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The risk of reinsurance portfolios covering globally occurring naturalcatastrophes, such as earthquakes and hurricanes, is quantified by employingsimulations. These simulations are computationally intensive and require largeamounts of data to be processed. The use of many-core hardware accelerators,such as the Intel Xeon Phi and the NVIDIA Graphics Processing Unit (GPU), aredesirable for achieving high-performance risk analytics. In this paper, we setout to investigate how accelerators can be employed in risk analytics, focusingon developing parallel algorithms for Aggregate Risk Analysis, a simulationwhich computes the Probable Maximum Loss of a portfolio taking both primary andsecondary uncertainties into account. The key result is that both hardwareaccelerators are useful in different contexts; without taking data transfertimes into account the Phi had lowest execution times when used independentlyand the GPU along with a host in a hybrid platform yielded best performance.

The GPU vs Phi Debate: Risk Analytics Using Many-Core Computing