Achieving Speedup in Aggregate Risk Analysis using Multiple GPUs
Abstract
Stochastic 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.
Cite
@article{arxiv.1308.2572,
title = {Achieving Speedup in Aggregate Risk Analysis using Multiple GPUs},
author = {A. K. Bahl and O. Baltzer and A. Rau-Chaplin and B. Varghese and A. Whiteway},
journal= {arXiv preprint arXiv:1308.2572},
year = {2013}
}
Comments
Workshop Proceedings of International Conference on Parallel Processing, Lyon, France, 2013, 8 pages. arXiv admin note: text overlap with arXiv:1308.2066