Libor market model simulation on an FPGA parallel machine

Abstract

In this paper, we present a high performance scalable FPGA design and implementation of an interest rate derivative pricing engine that targets on the cap pricing. The design consists of a Gaussian random number generator, based on the Mersenne Twister uniform random generator, and a Monte Carlo path generation engine which calculates the prices of an interest rate derivative based on the LIBOR market model. We implemented this design on the Maxwell FPGA supercomputer using up to 32 Xilinx XC4VFX100 FPGA nodes. We have also compared our FPGA hardware implementation with an equivalent optimized pure software implementation running on up to 32 2.8GHz Xeon processors with 1 GB RAM each. This showed our FPGA implementation to be 58x faster than the optimized software implementation, while being more than two orders of magnitude more energy efficient. These results scale linearly with the number of FPGA and Xeon processor nodes used.