In this paper, a new viable bandwidth reduction algorithm for reducing the bandwidth of sparse symmetric matrices, is described. The proposed algorithm provides a reliable procedure to reduce the bandwidth and can easily be applied to the sparse symmetric matrices of any size. This algorithm is tested on structured graphs and the reduced bandwidth results obtained are compared with the GPS algorithm. The bandwidth obtained by the present method is smaller than or equal to the one obtained by the GPS and standard examples are included to illustrate in detail the proposed algorithm
This work proposes the minimization of bandwidth in sparse symmetric Matrix, using genetic algorit...
Most research in algorithm design relies on worst-case analysis for performance comparisons. Unfortu...
On multicore architectures, the ratio of peak memory bandwidth to peak floating-point performance (b...
AbstractComputational and storage costs of resolution of large sparse linear systems Ax=b can be per...
The paper describes a new bandwidth reduction method for sparse matrices which promises to be both f...
The problem of sparse matrix bandwidth reduction is addressed and solved with two approaches suitabl...
Abstract. For a sparse symmetric matrix, there has been much attention given to algorithms for reduc...
A simple and efficient algorithm for the bandwidth reduction of sparse symmetric matrices is propose...
This paper studies heuristics for the bandwidth reduction of large-scale matrices in serial computat...
Since 1969 a standard approach to the reduction of matrix bandwidth and profile has been to grow roo...
We develop an algorithmic framework for reducing the bandwidth of symmetric matrices. This framework...
The bandwidth, average bandwidth, envelope, profile and antibandwidth of the matrices have been the ...
Large sparsely populated matrices of diagonal character are common in finite element calculations. C...
Abstract — In this article we first review previous exact approaches as well as theoretical contribu...
This program, REDUCE, reduces the bandwidth and profile of sparse symmetric matrices, using row and ...
This work proposes the minimization of bandwidth in sparse symmetric Matrix, using genetic algorit...
Most research in algorithm design relies on worst-case analysis for performance comparisons. Unfortu...
On multicore architectures, the ratio of peak memory bandwidth to peak floating-point performance (b...
AbstractComputational and storage costs of resolution of large sparse linear systems Ax=b can be per...
The paper describes a new bandwidth reduction method for sparse matrices which promises to be both f...
The problem of sparse matrix bandwidth reduction is addressed and solved with two approaches suitabl...
Abstract. For a sparse symmetric matrix, there has been much attention given to algorithms for reduc...
A simple and efficient algorithm for the bandwidth reduction of sparse symmetric matrices is propose...
This paper studies heuristics for the bandwidth reduction of large-scale matrices in serial computat...
Since 1969 a standard approach to the reduction of matrix bandwidth and profile has been to grow roo...
We develop an algorithmic framework for reducing the bandwidth of symmetric matrices. This framework...
The bandwidth, average bandwidth, envelope, profile and antibandwidth of the matrices have been the ...
Large sparsely populated matrices of diagonal character are common in finite element calculations. C...
Abstract — In this article we first review previous exact approaches as well as theoretical contribu...
This program, REDUCE, reduces the bandwidth and profile of sparse symmetric matrices, using row and ...
This work proposes the minimization of bandwidth in sparse symmetric Matrix, using genetic algorit...
Most research in algorithm design relies on worst-case analysis for performance comparisons. Unfortu...
On multicore architectures, the ratio of peak memory bandwidth to peak floating-point performance (b...