Achieving Speedup in Aggregate Risk Analysis using Multiple GPUs
AbstractStochastic simulation techniques employed for the analysis of portfolios of insurance/reinsurance risk, often referred to as `Aggregate Risk Analysis', can benefit from exploiting state-of-the-art high-performance computing platforms. In this paper, parallel methods to speed-up aggregate risk analysis for supporting real-time pricing are explored. An algorithm for analysing aggregate risk is proposed and implemented for multi-core CPUs and for many-core GPUs. Experimental studies indicate that GPUs offer a feasible alternative solution over traditional high-performance computing systems. A simulation of 1,000,000 trials with 1,000 catastrophic events per trial on a typical exposure set and contract structure is performed in less than 5 seconds on a multiple GPU platform. The key result is that the multiple GPU implementation can be used in real-time pricing scenarios as it is approximately 77x times faster than the sequential counterpart implemented on a CPU.
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Bibliographic InfoPaper provided by arXiv.org in its series Papers with number 1308.2572.
Date of creation: Aug 2013
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Web page: http://arxiv.org/
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-08-23 (All new papers)
- NEP-CMP-2013-08-23 (Computational Economics)
- NEP-IAS-2013-08-23 (Insurance Economics)
- NEP-RMG-2013-08-23 (Risk Management)
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