Gaussian elimination on hypercubes:
Several implementations of the Gaussian elimination algorithm are compared for solving dense linear systems on hypercube parallel processors. Two classes of methods: methods that require to move the elimination row (or column) to all processors before the elimination proceeds, and methods that requi...
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New Haven, Connecticut
1986
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| Schriftenreihe: | Yale University <New Haven, Conn.> / Department of Computer Science: Research report
462 |
| Schlagworte: | |
| Zusammenfassung: | Several implementations of the Gaussian elimination algorithm are compared for solving dense linear systems on hypercube parallel processors. Two classes of methods: methods that require to move the elimination row (or column) to all processors before the elimination proceeds, and methods that require only moving data to nearest neighbors. Algorithms of the second class, which are called pipelined algorithms, require only a ring or grid structure which is embedded into the hypercube. One of the main conclusions is that for Gaussian elimination the additional connectivity of the hypercube topology over that a two dimensional grid of processors does not help much in improving efficiency. Another result of the analysis is that there is little reason for using row or column typle algorithms instead of grid algorithms. One of the goals of the paper is also to show a simple model of complexity analysis at work, by comparing the estimated times that it provides with the actual execution times. |
| Beschreibung: | 15 S. |
Internformat
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| 490 | 1 | |a Yale University <New Haven, Conn.> / Department of Computer Science: Research report |v 462 | |
| 520 | 3 | |a Several implementations of the Gaussian elimination algorithm are compared for solving dense linear systems on hypercube parallel processors. Two classes of methods: methods that require to move the elimination row (or column) to all processors before the elimination proceeds, and methods that require only moving data to nearest neighbors. Algorithms of the second class, which are called pipelined algorithms, require only a ring or grid structure which is embedded into the hypercube. One of the main conclusions is that for Gaussian elimination the additional connectivity of the hypercube topology over that a two dimensional grid of processors does not help much in improving efficiency. Another result of the analysis is that there is little reason for using row or column typle algorithms instead of grid algorithms. One of the goals of the paper is also to show a simple model of complexity analysis at work, by comparing the estimated times that it provides with the actual execution times. | |
| 650 | 4 | |a Embedded computer system | |
| 650 | 4 | |a Hypercubes | |
| 650 | 7 | |a Algorithms |2 dtict | |
| 650 | 7 | |a Computer Hardware |2 scgdst | |
| 650 | 7 | |a Computer Programming and Software |2 scgdst | |
| 650 | 7 | |a Computer programming |2 dtict | |
| 650 | 7 | |a Elimination |2 dtict | |
| 650 | 7 | |a Gaussian noise |2 dtict | |
| 650 | 7 | |a Grids |2 dtict | |
| 650 | 7 | |a Mapping(transformations) |2 dtict | |
| 650 | 7 | |a Models |2 dtict | |
| 650 | 7 | |a Motion |2 dtict | |
| 650 | 7 | |a Parallel processors |2 dtict | |
| 650 | 7 | |a Structural properties |2 dtict | |
| 650 | 7 | |a Topology |2 dtict | |
| 650 | 7 | |a Two dimensional |2 dtict | |
| 810 | 2 | |a Department of Computer Science: Research report |t Yale University <New Haven, Conn.> |v 462 |w (DE-604)BV006663362 |9 462 | |
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| author | Saad, Yousef |
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| id | DE-604.BV035582658 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-09T21:40:57Z |
| institution | BVB |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-017638043 |
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| physical | 15 S. |
| publishDate | 1986 |
| publishDateSearch | 1986 |
| publishDateSort | 1986 |
| record_format | marc |
| series2 | Yale University <New Haven, Conn.> / Department of Computer Science: Research report |
| spelling | Saad, Yousef Verfasser (DE-588)1025729978 aut Gaussian elimination on hypercubes New Haven, Connecticut 1986 15 S. txt rdacontent n rdamedia nc rdacarrier Yale University <New Haven, Conn.> / Department of Computer Science: Research report 462 Several implementations of the Gaussian elimination algorithm are compared for solving dense linear systems on hypercube parallel processors. Two classes of methods: methods that require to move the elimination row (or column) to all processors before the elimination proceeds, and methods that require only moving data to nearest neighbors. Algorithms of the second class, which are called pipelined algorithms, require only a ring or grid structure which is embedded into the hypercube. One of the main conclusions is that for Gaussian elimination the additional connectivity of the hypercube topology over that a two dimensional grid of processors does not help much in improving efficiency. Another result of the analysis is that there is little reason for using row or column typle algorithms instead of grid algorithms. One of the goals of the paper is also to show a simple model of complexity analysis at work, by comparing the estimated times that it provides with the actual execution times. Embedded computer system Hypercubes Algorithms dtict Computer Hardware scgdst Computer Programming and Software scgdst Computer programming dtict Elimination dtict Gaussian noise dtict Grids dtict Mapping(transformations) dtict Models dtict Motion dtict Parallel processors dtict Structural properties dtict Topology dtict Two dimensional dtict Department of Computer Science: Research report Yale University <New Haven, Conn.> 462 (DE-604)BV006663362 462 |
| spellingShingle | Saad, Yousef Gaussian elimination on hypercubes Embedded computer system Hypercubes Algorithms dtict Computer Hardware scgdst Computer Programming and Software scgdst Computer programming dtict Elimination dtict Gaussian noise dtict Grids dtict Mapping(transformations) dtict Models dtict Motion dtict Parallel processors dtict Structural properties dtict Topology dtict Two dimensional dtict |
| title | Gaussian elimination on hypercubes |
| title_auth | Gaussian elimination on hypercubes |
| title_exact_search | Gaussian elimination on hypercubes |
| title_full | Gaussian elimination on hypercubes |
| title_fullStr | Gaussian elimination on hypercubes |
| title_full_unstemmed | Gaussian elimination on hypercubes |
| title_short | Gaussian elimination on hypercubes |
| title_sort | gaussian elimination on hypercubes |
| topic | Embedded computer system Hypercubes Algorithms dtict Computer Hardware scgdst Computer Programming and Software scgdst Computer programming dtict Elimination dtict Gaussian noise dtict Grids dtict Mapping(transformations) dtict Models dtict Motion dtict Parallel processors dtict Structural properties dtict Topology dtict Two dimensional dtict |
| topic_facet | Embedded computer system Hypercubes Algorithms Computer Hardware Computer Programming and Software Computer programming Elimination Gaussian noise Grids Mapping(transformations) Models Motion Parallel processors Structural properties Topology Two dimensional |
| volume_link | (DE-604)BV006663362 |
| work_keys_str_mv | AT saadyousef gaussianeliminationonhypercubes |