Famine and land, 1845-80

While historians once tended to displace the Famine from a pivotal position in modern Irish history, more recent research emphasizes its centrality, and focuses upon the controversial issue of state responsibility. Mortality levels from the Famine place it, proportionately, as one of the most devastating recorded human catastrophes. Official British policy towards Ireland spanned two governments, those of Robert Peel and John Russell, with historians taking a more emollient view of the former: in fact there were significant continuities between the two. The legacy of the Famine was uneven, with commercial and technological advance and the consolidation of both the farming interest and landlordism. On the other hand, recent research emphasizes evidence of continuing economic uncertainty, particularly in the West, together with ongoing landlord-tenant tensions. Rural insecurities, crystallized by the poor harvests of 185964, underlay the post-Famine years, and fed into the politicization of the later 1870s.

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.