12 Jul 2019
•
Hübschle-Schneider Lorenz
•
Sanders Peter
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 replacement. Experiments on shared-memory parallel machines with up to 158 threads show near
linear speedups both for construction and queries.(read more)