Accelerating Compute-Intensive Applications with GPUs and FPGAs
SASP '08 Proceedings of the 2008 Symposium on Application Specific Processors
Surviving the end of frequency scaling with reconfigurable dataflow computing
ACM SIGARCH Computer Architecture News
Special Issue for the Workshop on High Performance Computational Finance
Concurrency and Computation: Practice & Experience
Multi-level customisation framework for curve based monte carlo financial simulations
ARC'12 Proceedings of the 8th international conference on Reconfigurable Computing: architectures, tools and applications
Moving from petaflops to petadata
Communications of the ACM
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We report new results from an on-going project to accelerate derivatives computations. Our earlier work was focused on accelerating the valuation of credit derivatives. In this paper, we extend our work in two ways: by applying the same techniques, first, to accelerate the computation of portfolio level risk for credit derivatives and, second, to different asset classes using a different type of mathematical model, which together present challenges that are quite different to those dealt with in our earlier work. Specifically, we report acceleration over 270 times faster than a single Intel Core for a multi-asset Monte Carlo model. We also explore the implications for risk. Copyright © 2011 John Wiley & Sons, Ltd.