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Parallel Weighted Random Sampling
2019
European Symposium on Algorithms
Data structures for efficient sampling from a set of weighted items are an important building block of many applications. However, few parallel solutions are known. We close many of these gaps both for shared-memory and distributed-memory machines. We give efficient, fast, and practicable algorithms for sampling single items, k items with/without replacement, permutations, subsets, and reservoirs. We also give improved sequential algorithms for alias table construction and for sampling with
doi:10.4230/lipics.esa.2019.59
dblp:conf/esa/Hubschle-Schneider19
fatcat:ilqbdd4vsnda7kvwo7j3xzc7ly