Parallel Quasi-Monte Carlo Integration by Partitioning Low Discrepancy Sequences [chapter]

Alexander Keller, Leonhard Grünschloß
2012 Monte Carlo and Quasi-Monte Carlo Methods 2010  
A general concept for parallelizing quasi-Monte Carlo methods is introduced. By considering the distribution of computing jobs across a multiprocessor as an additional problem dimension, the straightforward application of quasi-Monte Carlo methods implies parallelization. The approach in fact partitions a single low-discrepancy sequence into multiple low-discrepancy sequences. This allows for adaptive parallel processing without synchronization, i.e. communication is required only once for the
more » ... inal reduction of the partial results. Independent of the number of processors, the resulting algorithms are deterministic, and generalize and improve upon previous approaches.
doi:10.1007/978-3-642-27440-4_27 fatcat:xwjvnhnb7ne5vaubvaky4dffda