Computing probable maximum loss in catastrophe reinsurance portfolios on multi-core and many-core architectures

In the reinsurance market, the risks natural catastrophes pose to portfolios of properties must be quantified, so that they can be priced, and insurance offered. The analysis of such risks at a portfolio level requires a simulation of up to 800 000 trials with an average of 1000 catastrophic events per trial. This is sufficient to capture risk for a global multi-peril reinsurance portfolio covering a range of perils including earthquake, hurricane, tornado, hail, severe thunderstorm, wind storm, storm surge and riverine flooding, and wildfire. Such simulations are both computation and data intensive, making the application of high-performance computing techniques desirable.

In this paper, we explore the design and implementation of portfolio risk analysis on both multi-core and many-core computing platforms. Given a portfolio of property catastrophe insurance treaties, key risk measures, such as probable maximum loss, are computed by taking both primary and secondary uncertainties into account. Primary uncertainty is associated with whether or not an event occurs in a simulated year, while secondary uncertainty captures the uncertainty in the level of loss due to the use of simplified physical models and limitations in the available data. A combination of fast lookup structures, multi-threading and careful hand tuning of numerical operations is required to achieve good performance. Experimental results are reported for multi-core processors and systems using NVIDIA graphics processing unit and Intel Phi many-core accelerators.

Investigating Tools used to Analyse the Impact of a Wave Farm on the surrounding Wave Field

For wave energy to become commercially viable, it is predicted that wave energy converters (WECs) will need to be installed in large wave farms. This will required an extensive environmental impact study. Assessments of impacts of these sites requires prior numerical modelling however the available tools have not been fully validated.
This project investigates the area surrounding an array of five scaled WEC models using experimental techniques. It then assesses the suitability of numerical tools to be validated with this experimental data. Validated numerical tools could then be used to predict parameters relating to the models such as reflection and transmission coefficients.
The physical aspect of this project was conducted in the Portaferry wave basin owned by Queen’s University Belfast. The device studied was a bottom hinged oscillating wave surge converter (OWSC) which penetrates the surface (similar to the Oyster device). The models were tested at 40th scale.