SPADE: GPU-Powered Spatial Database Engine for Commodity Hardware

Harish Doraiswamy, Juliana Freire

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Given the massive growth in the volume of spatial data, there is a great need for systems that can efficiently evaluate spatial queries over large data sets. These queries are notoriously expensive using traditional database solutions. While faster response times can be attained through powerful clusters or servers with large main-memory, these options, due to cost and complexity, are out of reach to many data scientists and analysts making up the long tail. Graphics Processing Units (GPUs), which are now widely available even in commodity desktops and laptops, provide a cost-effective alternative to support high-performance computing, opening up new opportunities to the efficient evaluation of spatial queries. While GPU-based approaches proposed in the literature have shown great improvements in performance, they are tied to specific GPU hardware and only handle specific queries over fixed geometry types. In this paper we present SPADE, a GPU-powered spatial database engine that supports a rich set of spatial queries. We discuss the challenges involved in attaining efficient query evaluation over large datasets as well as portability across different GPU hardware, and how these are addressed in SPADE. We performed a detailed experimental evaluation to assess the effectiveness of the system for wide range of queries and datasets, and report results which show that SPADE is scalable and able to handle data larger than main-memory, and its performance on a laptop is on par with that other systems that require clusters or large-memory servers.

Original languageEnglish (US)
Title of host publicationProceedings - 2022 IEEE 38th International Conference on Data Engineering, ICDE 2022
PublisherIEEE Computer Society
Number of pages13
ISBN (Electronic)9781665408837
StatePublished - 2022
Event38th IEEE International Conference on Data Engineering, ICDE 2022 - Virtual, Online, Malaysia
Duration: May 9 2022May 12 2022

Publication series

NameProceedings - International Conference on Data Engineering
ISSN (Print)1084-4627


Conference38th IEEE International Conference on Data Engineering, ICDE 2022
CityVirtual, Online


  • Geospatial queries
  • GPU computing

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Information Systems


Dive into the research topics of 'SPADE: GPU-Powered Spatial Database Engine for Commodity Hardware'. Together they form a unique fingerprint.

Cite this