The Centre for Scientific Computing & Complex Systems Modelling (SCI-SYM) is a centre of excellence for researchers working in high performance computing (HPC) applied to computational and mathematical models for complex systems in engineering, natural and applied sciences. It has been created in 2007.
Sci-Sym as University Designated Reseach Centre (UDRC).
Scientific Computing and Complex Systems explores models of the natural and artificial world, through high performance computer solutions of problems, which, due to their complexity, are intractable by conventional methods such as experimental, mathematical or semi-analytical methods alone. Complex systems arise in a variety of fields, e.g. physics, biology, chemistry, eco- and other hybrid sciences, finance, socio-economic phenomena, and others and are truly interdisciplinary. In some cases, a formal model may be proposed and investigated; in others large amounts of data may be mined and empirically analysed or computational models may be designed and tested against available data.
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Aims are to improve and enhance the theoretical and computational modelling expertise in DCU as a whole, in order to promote successful bids for funded research schemes, (both national and international), and to provide an R&D pool to client companies, hence positioning DCU for a future strategic research cluster or CSET bid. SciSym also develops an expanded High Performance Computing (HPC) research cluster facility, which will be comparable to those of intermediate international capability, and supports multidisciplinary research projects to national, ICHEC capability, level. The HPC cluster provides, additionally, a sufficiently sophisticated resource for Grid access. Consequently, the UDRC is particularly timely in the light of current national and international developments and the recent targeting (in FP7) of strategic research including grid technologies and pervasive computing, Bioinformatics and Microscopic Biosystems synergies and Complex Systems, amongst others. The in-house high-performance computing facility would be accessible across all Schools, research centres and disciplines for parallel and distributed computing research with high computational requirements, while grid access would not only facilitate research, involving integration of heterogeneous information sources and data mining, but also projects at the knowledge layer. Demand is dictated by key phases in Complex Systems modelling and analysis, which generally include the following:
- Development of the mathematical model or data sourcing
- Design/Implementation of algorithms
- Generation of solutions e.g. through numerical simulation of the phenomenon of interest, data mining, matching and/or analysis
- Representation of the computed results or analyses
- Interpretation of results and model validation
Key strategic areas for development, in which there are both current university-wide strengths and capacity to expand, include:
- Bioinformatics and Microscopic Biosystems
- Social, Economical and Environmental Systems
- Complexity and Computation in Physics
- Theoretical Approaches and Methodologies in Complexity