About Us

Scientific Applications

About Us

The focus of the Research Group Scientific Computing, which is headed by Prof. Siegfried Benkner, is within the challenging area of software for high-end computing systems covering a broad range of architectures from multi-core servers, to clusters and supercomputers, all the way to heterogeneous distributed systems, Grids, and Clouds.

The research agenda comprises programming paradigms, compilers, runtime systems, and software development environments in order to support users in the process of solving increasingly complex compute- and data-intensive problems in science and engineering.

High-end computing technologies have become strategic tools providing the computational capabilities required for simulating and optimizing complex processes as they occur in industry, economy, and science. The tremendous performance offered by parallel computing systems is also key to advanced new applications based on Big Data analytics and machine learning. This can be mainly attributed to exponential performance improvements of processors, storage technologies and interconnection networks.

Modern processor technologies accommodate several dozens of processor cores on a single chip and state-of-the-art supercomputers comprise hundreds of thousands of processors. Grids and Clouds integrate these systems on a global scale.
While all these systems are being built from commodity-of-the-shelf components, the major challenges are now with the software for such systems. Only programs and applications specifically designed and optimized for parallelism are capable of exploiting the performance potential of parallel and distributed hardware. However, most existing software systems and applications have been developed for sequential (single processor) systems.

The development of effective methods and software technologies for parallel systems thus represents one of the key challenges of computer science and information technology.

The Research Group Scientific Computing operates a state-of- the-art computer infrastructure and cooperates with major universities, research centers and enterprises worldwide.

Research Areas

  • Parallel Computing

    • Programming paradigms and languages
    • Compilers, transformation systems, runtime system
    • Parallelization, optimization and auto-tuning

  • Cloud and Grid Computing

    • Application development and service provisioning environments
    • Distributed programming models
    • Data-intensive science, large-scale data mining and data integration

  • Application-oriented inter-disciplinary research

    • Medicine, Biology, Life Sciences
    • Finance, Economics
    • Physics, Chemistry, Engineering