高性能计算中的亚式期权蒙特卡罗加速方法

研究蒙特卡罗控制变量方法在CPU(central processing unit)集群和GPU(graphic processing unit)计算环境中的实现问题.以离散取样的随机波动率下的算术平均亚式期权为例,选取合适的控制变量,分别研究了在CPU集群和GPU计算中算法与硬件并行加速两者的运算效率,并讨论了模型参数的变化对计算结果的影响.数值试验表明采用算法与硬件加速相结合的方法可以极大提高计算效率、缩短运算时间.

Monte Carlo Acceleration Method for Pricing Asian Options in High Performance Computing

An investigation was made into the control variate method of Monte Carlo simulation to price Asian options by stochastic volatility model with central processing unit(CPU) cluster and graphic processing unit(GPU) devices. By taking arithmetic average Asian options with stochastic volatility under discrete monitoring time as example, an efficient control variate was chosen, and the computing efficiencies between algorithm accelerating method and devices accelerating method in CPU cluster and GPU were studied respectively. The relationship between the computation results and the parameters of the model was explored. Numerical results show that an integration of the two accelerating methods can shorten the computation time a lot.