This talk introduces GPU version of PostGIS and GiST-Index that we have developed as a new feature of PG-Strom.

Nowadays, our devices (like mobile phones) generate geolocational data time-by-time, and it is often utilized for area-marketing, push-delivery, disaster notification, and so on. People often use GIS technology to pick up users based on their current location. Even if area definitions are complicated polygons, PostGIS functions can generate right intersections, however, it is often highly computing intensive workloads.

GPU is designed for massive parallel computing workloads, with more than thousands cores per chip. And, we have developed PG-Strom extension to run a part of SQL workloads on GPU devices. At the upcoming PG-Strom v3.0, it newly supports several PostGIS functions and GiST-index for the computing intensive geolocational workloads.

In this talk, we will introduce the technology background, usage, implementation and benchmark result of GPU version of PostGIS and GiST-Index.