Local Volatility FX Basket Option on CPU and GPU

Jacques du Toit, Isabel Ehrlich
Numerical Algorithms Group
Numerical Algorithms Group, Technical report TR1/13, 2013


   title={Local Volatility FX Basket Option on CPU and GPU},

   author={du Toit, Jacques and Ehrlich, Isabel},



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We present high performance implementations on a CPU and an NVIDIA GPU of a Monte Carlo pricer for a simple FX basket option driven by a multi-factor local volatility model. Basket options such as these are typically considered too complicated to tackle analytically in a market-consistent manner, and are too high dimensional for PDE methods. Consequently these products are valued using Monte Carlo methods. This results in a compute intensive, massively parallel problem which is ideally suited to modern CPUs and GPUs. We develop fully parallelized, fully vectorized code and study the effects of mixed precision on accuracy and performance. We also investigate using texture memory on the GPU.
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