A new stable method for the reduction of rectangular dense matrices to bidiagonal form has been proposed recently. This is a one-sided method since it can be entirely expressed in terms of operations with (full) columns of the matrix under transformation. The algorithm is well suited to parallel computing and, in order to make it even more attractive for distributed memory systems, we introduce a modification which halves the number of communication instances. In this paper we present such a modification. A block organization of the algorithm to use level~3 BLAS routines seems difficult and, at least for the moment, it relies upon level~2 BLAS routines. Nevertheless, we found that our sequential code is competitive with the LAPACK...
International audienceWe present block algorithms and their implementation for the parallelization o...
We present a distributed-memory library for computations with dense structured matrices. A matrix is...
AbstractA new bidiagonal reduction method is proposed for X∈Rm×n. For m⩾n, it decomposes X into the ...
International audienceWe study tiled algorithms for going from a " full " matrix to a condensed " ba...
We consider algorithms for going from a ``full'' matrix to a condensed``band bidiagonal'' form using...
Most methods for calculating the SVD (singular value decomposition) require to first bidiagonalize t...
AbstractWe present an idea for reducing a rectangular matrix A to bidiagonal form which is based on ...
AbstractFour parallel algorithms for the solution of block bidiagonal linear systems on distributed ...
Abstract. The objective of this paper is to extend, in the context of multicore architectures, the c...
The objective of this paper is to extend, in the context of multicore architectures, the concepts of...
This paper presents a new efficient algorithm for solving bidiagonal systems of linear equations on ...
International audienceWe present a new parallel algorithm to compute an exact triangularization of l...
International audienceThis special issue of Parallel Computing contains nine articles, selected afte...
Structured dense matrices result from boundary integral problems in electrostatics and geostatistics...
The polyalgorithm library, originally designed in 1991-1993 by Robert Falgout, Jin Li, and Anthony S...
International audienceWe present block algorithms and their implementation for the parallelization o...
We present a distributed-memory library for computations with dense structured matrices. A matrix is...
AbstractA new bidiagonal reduction method is proposed for X∈Rm×n. For m⩾n, it decomposes X into the ...
International audienceWe study tiled algorithms for going from a " full " matrix to a condensed " ba...
We consider algorithms for going from a ``full'' matrix to a condensed``band bidiagonal'' form using...
Most methods for calculating the SVD (singular value decomposition) require to first bidiagonalize t...
AbstractWe present an idea for reducing a rectangular matrix A to bidiagonal form which is based on ...
AbstractFour parallel algorithms for the solution of block bidiagonal linear systems on distributed ...
Abstract. The objective of this paper is to extend, in the context of multicore architectures, the c...
The objective of this paper is to extend, in the context of multicore architectures, the concepts of...
This paper presents a new efficient algorithm for solving bidiagonal systems of linear equations on ...
International audienceWe present a new parallel algorithm to compute an exact triangularization of l...
International audienceThis special issue of Parallel Computing contains nine articles, selected afte...
Structured dense matrices result from boundary integral problems in electrostatics and geostatistics...
The polyalgorithm library, originally designed in 1991-1993 by Robert Falgout, Jin Li, and Anthony S...
International audienceWe present block algorithms and their implementation for the parallelization o...
We present a distributed-memory library for computations with dense structured matrices. A matrix is...
AbstractA new bidiagonal reduction method is proposed for X∈Rm×n. For m⩾n, it decomposes X into the ...