Abstract
When a large sparse matrix is calculated for a horizontal geodetic network adjustment, it needs to go through the process of matrix reordering for the efficiency of time and space. In this study, several reordering methods for sparse matrix were tested, using Sparse Matrix Manipulation System (SMMS) program, total processing time and Fill-in number produced in factorization process were measured and compared. As a result, Minimum Degree (MD) and Mutiple Minimum Degree (MMD), which are based on Minimum Degree are better than Gibbs-Poole-Stockmeyer (GPS) and Reverse Cuthill-Mckee (RCM), which are based on Minimum Bandwidth. However, the method of the best efficiency can be changed dependent on distribution of non-zero elements in a matrix. This finding could be applied to heighten the efficiency of time and storage space for national datum readjustment and other large geodetic network adjustment.
| Original language | English |
|---|---|
| Pages (from-to) | 85-91 |
| Number of pages | 7 |
| Journal | Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography |
| Volume | 26 |
| Issue number | 1 |
| Publication status | Published - 2008 Feb 29 |
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All Science Journal Classification (ASJC) codes
- Earth and Planetary Sciences(all)
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A comparative study on the efficient reordering methods of sparse matrix problem for large-Scale surveying network adjustment. / Woo, Sun Kyu; Heo, Joon; Yun, Kong Hyun.
In: Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 26, No. 1, 29.02.2008, p. 85-91.Research output: Contribution to journal › Article
TY - JOUR
T1 - A comparative study on the efficient reordering methods of sparse matrix problem for large-Scale surveying network adjustment
AU - Woo, Sun Kyu
AU - Heo, Joon
AU - Yun, Kong Hyun
PY - 2008/2/29
Y1 - 2008/2/29
N2 - When a large sparse matrix is calculated for a horizontal geodetic network adjustment, it needs to go through the process of matrix reordering for the efficiency of time and space. In this study, several reordering methods for sparse matrix were tested, using Sparse Matrix Manipulation System (SMMS) program, total processing time and Fill-in number produced in factorization process were measured and compared. As a result, Minimum Degree (MD) and Mutiple Minimum Degree (MMD), which are based on Minimum Degree are better than Gibbs-Poole-Stockmeyer (GPS) and Reverse Cuthill-Mckee (RCM), which are based on Minimum Bandwidth. However, the method of the best efficiency can be changed dependent on distribution of non-zero elements in a matrix. This finding could be applied to heighten the efficiency of time and storage space for national datum readjustment and other large geodetic network adjustment.
AB - When a large sparse matrix is calculated for a horizontal geodetic network adjustment, it needs to go through the process of matrix reordering for the efficiency of time and space. In this study, several reordering methods for sparse matrix were tested, using Sparse Matrix Manipulation System (SMMS) program, total processing time and Fill-in number produced in factorization process were measured and compared. As a result, Minimum Degree (MD) and Mutiple Minimum Degree (MMD), which are based on Minimum Degree are better than Gibbs-Poole-Stockmeyer (GPS) and Reverse Cuthill-Mckee (RCM), which are based on Minimum Bandwidth. However, the method of the best efficiency can be changed dependent on distribution of non-zero elements in a matrix. This finding could be applied to heighten the efficiency of time and storage space for national datum readjustment and other large geodetic network adjustment.
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M3 - Article
AN - SCOPUS:77953930466
VL - 26
SP - 85
EP - 91
JO - Journal of the Korean Society of Surveying Geodesy Photogrammetry and Cartography
JF - Journal of the Korean Society of Surveying Geodesy Photogrammetry and Cartography
SN - 1598-4850
IS - 1
ER -