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Parallel Frontal Solvers for Large Sparse Linear Systems
 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 increases, it can become necessary to consider exploiting multiprocessors to solve these systems. We report o ..."
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Cited by 12 (2 self)
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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 increases, it can become necessary to consider exploiting multiprocessors to solve these systems. We report
Solving Large Sparse Linear Systems Over Finite Fields
, 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 ..."
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Cited by 89 (3 self)
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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
Multipolebased preconditioners for large sparse linear systems
, 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 lowrank 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 lowrank approximations and hierarchical multipole approximations, the cost
Amesos2 and Belos: Direct and iterative solvers for large sparse linear systems
 Scientific Programming
, 2012
"... Solvers for large sparse linear systems come in two categories: direct 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 ..."
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Cited by 7 (6 self)
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Solvers for large sparse linear systems come in two categories: direct 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
GREMLINS: a large sparse linear solver for grid environment
"... Traditional large sparse linear solvers are not suited in a grid computing environment as they require a large amount of synchronization and communication penalizing the performance on this architecture. This paper presents some features of the solver designed during the current GREMLINS (GRid Effic ..."
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Cited by 1 (1 self)
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Traditional large sparse linear solvers are not suited in a grid computing environment as they require a large amount of synchronization and communication penalizing the performance on this architecture. This paper presents some features of the solver designed during the current GREMLINS (GRid
Parallel multilevel block ILU preconditioning techniques for large sparse linear systems
 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 ..."
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Cited by 1 (0 self)
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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 QSDecomposition for Large Sparse Linear System of Equations
"... 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 onedimensional 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 onedimensional situations and O(n 3/2 ) in second dimensional
The Efficient Parallel Iterative Solution Of Large Sparse Linear Systems
, 1992
"... The development of efficient, generalpurpose 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 ..."
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Cited by 9 (0 self)
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The development of efficient, generalpurpose 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
 J. Symbolic Comput
, 1998
"... this paper appeared in "Design and Implementation of Symbolic Computation Systems," A. Miola (ed.), Springer Lect. Notes Comput. Science, 722, 6680 (1993). ..."
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Cited by 8 (3 self)
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this paper appeared in "Design and Implementation of Symbolic Computation Systems," A. Miola (ed.), Springer Lect. Notes Comput. Science, 722, 6680 (1993).
Results 1  10
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43,411