Abstract
This demo presents Scout; a full-fledged interactive data visualization system with native support for spatio-temporal data. Scout utilizes computing power of GPUs to achieve real-time query performance. The key idea behind Scout is a GPU-aware multi-version spatio-temporal index. The indexing and query processing modules of Scout are designed to complement the GPU hardware characteristics. Front end of Scout provides a user interface to submit queries and view results. Scout supports a variety of spatio-temporal queriesrange, k-NN, and join. We use real data sets to demonstrate scalability and important features of Scout.
| Original language | English (US) |
|---|---|
| Title of host publication | SIGMOD 2017 - Proceedings of the 2017 ACM International Conference on Management of Data |
| Publisher | Association for Computing Machinery |
| Pages | 1691-1694 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781450341974 |
| DOIs | |
| State | Published - May 9 2017 |
| Event | 2017 ACM SIGMOD International Conference on Management of Data, SIGMOD 2017 - Chicago, United States Duration: May 14 2017 → May 19 2017 |
Publication series
| Name | Proceedings of the ACM SIGMOD International Conference on Management of Data |
|---|---|
| Volume | Part F127746 |
| ISSN (Print) | 0730-8078 |
Other
| Other | 2017 ACM SIGMOD International Conference on Management of Data, SIGMOD 2017 |
|---|---|
| Country/Territory | United States |
| City | Chicago |
| Period | 5/14/17 → 5/19/17 |
Bibliographical note
Publisher Copyright:© 2017 ACM.