ParaStream: A parallel streaming Delaunay triangulation algorithm for LiDAR points on multicore architectures

This paper presents a robust parallel Delaunay triangulation algorithm called ParaStream for processing billions of points from nonoverlapped block LiDAR files. The algorithm targets ubiquitous multicore architectures. ParaStream integrates streaming computation with a traditional divide-and-conquer scheme, in which additional erase steps are implemented to reduce the runtime memory footprint. Furthermore, a kd-tree-based dynamic schedule strategy is also proposed to distribute triangulation and merging work onto the processor cores for improved load balance. ParaStream exploits most of the computing power of multicore platforms through parallel computing, demonstrating qualities of high data throughput as well as a low memory footprint. Experiments on a 2-Way-Quad-Core Intel Xeon platform show that ParaStream can triangulate approximately one billion LiDAR points (16.4 GB) in about 16 min with only 600 MB physical memory. The total speedup (including I/O time) is about 6.62 with 8 concurrent threads.