P42 - Database Optimization Techniques for Scientific Applications
Presenter
DescriptionDatabases have proven to be a very important component in both commercial and scientific areas. Traditional techniques to optimize database systems have only been helpful in managing structured or semi-structured data. However, many scientific applications like climate observation or biochemical simulations are data-intensive and produce large volumes of complex data. Therefore, this work focuses on the improvement of organizing and searching techniques to obtain maximum scientific-computing performance by tuning the queries and the execution processes with respect to three attributes:
1. Using frameworks like MPI to exploit massive parallelism within large databases to provide scalable, fast query performance
2. Using array databases for maximum scientific-computing performance - Comparison of different Array Alegra techniques (NRCA, SciQL, AFL, ODMG) have been made.
3. A directed graph representation of hierarchial relationships so that queries against the table that require the path information may be answered quickly and efficiently.
1. Using frameworks like MPI to exploit massive parallelism within large databases to provide scalable, fast query performance
2. Using array databases for maximum scientific-computing performance - Comparison of different Array Alegra techniques (NRCA, SciQL, AFL, ODMG) have been made.
3. A directed graph representation of hierarchial relationships so that queries against the table that require the path information may be answered quickly and efficiently.
TimeTuesday, 6 July 202117:30 - 19:00 CEST
Location
SessionPoster Session
Event Type
Poster