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Financial Derivatives Modeling Using GPU’s

Myungho Lee, Chin Hong Chun, Sugwon Hong
Dept. of Comput. Software, Myong Ji Univ., Yong In, South Korea
International Conference on Scalable Computing and Communications; Eighth International Conference on Embedded Computing, 2009. SCALCOM-EMBEDDEDCOM’09

@conference{lee2009financial,

   title={Financial Derivatives Modeling Using GPU’s},

   author={Lee, M. and Chun, C.H. and Hong, S.},

   booktitle={International Conference on Scalable Computing and Communications; The Eighth International Conference on Embedded Computing},

   pages={440–445},

   year={2009},

   organization={IEEE}

}

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The architecture of the latest graphic processing unit (GPU) has surpassed the previous application-specific stream architecture. This has led to an architecture consisting of a number of uniform programmable units integrated on the same chip which facilitate the general-purpose computing beyond the graphic processing. With the multiple programmable units executing in parallel, the latest GPU shows superior performance. Furthermore, programmers can have a direct control on the GPU pipeline using easy-to-use parallel programming environments, whereas they had to rely on specific graphics API’s in the past. These advances in hardware and software make general-purpose GPU (GPGPU) computing widespread. In this paper, using the latest GPU and its software environment, we parallelize a computationally demanding financial application and optimize its performance. We also analyze the performance results compared with those obtained using CPU only. Experimental results show that GPU can achieve a superior performance, greater than 190x, compared with the CPU-only case.
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