Effective Sparse Matrix Ordering: Just Around the BEND
نویسندگان
چکیده
When performing sparse matrix factorization, the ordering of matrix rows and columns has a dramatic impact on the factorization time. This paper describes an approach to the reordering problem that produces signiicantly better orderings than previous methods. The algorithm is a hybrid of nested dissection and minimum degree ordering, and combines an assortment of algorithmic techniques.
منابع مشابه
The effect of the geometry of the scour around bridge abutments in the river bend
Every year a large number of bridges flooding in the river just when they most need them there destroy all born. Carried out. In this study, the four fulcrum forms a semi-circular, trapezoidal, rectangular edges rounded rectangle 90 degrees at 70 degrees in Sagittarius with four different discharges depth of constant scouring around the abutment in pure water were examined. For material of flum...
متن کاملExperimental Study of the Effect of Base-level fall at the Beginning of the Bend on Reduction of Scour around a Rectangular Bridge Pier Located in the 180 Degree Sharp Bend
Base-level fall in river beds occurs due to varying natural or unnatural causes. Base-level fall causes the change in the behavior of flow at the location of drop in base-level. In such situations, most of scour occur at the foot of the slope, and slope wall retreats in the upstream direction. This phenomenon widens the wall of the river bank, thus leading to its destruction. The amount of bed ...
متن کاملA Structural Diagnosis of Some IC Orderings
We present a novel analysis of the potential effectiveness of a matrix ordering for IC in terms of just the sparsity structure. By looking at the structure of the approximate inverse implicitly created by IC we can help to explain the success of Reverse Cuthill-McKee orderings, the problems IC(0) has under Red-Black orderings that disappear when extra fill is included, and where fill must be ad...
متن کاملEffective Preconditioning through Ordering Interleaved with Incomplete Factorization
Consider the solution of a sparse linear system Ax = b when the matrix A is symmetric and positive definite. A typical iterative solver is obtained by using the method of Conjugate Gradients (CG) [15] preconditioned with an incomplete Cholesky (IC) factor L̂ [4]. The latter is an approximation to the (complete) Cholesky factor L, where A = LL . Consequently, the process of computing L̂ relies to ...
متن کاملMultifrontal Techniques for Chemical Process Simulation on Supercomputers
A critical computational step in large-scale process simulation using rigorous equationbased models is the solution of a sparse linear equation system. Traditional sparse solvers based on indirect addressing are not effective on supercomputers because they do not vectorize well. By relying on vectorized dense matrix kernels, the multifrontal and frontal methods provide much better performance, ...
متن کامل