Accelerating Financial Applications on the GPU
Computer and Information Sciences, University of Delaware, Newark, DE 19716
6th Workshop on General Purpose Processor Using Graphics Processing Units (GPGPU-6), 2013
@article{grauer2013accelerating,
title={Accelerating Financial Applications on the GPU},
author={Grauer-Gray, Scott and Killian, William and Searles, Robert and Cavazos, John},
year={2013}
}
The QuantLib library is a popular library used for many areas of computational finance. In this work, the parallel processing power of the GPU is used to accelerate QuantLib financial applications. Black-Scholes, Monte-Carlo, Bonds, and Repo code paths in QuantLib are accelerated using hand-written CUDA and OpenCL codes specifically targeted for the GPU. Additionally, HMPP and OpenACC versions of the applications were created to drive the automatic generation of GPU code from sequential code. The results demonstrate a significant speedup for each code using each parallelization method. We were also able to increase the speedup of HMPP-generated code with auto-tuning.
May 6, 2013 by hgpu
