A Scalable Low Discrepancy Point Generator for Parallel Computing

The Monte Carlo (MC) method is a simple but effective way to perform simulations involving complicated or multivariate functions. The QuasiMonte Carlo (QMC) method is similar but replaces independent and identically distributed (i.i.d.) random points by low discrepancy points. Low discrepancy points are regularly distributed points that may be deterministic or randomized. The digital net is a kind of low discrepancy point set that is generated by number theoretical methods. A computer library for low discrepancy point generation has been developed. It is thread-safe and supports MPI for parallel computation. Some numerical examples from physics and computational finance are shown.

• Type: Conference
• Year: 2004
• Where: ISPA
• Authors: Kwong-Ip Liu, Fred J. Hickernell
• Keywords: Discrepancy Point Generation, ISPA 2004, Low Discrepancy Point, Random Points