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Parallel Frontal Solvers for Large Sparse Linear Systems

by Jennifer A. Scott - COMPUTERS IN CHEMICAL ENGINEERING , 2003
"... Many applications in science and engineering give rise to large sparse linear systems of equations that need to be solved as efficiently as possible. As the size of the problems of interest in-creases, it can become necessary to consider exploiting multiprocessors to solve these systems. We report o ..."
Abstract - Cited by 12 (2 self) - Add to MetaCart
Many applications in science and engineering give rise to large sparse linear systems of equations that need to be solved as efficiently as possible. As the size of the problems of interest in-creases, it can become necessary to consider exploiting multiprocessors to solve these systems. We report

Solving Large Sparse Linear Systems Over Finite Fields

by B. A. Lamacchia, A. M. Odlyzko , 1991
"... Many of the fast methods for factoring integers and computing discrete logarithms require the solution of large sparse linear systems of equations over finite fields. This paper presents the results of implementations of several linear algebra algorithms. It shows that very large sparse systems can ..."
Abstract - Cited by 89 (3 self) - Add to MetaCart
Many of the fast methods for factoring integers and computing discrete logarithms require the solution of large sparse linear systems of equations over finite fields. This paper presents the results of implementations of several linear algebra algorithms. It shows that very large sparse systems can

Multipole-based preconditioners for large sparse linear systems

by Sreekanth R. Sambavaram A, Vivek Sarin A, Ahmed Sameh B, Ananth Grama B , 2003
"... Dense operators for preconditioning sparse linear systems have traditionally been considered infeasible due to their excessive computational and memory requirements. With the emergence of techniques such as block low-rank approximations and hierarchical multipole approximations, the cost of computin ..."
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Dense operators for preconditioning sparse linear systems have traditionally been considered infeasible due to their excessive computational and memory requirements. With the emergence of techniques such as block low-rank approximations and hierarchical multipole approximations, the cost

large sparse linear systems over GF(2)

by Thorsten Kleinjung, Lucas Nussbaum, Projet Algorille, Loria Université Nancy, Emmanuel Thomé
"... Using a grid platform for solving ..."
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Using a grid platform for solving

Amesos2 and Belos: Direct and iterative solvers for large sparse linear systems

by Eric Bavier, Mark Hoemmen, Sivasankaran Rajamanickam, Heidi Thornquist - Scientific Programming , 2012
"... Solvers for large sparse linear systems come in two categories: di-rect and iterative. Amesos2, a package in the Trilinos software project, provides direct methods, and Belos, another Trilinos package, provides iterative methods. Amesos2 offers a common interface to many different sparse matrix fact ..."
Abstract - Cited by 7 (6 self) - Add to MetaCart
Solvers for large sparse linear systems come in two categories: di-rect and iterative. Amesos2, a package in the Trilinos software project, provides direct methods, and Belos, another Trilinos package, provides iterative methods. Amesos2 offers a common interface to many different sparse matrix

Parallel multilevel block ILU preconditioning techniques for large sparse linear systems

by Chi Shen, Jun Zhang, Kai Wang - In Proceedings of International Parallel and Distributed Processing Symposium , 2003
"... We present a class of parallel preconditioning strategies built on a multilevel block incomplete LU (ILU) factorization technique to solve large sparse linear systems on distributed memory parallel computers. The preconditioners are constructed by using the concept of block independent sets. Two alg ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
We present a class of parallel preconditioning strategies built on a multilevel block incomplete LU (ILU) factorization technique to solve large sparse linear systems on distributed memory parallel computers. The preconditioners are constructed by using the concept of block independent sets. Two

A Sparse QS-Decomposition for Large Sparse Linear System of Equations

by Wujian Peng , Biswa N Datta
"... Summary. A direct solver for large scale sparse linear system of equations is presented in this paper. As a direct solver, this method is among the most efficient direct solvers available so far with flop count as O(n logn) in one-dimensional situations and O(n 3/2 ) in second dimensional situation ..."
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Summary. A direct solver for large scale sparse linear system of equations is presented in this paper. As a direct solver, this method is among the most efficient direct solvers available so far with flop count as O(n logn) in one-dimensional situations and O(n 3/2 ) in second dimensional

The Efficient Parallel Iterative Solution Of Large Sparse Linear Systems

by Mark T. Jones, Paul E. Plassmann , 1992
"... The development of efficient, general-purpose software for the iterative solution of sparse linear systems on a parallel MIMD computer requires an interesting combination of expertise. Parallel graph heuristics, convergence analysis, and basic linear algebra implementation issues must all be conside ..."
Abstract - Cited by 9 (0 self) - Add to MetaCart
The development of efficient, general-purpose software for the iterative solution of sparse linear systems on a parallel MIMD computer requires an interesting combination of expertise. Parallel graph heuristics, convergence analysis, and basic linear algebra implementation issues must all

Process Scheduling in DSC and the Large Sparse Linear Systems Challenge

by A. Díaz, A. D Iaz, M. Hitz, E. Kaltofen, A. Lobo, T. Valente - J. Symbolic Comput , 1998
"... this paper appeared in "Design and Implementation of Symbolic Computation Systems," A. Miola (ed.), Springer Lect. Notes Comput. Science, 722, 66--80 (1993). ..."
Abstract - Cited by 8 (3 self) - Add to MetaCart
this paper appeared in "Design and Implementation of Symbolic Computation Systems," A. Miola (ed.), Springer Lect. Notes Comput. Science, 722, 66--80 (1993).

Parallel Solution of Large Sparse Linear Systems by a Balance Scheme Preconditioner

by Tz Ostromsky , A Sameh , V Sarin
"... Abstract A parallel algorithm for preconditioning large and sparse linear systems is proposed. Both structural and numerical dropping are used to construct a preconditioner with proper structure. The Balance method is used to solve the linear system involving such preconditioner in each iteration. ..."
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Abstract A parallel algorithm for preconditioning large and sparse linear systems is proposed. Both structural and numerical dropping are used to construct a preconditioner with proper structure. The Balance method is used to solve the linear system involving such preconditioner in each iteration
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