Grid-based Quasi-Monte Carlo Applications

In this paper, we extend the techniques used in Grid-based Monte Carlo applications to Grid-based quasi-Monte Carlo applications. These techniques include an N-out-of-M strategy for efficiently scheduling subtasks on the Grid, lightweight checkpointing for Grid subtask status recovery, a partial result validation scheme to verify the correctness of each individual partial result, and an intermediate result checking scheme to enforce the faithful execution of each subtask. Our analysis shows that the extremely high uniformity seen in quasirandom sequences prevents us from applying many of our Grid-based Monte Carlo techniques to Grid-based quasi-Monte Carlo applications. However, the use of scrambled quasirandom sequence becomes a key to tackling this problem, and makes many of the techniques we used in Grid-based Monte Carlo applications effective in Grid-based quasi-Monte Carlo applications. All the techniques we will describe here contribute to performance improvement and trustworthiness enhancement for large-scale quasi-Monte Carlo applications on the Grid, which eventually lead to a high-performance Grid-computing infrastructure that is capable of providing trustworthy quasi-Monte Carlo computation services.