is a common kernel in many scientific applica...
AbstractWe propose a new storage scheme (word packing) for matrices with elements in Z2 that enables...
The sphere optimization program sphopt was originally written as a sequential program using LAPACK, ...
This contribution describes a Square Block, SB, format for storing a banded symmetric matrix. This i...
The paper describes a storage scheme for sparse symmetric or nonsymmetric matrices which has b...
This paper describes a new implementation of algorithms for solving large, dense symmetric eigen-pro...
We present subroutines for the Cholesky factorization of a positive-definite symmetric matrix and fo...
Abstract. The sequential algorithm of Multiple Relatively Robust Representations, MRRR, can compute ...
In this dissertation we have identified vector processing shortcomings related to the efficient stor...
The authors describe a new extension to ScaLAPACK for computing with symmetric (Hermitian) matrices ...
ABSTRACT: Recently codes have been developed for computing the Cholesky factorization with complete ...
The irregular nature of sparse matrix-vector multiplication, Ax = y, has led to the development of a...
The irregular nature of sparse matrix-vector multiplication, Ax = y, has led to the development of a...
The handling of the sparse matrix vector product(SMVP) is a common kernel in many scientific applica...
An important kernel of scientific software is the multiplication of a sparse matrix by a vector. The...
The handling of the sparse matrix vector product(SMVP) is a common kernel in many scientific applica...
AbstractWe propose a new storage scheme (word packing) for matrices with elements in Z2 that enables...
The sphere optimization program sphopt was originally written as a sequential program using LAPACK, ...
This contribution describes a Square Block, SB, format for storing a banded symmetric matrix. This i...
The paper describes a storage scheme for sparse symmetric or nonsymmetric matrices which has b...
This paper describes a new implementation of algorithms for solving large, dense symmetric eigen-pro...
We present subroutines for the Cholesky factorization of a positive-definite symmetric matrix and fo...
Abstract. The sequential algorithm of Multiple Relatively Robust Representations, MRRR, can compute ...
In this dissertation we have identified vector processing shortcomings related to the efficient stor...