A parallel search algorithm for the SAT
In order to be able to perform multimedia searches (like sounds, videos, images, etc.) we have to use data structures like the Spatial Approximation Tree (SAT). This structure is a nice example of a tree structure in which well-known tricks for tree parallelization simply do not work. It is too spar...
Guardado en:
| Autores principales: | , , , |
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| Formato: | Articulo |
| Lenguaje: | Inglés |
| Publicado: |
2005
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| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/9608 http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Dec05-21.pdf |
| Aporte de: |
| Sumario: | In order to be able to perform multimedia searches (like sounds, videos, images, etc.) we have to use data structures like the Spatial Approximation Tree (SAT). This structure is a nice example of a tree structure in which well-known tricks for tree parallelization simply do not work. It is too sparse, unbalanced and its performance is too dependent on the work-load generated by the queries being solved by means of searching the tree. The complexity measure is given by the number of distances computed to retrieve those objects close enough to the query. In this paper we examine some alternatives to parallelize this structure through the MPI library and the BSPpub library. |
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