Abstract
A high performance geographic information system (GIS) is a central component of many real-time applications of spatial decision making. The GIS may contain gigabytes of geometric and feature data (e.g. location, elevation, soil type etc.) stored on a hierarchy of memory devices and represented as grids and large sets of polygons. The data is often accessed via range queries (like polygon clipping) and map-overlay queries. For example, a real-time visualization program retrieves the visible subset of GIS data around the current location of simulator via range queries fetching a million points/second. Such performance can be obtained only with major advances in exploiting parallelism and spatial database techniques within the computational geometry algorithms for range and map-overlay queries.
In this paper, we develop and experimentally evaluate data partitioning and load-balancing techniques for range queries in High Performance GIS. We implement static and dynamic load-balancing methods on a distributed memory parallel machine (Cray T3D) for polygon data, and we experimentally evaluate their performance. Preliminary results show that both the static and dynamic load-balancing methods are necessary for improved performance but are not sufficient by themselves. We propose a new quasi-dynamic load-balancing (QDLB) technique which achieves better load-balance and speedups than traditional methods. On 16 processors, we are able to process range queries in under 0.12 seconds for a map with 329,296 edges, where the range query size is 20–25% of the total area of the map. We are also able to achieve average speedups of 14 on 16 processors.
This work was supported by Army High Performance Computing Research Center under contract the auspices of the Department of Army, Army Research Laboratory cooperative agreement number DAAH04-95-2-0003/contract number DA/DAAH04-95-C-0008.
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Shekhar, S., Ravada, S., Kumar, V., Chubb, D., Turner, G. (1995). Load-balancing in high performance GIS: Declustering polygonal maps. In: Egenhofer, M.J., Herring, J.R. (eds) Advances in Spatial Databases. SSD 1995. Lecture Notes in Computer Science, vol 951. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60159-7_13
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