Association for Computing Machinery
ICPP 2018 Proceedings of the 47th International Conference on Parallel Processing
In recent times, geospatial datasets are growing in terms of size, complexity and heterogeneity. High performance systems are needed to analyze such data to produce actionable insights in an efficient manner. For polygonal a.k.a vector datasets, operations such as I/O, data partitioning, communication, and load balancing becomes challenging in a cluster environment. In this work, we present MPI-Vector-IO 1 , a parallel I/O library that we have designed using MPI-IO specifically for partitioning and reading irregular vector data formats such as Well Known Text. It makes MPI aware of spatial data, spatial primitives and provides support for spatial data types embedded within collective computation and communication using MPI message-passing library. These abstractions along with parallel I/O support are useful for parallel Geographic Information System (GIS) application development on HPC platforms.
Puri, Satish; Paudel, Anmol; and Prasad, Sushil K., "MPI-Vector-IO: Parallel I/O and Partitioning for Geospatial Vector Data" (2018). Computer Science Faculty Research and Publications. 12.
ADA Accessible Version
Accepted version. ICPP 2018 Proceedings of the 47th International Conference on Parallel Processing, No. 13 (2018). DOI. © 2018 Association for Computing Machinery. Used with permission.