Parallel simulation of high‐dimensional American option pricing based on CPU versus MIC

Summary American option pricing is a high‐dimensional problem, and its computational challenges have attracted significant attention. We examine this problem using a stochastic mesh method enhanced with bias reduction within the classic Black–Scholes framework. We present Many Integrated Core (MIC) parallelization and acceleration techniques, which result in significant numerical acceleration for large‐scale simulations. In particular, we observe speed‐ups of 21‐fold and 28‐fold for CPU and MIC, respectively, over conventional means. Convergence performance is also examined.