2D biharmonic operator w/Langrage constraints, for smoothing
Name Hardesty1
Group Hardesty
Matrix ID 2831
Num Rows 938,905
Num Cols 938,905
Nonzeros 12,143,314
Pattern Entries 12,143,314
Kind Computer Graphics/Vision Problem
Symmetric Yes
Date 2013
Author S. Hardesty
Editor T. Davis
Structural Rank 938,905
Structural Rank Full true
Num Dmperm Blocks 7,811
Strongly Connect Components 1
Num Explicit Zeros 0
Pattern Symmetry 100%
Numeric Symmetry 100%
Cholesky Candidate no
Positive Definite no
Type integer
Download MATLAB Rutherford Boeing Matrix Market
Surface fitting problem for visualization, Sean Hardesty              
Visualization of 3D structures in the earth                           
The Hardesty3 matrix is an interpolation matrix stacked above a       
weighted Laplacian, to to fit a surface z(x,y) to a set of points     
in R^3 subject to a smoothness constraint enforced via regularization.
Hardesty2 is a smaller version of this problem.                       
For the big matrix (Hardesty/Hardesty3), sparse QR (via SuiteSparseQR,
or SPQR) finds an R factor and a set of Householder vectors (Q.H) with
about 150 million nonzeros.  Sparse LU factorization (with UMFPACK    
v5.7.1) sees very high fillin (about 2.5 billion nonzeros in L+U).    
The Hardesty1 matrix is a simple discretization of a 2D biharmonic    
operator with some Lagrange multiplier constraints used for smoothing.