Parallel interpolation of elevation grids
Fall 2006 with Scott Blaha. Advisor: Andy Danner
Real life geographic elevation data comes in three-dimensional point clouds, meaning data is not aligned along a grid or even has uniform distribution. Geographic Information Systems take elevation grids for most processing tasks (viewshed computation, watershed computation, flow routing etc.). The natural way of getting grids from point clouds is interpolation. However, interpolation is extremely computationally intensive and GIS data sets are getting bigger by the second.
Thankfully interpolation is RP (ridiculously parallelizable), which can theoretically give us nx speed up in n-way parallelization. We implemented a few interpolation algorithms, parallelize them and observed the improvement in performance. Programmed in C using LAM/MPI.
Download: paper (PDF)
