AbstractWe compare two methods for solving banded linear systems on a hypercube multiprocessor. Both methods are based on Gaussian elimination. The differences in the methods are due to different allocation schemes to distribute the data among the nodes. We implemented both methods on the Intel iPSC/2 hypercube. Timing results and efficiency results obtained on this multiprocessor are discussed
We describe the solution of linear systems of equations, Ax = b, on distributed-memory concurrent co...
We describe the solution of linear systems of equations, Ax = b, on distributed-memory concurrent co...
AbstractThis paper gives a classification for the triangular factorization of square matrices. These...
AbstractWe compare two methods for solving banded linear systems on a hypercube multiprocessor. Both...
AbstractWe propose several implementations of Gaussian elimination for solving banded linear systems...
AbstractWe propose several implementations of Gaussian elimination for solving banded linear systems...
[[abstract]]In this paper we use hypercube computers for solving linear systems. First, the pivoting...
Parallel Gaussian elimination technique for the solution of a system of equations Ax C where A is a ...
Parallel Gaussian elimination technique for the solution of a system of equations Ax C where A is a ...
this paper, we give a block algorithm for the Gauss-Huard elimination. For distributed memory system...
AbstractGaussian elimination is used in many applications and in particular in the solution of syste...
As computing machines advance, new fields are explored and old ones are expanded. This thesis consid...
We investigate parallel Gauss elimination for sparse matrices, especially those arising from the dis...
AbstractThis paper uses a graph-theoretic approach to derive asymptotically optimal algorithms for p...
AbstractThis paper proposes a few lower bounds for communication complexity of the Gaussian eliminat...
We describe the solution of linear systems of equations, Ax = b, on distributed-memory concurrent co...
We describe the solution of linear systems of equations, Ax = b, on distributed-memory concurrent co...
AbstractThis paper gives a classification for the triangular factorization of square matrices. These...
AbstractWe compare two methods for solving banded linear systems on a hypercube multiprocessor. Both...
AbstractWe propose several implementations of Gaussian elimination for solving banded linear systems...
AbstractWe propose several implementations of Gaussian elimination for solving banded linear systems...
[[abstract]]In this paper we use hypercube computers for solving linear systems. First, the pivoting...
Parallel Gaussian elimination technique for the solution of a system of equations Ax C where A is a ...
Parallel Gaussian elimination technique for the solution of a system of equations Ax C where A is a ...
this paper, we give a block algorithm for the Gauss-Huard elimination. For distributed memory system...
AbstractGaussian elimination is used in many applications and in particular in the solution of syste...
As computing machines advance, new fields are explored and old ones are expanded. This thesis consid...
We investigate parallel Gauss elimination for sparse matrices, especially those arising from the dis...
AbstractThis paper uses a graph-theoretic approach to derive asymptotically optimal algorithms for p...
AbstractThis paper proposes a few lower bounds for communication complexity of the Gaussian eliminat...
We describe the solution of linear systems of equations, Ax = b, on distributed-memory concurrent co...
We describe the solution of linear systems of equations, Ax = b, on distributed-memory concurrent co...
AbstractThis paper gives a classification for the triangular factorization of square matrices. These...