Reverse Longstaff-Schwartz American Option Pricing on hybrid CPU/FPGA Systems
Christian Brugger1,a, Javier Alejandro Varela1,b, Norbert Wehn1,c, Songyin Tang2,d and Ralf Korn2,e
1Microelectronic Systems Design Research Group, University of Kaiserslautern, Germany.
2Stochastic Control and Financial Mathematics Group, University of Kaiserslautern, Germany.
In today's markets, high-speed and energy-efficient computations are mandatory in the financial and insurance industry. At the same time, the gradual convergence of highperformance computing with embedded systems is having a huge impact on the design methodologies, where dedicated accelerators are implemented to increase performance and energy efficiency. This paper follows this trend and presents a novel way to price high-dimensional American options using techniques of the embedded community. The proposed architecture targets heterogeneous CPU/FPGA systems, and it exploits the FPGA reconfiguration to deliver high-throughput. With a bit-true algorithmic transformation based on recomputation, it is possible to eliminate the memory bottleneck and access costs. The result is a pricing system that is 16x faster and 268x more energy-efficient than an optimized Intel CPU implementation.
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