The group’s activities will focus on:
- design and development of efficient techniques and algorithms on parallel computing architectures, on topics including: execution of cellular automata, analysis and processing of heterogeneous and large data, scientific simulation.
- design and development of models for statistical estimation of parallel systems performance;
- design and development of multilevel analytical models for performance evaluation of high-performance algorithms;
- design, implementation and management of systems for the development of HPEC (High Performance Edge Computing) applications.
The group is devoted to the analysis, design and development of methods, algorithms and software on high-performance computers in the field of scientific computing.
The implementation of algorithms on specific high-performance architectures is strongly influenced by factors such as data transfer and computational load balancing, thus requiring the design of specific solutions as well as the evaluation of algorithmic and technological parameters. In fact, load balancing requires that all computational resources are committed, while the minimization of data-transfer/computation ratio maximizes parallel efficiency. Among other things, an efficient implementation addressing these aspects allows the minimization of the time-to-solution.
Scientific and Environmental Simulation, Biology, Medicine, Cultural Heritage, Aerospace