pRPL 2.0: Improving the Parallel Raster Processing Library

This article presents an improvedparallelRasterProcessingLibrary –pRPLversion 2.0. Since the release of version 1.0, a series of modifications has been made inpRPLto improve its usability, flexibility, and performance. While retaining some of the key features ofpRPL, the new version has gained several new features: (1) a newDataManagerclass has been added for integrated data management, and to facilitate data decomposition, assignment mapping, data distribution,Transitionexecution, and load‐balancing; (2) aGDAL‐based raster dataI/Omechanism has been added to support various geospatial raster data formats, and provide centralized and pseudo parallelI/Omodes; and (3) a static load‐balancing mode and a dynamic load‐balancing mode using the task‐farming technique are provided. A parallel zonal statistics tool and a parallel Cellular Automata model were developed to demonstrate the usability and performance ofpRPL2.0. The experiments using the California datasets showed that the performance altered when differentpRPLoptions (i.e. load‐balancing mode,I/Omode and writer mode) were used for different algorithms, datasets, and varying numbers of processes.