Multi-granularities approximate method for obtaining qualitative spatial relations
Qualitative spatial relations are widely used in spatial description logics, spatial ontologies and other applications. Efficient method to obtain qualitative spatial relations from traditional GIS has not been discussed in previous literatures. We give an efficient method for calculating qualitative spatial relations. We propose the multi-granularities approximate representation of GIS objects which requires less process time. Then some algorithms are proposed to calculate the spatial relations based on multi-granularities approximate region. The analysis and test result all show that our method supports complex and integrated spatial relations and require less process time than traditional spatial query.
An instruction-level simulator for IBM 3090 with VF (vector facility) has been developed for studying the performance of vector processors and their memory hierarchies. Results of a study of the locality of several large scientific applications are presented. The cache miss ratios of vectorized applications are found to be almost equal to those of their original scalar executions. Moreover, both the spatial and temporal locality of these applications (in scalar and vector executions) are strong enough to show a sufficiently high hit ratio on conventional cache structures.<<ETX>>