Mercurial > octave-nkf
view liboctave/UMFPACK/AMD/MATLAB/amd_demo.m.out @ 5164:57077d0ddc8e
[project @ 2005-02-25 19:55:24 by jwe]
author | jwe |
---|---|
date | Fri, 25 Feb 2005 19:55:28 +0000 |
parents | |
children |
line wrap: on
line source
>> amd_demo AMD Approximate minimum degree permutation. P = AMD (S) returns the approximate minimum degree permutation vector for the sparse matrix C = S+S'. The Cholesky factorization of C (P,P), or S (P,P), tends to be sparser than that of C or S. AMD tends to be faster than SYMMMD and SYMAMD, and tends to return better orderings than SYMMMD. S must be square. If S is full, amd (S) is equivalent to amd (sparse (S)). Usage: P = amd (S) ; % finds the ordering [P, Info] = amd (S, Control) ; % optional parameters & statistics Control = amd ; % returns default parameters amd ; % prints default parameters. Control (1); If S is n-by-n, then rows/columns with more than max (16, (Control (1))* sqrt(n)) entries in S+S' are considered "dense", and ignored during ordering. They are placed last in the output permutation. The default is 10.0 if Control is not present. Control (2): If nonzero, then aggressive absorption is performed. This is the default if Control is not present. Control (3): If nonzero, print statistics about the ordering. Info (1): status (0: ok, -1: out of memory, -2: matrix invalid) Info (2): n = size (A,1) Info (3): nnz (A) Info (4): the symmetry of the matrix S (0.0 means purely unsymmetric, 1.0 means purely symmetric). Computed as: B = tril (S, -1) + triu (S, 1) ; symmetry = nnz (B & B') / nnz (B); Info (5): nnz (diag (S)) Info (6): nnz in S+S', excluding the diagonal (= nnz (B+B')) Info (7): number "dense" rows/columns in S+S' Info (8): the amount of memory used by AMD, in bytes Info (9): the number of memory compactions performed by AMD The following statistics are slight upper bounds because of the approximate degree in AMD. The bounds are looser if "dense" rows/columns are ignored during ordering (Info (7) > 0). The statistics are for a subsequent factorization of the matrix C (P,P). The LU factorization statistics assume no pivoting. Info (10): the number of nonzeros in L, excluding the diagonal Info (11): the number of divide operations for LL', LDL', or LU Info (12): the number of multiply-subtract pairs for LL' or LDL' Info (13): the number of multiply-subtract pairs for LU Info (14): the max # of nonzeros in any column of L (incl. diagonal) Info (15:20): unused, reserved for future use An assembly tree post-ordering is performed, which is typically the same as an elimination tree post-ordering. It is not always identical because of the approximate degree update used, and because "dense" rows/columns do not take part in the post-order. It well-suited for a subsequent "chol", however. If you require a precise elimination tree post-ordering, then do: P = amd (S) ; C = spones (S) + spones (S') ; % skip this if S already symmetric [ignore, Q] = sparsfun ('symetree', C (P,P)) ; P = P (Q) ; -------------------------------------------------------------------------- AMD Version 1.1 (Jan. 21, 2004), Copyright (c) 2004 by Timothy A. Davis, Patrick R. Amestoy, and Iain S. Duff. See ../README for License. email: davis@cise.ufl.edu CISE Department, Univ. of Florida. web: http://www.cise.ufl.edu/research/sparse/amd -------------------------------------------------------------------------- Acknowledgements: This work was supported by the National Science Foundation, under grants ASC-9111263, DMS-9223088, and CCR-0203270. See also COLMMD, COLAMD, COLPERM, SYMAMD, SYMMMD, SYMRCM. Matrix name: HB/can_24 Matrix title: 1SYMMETRIC PATTERN FROM CANNES,LUCIEN MARRO,JUNE 1981. If the next step fails, then you have not yet compiled the AMD mexFunction. amd: approximate minimum degree ordering, parameters: dense row parameter: 10 (rows with more than max (10 * sqrt (n), 16) entries are considered "dense", and placed last in output permutation) aggressive absorption: yes input matrix A is 24-by-24 input matrix A has 160 nonzero entries amd: approximate minimum degree ordering, results: status: OK n, dimension of A: 24 nz, number of nonzeros in A: 160 symmetry of A: 1.0000 number of nonzeros on diagonal: 24 nonzeros in pattern of A+A' (excl. diagonal): 136 # dense rows/columns of A+A': 0 memory used, in bytes: 1516 # of memory compactions: 0 The following approximate statistics are for a subsequent factorization of A(P,P) + A(P,P)'. They are slight upper bounds if there are no dense rows/columns in A+A', and become looser if dense rows/columns exist. nonzeros in L (excluding diagonal): 97 nonzeros in L (including diagonal): 121 # divide operations for LDL' or LU: 97 # multiply-subtract operations for LDL': 275 # multiply-subtract operations for LU: 453 max nz. in any column of L (incl. diagonal): 8 chol flop count for real A, sqrt counted as 1 flop: 671 LDL' flop count for real A: 647 LDL' flop count for complex A: 3073 LU flop count for real A (with no pivoting): 1003 LU flop count for complex A (with no pivoting): 4497 Permutation vector: 23 21 11 24 13 6 17 9 15 5 16 8 2 10 14 18 1 3 4 7 12 19 22 20 Analyze A(p,p) with MATLAB's symbfact routine: predicted nonzeros: 120 predicted flops: 656 predicted height: 16 predicted front size: 7 number of nonzeros in L (including diagonal): 120 floating point operation count for chol (A (p,p)): 656 Results from AMD's approximate analysis: number of nonzeros in L (including diagonal): 121 floating point operation count for chol (A (p,p)): 671 Note that the nonzero and flop counts from AMD are slight upper bounds. This is due to the approximate minimum degree method used, in conjunction with "mass elimination". See the discussion about mass elimination in amd.h and amd_2.c for more details. >> diary off