Dense systems of linear equations are quite common in many science and engineering applications. Such linear systems place extreme storage and computational demands on computer resources and, in many cases, may severely limit the subsequent analysis. A dense out-of-core solver (DOCS) that operates on a partitioned coefficient matrix can reduce the in-core storage requirements of the linear system while spreading the associated computational burden over multiple processors (which reduces run time as well). In this report, I describe a DOCS that operates on a partitioned coefficient matrix that maybe distributed over multiple external storage devices. I have implemented this solver using Message-Passing Interface (MPI) protocols. This report ...
This research proposes an effective implementation of linear equation solver for an implicit integra...
(eng) The memory usage of sparse direct solvers can be the bottleneck to solve large-scale problems ...
In a previous PPoPP paper we showed how the FLAME method-ology, combined with the SuperMatrix runtim...
Abstract: Few realize that, for large matrices, many dense matrix computations achieve nearly the sa...
In this paper, we describe the design and implementation of the Platform Independent Parallel Solver...
International audienceABSTRACT The memory usage of sparse direct solvers can be the bottleneck to so...
HDSS (Huge Dense Linear System Solver) is a Fortran Application Programming Interface (API) to facil...
This research evaluates the applicability to microcomputers of various methods for determining the s...
The huge amount of memory is needed for solving the large-scale linear equations. However, many prob...
Few realize that, for large matrices, many dense matrix computations achieve nearly the same perform...
The solution of dense systems of linear equations is at the heart of numerical computations. Such sy...
International audienceThe increasing complexity of new parallel architectures has widened the gap be...
Out-of-core implementations of algorithms for dense matrix computations have traditionally focused o...
Factorizing a sparse matrix is a robust way to solve large sparse systems of linear equations. Howev...
Solution of large sparse linear systems is frequently the most time consuming operation in computati...
This research proposes an effective implementation of linear equation solver for an implicit integra...
(eng) The memory usage of sparse direct solvers can be the bottleneck to solve large-scale problems ...
In a previous PPoPP paper we showed how the FLAME method-ology, combined with the SuperMatrix runtim...
Abstract: Few realize that, for large matrices, many dense matrix computations achieve nearly the sa...
In this paper, we describe the design and implementation of the Platform Independent Parallel Solver...
International audienceABSTRACT The memory usage of sparse direct solvers can be the bottleneck to so...
HDSS (Huge Dense Linear System Solver) is a Fortran Application Programming Interface (API) to facil...
This research evaluates the applicability to microcomputers of various methods for determining the s...
The huge amount of memory is needed for solving the large-scale linear equations. However, many prob...
Few realize that, for large matrices, many dense matrix computations achieve nearly the same perform...
The solution of dense systems of linear equations is at the heart of numerical computations. Such sy...
International audienceThe increasing complexity of new parallel architectures has widened the gap be...
Out-of-core implementations of algorithms for dense matrix computations have traditionally focused o...
Factorizing a sparse matrix is a robust way to solve large sparse systems of linear equations. Howev...
Solution of large sparse linear systems is frequently the most time consuming operation in computati...
This research proposes an effective implementation of linear equation solver for an implicit integra...
(eng) The memory usage of sparse direct solvers can be the bottleneck to solve large-scale problems ...
In a previous PPoPP paper we showed how the FLAME method-ology, combined with the SuperMatrix runtim...