Distributed Monte Carlo simulation for option pricing: The first completed benchmark and applications of distributed Monte Carlo simulation model on high-performance computing architecture

Abstract

As financial institution computing requirements grow exponentially, we have explored the potential for the ClearSpeed Accelerator, the Cell processor and the FPGA (A field-programmable gate array) to run risk analytics applications. We also invented the Smoothed Alias Method based generator for FPGA in order to achieve the fast result. We have taken Monte Carlo algorithm from my C++ Quantitative Library and rewrite it for this benchmark purpose and test the algorithm with some clever numerical adaptation with the Bulk Synchronous Parallel (BSP) computing model in order to leverage the distributed computing architecture. Following the initial benchmark, we have chosen to use the ClearSpeed Accelerator. With some smart quant re-engineering, we have further optimized the Distributed MC algorithm for pricing Bermudan Swaption to exploit the potential of distributed-based architecture. We will show the comparative benchmark results of the MC algorithm on ClearSpeed Accelerator, Cell and FPGA platform for the first time within our industry based on my working notes from my time in Barclays Capital London.