Energy efficient acceleration and evaluation of financial computations towards real-time pricing
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part IV
Algorithmic complexity in the heston model: an implementation view
Proceedings of the fourth workshop on High performance computational finance
A hardware efficient random number generator for nonuniform distributions with arbitrary precision
International Journal of Reconfigurable Computing - Special issue on Selected Papers from the International Conference on Reconfigurable Computing and FPGAs (ReConFig'10)
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For numerous computationally complex applications, like financial modelling and Monte Carlo simulations, the fast generation of high quality non-uniform random numbers (RNs) is essential. The implementation of such generators in FPGA-based accelerators has therefore become a very active research field. In this paper we present a novel approach to create RNs for different distributions based on an efficient transformation of floating-point inputs. For the Gaussian distribution we can reduce the number of slices needed by up to 48\% compared to the state-of-the-art while achieving a higher output precision in the tail region. Our architecture produces samples up to $8.37\sigma$ and achieves 381MHz. We also present a comprehensive testing methodology based on stochastic analysis and verification in practical applications.