Mercurial > octave-nkf
view liboctave/UMFPACK/AMD/Demo/amd_demo.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 |
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AMD demo, with the 24-by-24 Harwell/Boeing matrix, can_24: 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: 24-by-24, with 160 entries. Note that for a symmetric matrix such as this one, only the strictly lower or upper triangular parts would need to be passed to AMD, since AMD computes the ordering of A+A'. The diagonal entries are also not needed, since AMD ignores them. Column: 0, number of entries: 9, with row indices in Ai [0 ... 8]: row indices: 0 5 6 12 13 17 18 19 21 Column: 1, number of entries: 6, with row indices in Ai [9 ... 14]: row indices: 1 8 9 13 14 17 Column: 2, number of entries: 6, with row indices in Ai [15 ... 20]: row indices: 2 6 11 20 21 22 Column: 3, number of entries: 6, with row indices in Ai [21 ... 26]: row indices: 3 7 10 15 18 19 Column: 4, number of entries: 6, with row indices in Ai [27 ... 32]: row indices: 4 7 9 14 15 16 Column: 5, number of entries: 6, with row indices in Ai [33 ... 38]: row indices: 0 5 6 12 13 17 Column: 6, number of entries: 9, with row indices in Ai [39 ... 47]: row indices: 0 2 5 6 11 12 19 21 23 Column: 7, number of entries: 9, with row indices in Ai [48 ... 56]: row indices: 3 4 7 9 14 15 16 17 18 Column: 8, number of entries: 4, with row indices in Ai [57 ... 60]: row indices: 1 8 9 14 Column: 9, number of entries: 9, with row indices in Ai [61 ... 69]: row indices: 1 4 7 8 9 13 14 17 18 Column: 10, number of entries: 6, with row indices in Ai [70 ... 75]: row indices: 3 10 18 19 20 21 Column: 11, number of entries: 6, with row indices in Ai [76 ... 81]: row indices: 2 6 11 12 21 23 Column: 12, number of entries: 6, with row indices in Ai [82 ... 87]: row indices: 0 5 6 11 12 23 Column: 13, number of entries: 6, with row indices in Ai [88 ... 93]: row indices: 0 1 5 9 13 17 Column: 14, number of entries: 6, with row indices in Ai [94 ... 99]: row indices: 1 4 7 8 9 14 Column: 15, number of entries: 6, with row indices in Ai [100 ... 105]: row indices: 3 4 7 15 16 18 Column: 16, number of entries: 4, with row indices in Ai [106 ... 109]: row indices: 4 7 15 16 Column: 17, number of entries: 9, with row indices in Ai [110 ... 118]: row indices: 0 1 5 7 9 13 17 18 19 Column: 18, number of entries: 9, with row indices in Ai [119 ... 127]: row indices: 0 3 7 9 10 15 17 18 19 Column: 19, number of entries: 9, with row indices in Ai [128 ... 136]: row indices: 0 3 6 10 17 18 19 20 21 Column: 20, number of entries: 6, with row indices in Ai [137 ... 142]: row indices: 2 10 19 20 21 22 Column: 21, number of entries: 9, with row indices in Ai [143 ... 151]: row indices: 0 2 6 10 11 19 20 21 22 Column: 22, number of entries: 4, with row indices in Ai [152 ... 155]: row indices: 2 20 21 22 Column: 23, number of entries: 4, with row indices in Ai [156 ... 159]: row indices: 6 11 12 23 Plot of input matrix pattern: 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 0: X . . . . X X . . . . . X X . . . X X X . X . . 1: . X . . . . . . X X . . . X X . . X . . . . . . 2: . . X . . . X . . . . X . . . . . . . . X X X . 3: . . . X . . . X . . X . . . . X . . X X . . . . 4: . . . . X . . X . X . . . . X X X . . . . . . . 5: X . . . . X X . . . . . X X . . . X . . . . . . 6: X . X . . X X . . . . X X . . . . . . X . X . X 7: . . . X X . . X . X . . . . X X X X X . . . . . 8: . X . . . . . . X X . . . . X . . . . . . . . . 9: . X . . X . . X X X . . . X X . . X X . . . . . 10: . . . X . . . . . . X . . . . . . . X X X X . . 11: . . X . . . X . . . . X X . . . . . . . . X . X 12: X . . . . X X . . . . X X . . . . . . . . . . X 13: X X . . . X . . . X . . . X . . . X . . . . . . 14: . X . . X . . X X X . . . . X . . . . . . . . . 15: . . . X X . . X . . . . . . . X X . X . . . . . 16: . . . . X . . X . . . . . . . X X . . . . . . . 17: X X . . . X . X . X . . . X . . . X X X . . . . 18: X . . X . . . X . X X . . . . X . X X X . . . . 19: X . . X . . X . . . X . . . . . . X X X X X . . 20: . . X . . . . . . . X . . . . . . . . X X X X . 21: X . X . . . X . . . X X . . . . . . . X X X X . 22: . . X . . . . . . . . . . . . . . . . . X X X . 23: . . . . . . X . . . . X X . . . . . . . . . . X return value from amd_order: 0 (should be 0) 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: 22 20 10 23 12 5 16 8 14 4 15 7 1 9 13 17 0 2 3 6 11 18 21 19 Inverse permutation vector: 16 12 17 18 9 5 19 11 7 13 2 20 4 14 8 10 6 15 21 23 1 22 0 3 Plot of permuted matrix pattern: 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 0: X X . . . . . . . . . . . . . . . X . . . . X . 1: X X X . . . . . . . . . . . . . . X . . . . X X 2: . X X . . . . . . . . . . . . . . . X . . X X X 3: . . . X X . . . . . . . . . . . . . . X X . . . 4: . . . X X X . . . . . . . . . . X . . X X . . . 5: . . . . X X . . . . . . . . X X X . . X . . . . 6: . . . . . . X . . X X X . . . . . . . . . . . . 7: . . . . . . . X X . . . X X . . . . . . . . . . 8: . . . . . . . X X X . X X X . . . . . . . . . . 9: . . . . . . X . X X X X . X . . . . . . . . . . 10: . . . . . . X . . X X X . . . . . . X . . X . . 11: . . . . . . X . X X X X . X . X . . X . . X . . 12: . . . . . . . X X . . . X X X X . . . . . . . . 13: . . . . . . . X X X . X X X X X . . . . . X . . 14: . . . . . X . . . . . . X X X X X . . . . . . . 15: . . . . . X . . . . . X X X X X X . . . . X . X 16: . . . . X X . . . . . . . . X X X . . X . X X X 17: X X . . . . . . . . . . . . . . . X . X X . X . 18: . . X . . . . . . . X X . . . . . . X . . X . X 19: . . . X X X . . . . . . . . . . X X . X X . X X 20: . . . X X . . . . . . . . . . . . X . X X . X . 21: . . X . . . . . . . X X . X . X X . X . . X . X 22: X X X . . . . . . . . . . . . . X X . X X . X X 23: . X X . . . . . . . . . . . . X X . X X . X X X