Forschungsinfrastruktur

University of Salzburg

Salzburg | Website

Short Description

The research infrastructure consists of a network of 15 high-end server systems from Supermicro with multi core CPUs based on the AMD64 architecture. It can be used for calculations and test setups in the fields of software development and algorithm research. The nodes are connected with 10Gbit/s ethernet and 2x 56Gbit/s (per computing node) Infiniband FDR and can be used for dedicated low level programming and development of RDMA capable software.

Additionally applications and operating systems can be run in an isolated and abstracted way using virtualisation and container technologies. The research infrastructure allows to satisfy diverse research needs. Memory- and CPU-intensive research projects as well as distributed computing projects utilizing multiple nodes at the same time can be run on the available infrastructure. Available configurations range from systems with 96GB up to 1TB RAM and 12 to 64 cores per node. Fast storage systems using RAID with double parity and backup systems in different locations allow safe storage of research data.

A Continuous Integration (CI) system for rapid development and distribution of research software to all nodes is available.

Contact Person

Prof. DI Dr. Nikolaus Augsten

Research Services

Systems and algorithms for processing data
Storing and querying large data
Approximate query processing
Spatio-temporal database systems
GIS enabled databases
Interconnected nodes with 2x56Gbit/s Infiniband (per computing node) and 10Gbit/s ethernet technology
Direct Infiniband hardware access for RDMA-enabled software and services
Abstraction and Isolation of running systems using virtualisation and container technologies

Methods & Expertise for Research Infrastructure

The database research group develops algorithms for data-intensive applications in database and information systems with a particular focus on similarity search queries over large data collections, for example, similarity matching of sets, strings, and trees, efficient indexes for distance computations, and top-k queries.

Other fields of research include the distribution of large scale database queries using fast networks and remote direct memory access, load balancing algorithms for distributed frameworks like MapReduce, and queries in geographic information systems.
The research results are new algorithms with performance guarantees, which are implemented and empirically evaluated on both benchmark datasets and on the motivating application. Key performance parameters are runtime, memory efficiency, and network traffic; the performance measurements require direct and exclusive access to the hardware of the machines.