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Computational finance relies heavily on the use of Monte Carlo simulation techniques. However, Monte Carlo simulation is computationally very demanding. The authors demonstrate the use of architecturally diverse systems to accelerate the performance of these simulations, exploiting both graphics processing units and field-programmable gate arrays. Performance results include a speedup of 74? relative to an 8 core multiprocessor system (180? relative to a single processor core).Monte Carlo simulation finds frequent application in computational finance, most notably for options pricing and risk assessment.
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