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|
|Number of pages||4|
|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
|Name||Proceedings of the ACM SIGMOD International Conference on Management of Data|
|Other||2017 ACM SIGMOD International Conference on Management of Data, SIGMOD 2017|
|Period||5/14/17 → 5/19/17|
Bibliographical noteFunding Information:
This research is supported by NSF grants IIS-0952977, IIS-1218168, IIS-1525953, and CNS-1512877.
© 2017 ACM.