Abstract
We are developing a high-performance GIS (our term for a parallel GIS) on an SGI Challenge, a 16-processor machine with a shared address space architecture (SASA). We describe how we parallelized a key GIS operation using a message-passing algorithm. We advocate the linking of two diverse approaches to the design of parallel architectures and algorithms. As part of our project, we evaluated the effect of parallelizing an important GIS operation: range query. We parallelized a range query using data partitioning (to reduce synchronization) and dynamic load balancing (to improve speedup). We found that these approaches do achieve the performance required for many GIS applications.
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