GODIVA: Lightweight data management for scientific visualization applications

Xiaosong Ma*, Marianne Winslett, John Norris, Xiangmin Jiao, Robert Fiedler

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

11 Citations (Scopus)

Abstract

Scientific visualization applications are very data-intensive, with high demands for I/O and data management. Developers of many visualization tools hesitate to use traditional DBMSs, due to the lack of support for these DBMSs on parallel platforms and the risk of reducing the portability of their tools and the user data. In this paper, we propose the GODIVA framework, which provides simple database-like interfaces to help visualization tool developers manage their in-memory data, and I/O optimizations such as prefetching and caching to improve input performance at run time. We implemented the GODIVA interfaces in a stand-alone, portable user library, which can be used by all types of visualization codes: interactive and batch-mode, sequential and parallel. Performance results from running a visualization tool using the GODIVA library on multiple platforms show that the GODIVA framework is easy to use, alleviates developers' data management burden, and can bring substantial I/O performance improvement.

Original languageEnglish
Pages732-743
Number of pages12
Publication statusPublished - 2004
Externally publishedYes
EventProceedings - 20th International Conference on Data Engineering - ICDE 2004 - Boston, MA., United States
Duration: 30 Mar 20042 Apr 2004

Conference

ConferenceProceedings - 20th International Conference on Data Engineering - ICDE 2004
Country/TerritoryUnited States
CityBoston, MA.
Period30/03/042/04/04

Fingerprint

Dive into the research topics of 'GODIVA: Lightweight data management for scientific visualization applications'. Together they form a unique fingerprint.

Cite this