The chosen strategy for Uncertainty Quantification (UQ) is to exploit MC algorithms. The parallelism can be easily exploited when running in supercomputers, and the most important point is to properly handle different execution sizes. We have already developed a framework capable of dynamically allocating resources and computing more MC iterations, which is a fundamental feature for hierarchy-adaptive MC algorithms.
To ensure full usage of the machine, the asynchronous analogous of the algorithms has been developed, and proved how this strategy increases the usage efficiency. MLMC estimators, capable of handling goal/solution-oriented adaptively refined hierarchies, were also added.
Concerning Optimization Under Uncertainties (OUU), we aim to provide different risk measures and to update those on-the-fly to keep a maximum parallel efficiency: expected value, variance, higher moments, quantiles, buffered failure probability and Conditional Value at Risk. Another open question is the application to complex engineering problems. A gradient-based techniques based on adjoint calculus was developed for the full-potential equation and applied for the optimization of a wing profile. Parametric optimization was developed in application to a wind engineering problem.
A novel approach, based on the combination of time average and ensamble averaging is proposed to reduce the computational effort needed for wind predictions. The new approach is particularly convenient when running in distributed environments and sufficiently computational resources are available. We found that computational times decreases with respect to the standard method of running a unique simulation with a large time window.
IMPACT
Aside for the possibility of scaling up to any system size, ExaQUte took advantage of persistent local storage. This allowed sidestepping IO bottlenecks, which represent one of the practical limitations of future HPC hardware.
The results from ExaQUte are open source, allowing industry and academia to develop world-class products and services that will help to maintain EC leadership in HPC. The modular structure used in the software framework, will allows the project outcomes to be used beyond the demonstrator application by a larger user community, including industry (civil engineering) which has historically not been a major customer of HPC infrastructure.
The application field of ExaQUte has potencial high socialeconomic and environmental impact for predictive safety of civil constructions( buildings, bridges, harbours, …) under forces due to water or natural hazards . The output of this research is essential for enhanced analysis, risk assessment and performance-based design of constructions, to protect population and infrastructure against hazards.
ExaQUte will contribute to keeping and fostering that knowledge and know-how of scientists within Europe. The use of HPC computers requires significant expertise. ExaQUte provides room for highly skilled scientists to develop their work at the highest level of international research in European institutions,
