High-performance computing in GIS: techniques and applications

In this paper, the application of High-Performance Computing (HPC) techniques in processing of geospatial data in Geographic Information System (GIS) is presented. We evaluate two parallel/distributed architectures and programming models: Message Passing Interface (MPI) over Network of Workstations (NoW) and Compute Unified Device Architecture (CUDA) on Graphics Processing Unit (GPU) in well-known problems in GIS: map matching and slope computations. A distributed application for map-matching computation over large-spatial data sets consisting of moving points and a road network was implemented using MPI and experimentally evaluated. A slope computations based on large-digital elevation model data was performed on GPU using CUDA which enable hundreds of threads to run concurrently employing multiprocessors on a graphics card. Experimental evaluations indicate improvement in performance and shows feasibility of using NoW and multiprocessors on a graphic card for HPC in GIS.