Parallel Adaptive Sampling with almost no Synchronization

@inproceedings{Grinten2019ParallelAS,
  title={Parallel Adaptive Sampling with almost no Synchronization},
  author={Alexander van der Grinten and Eugenio Angriman and Henning Meyerhenke},
  booktitle={Euro-Par},
  year={2019}
}
  • Alexander van der Grinten, Eugenio Angriman, Henning Meyerhenke
  • Published in Euro-Par 2019
  • Computer Science
  • Approximation via sampling is a widespread technique whenever exact solutions are too expensive. In this paper, we present techniques for an efficient parallelization of adaptive (a. k. a. progressive) sampling algorithms on multi-threaded shared-memory machines. Our basic algorithmic technique requires no synchronization except for atomic load-acquire and store-release operations. It does, however, require O(n) memory per thread, where n is the size of the sampling state. We present variants… CONTINUE READING

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    SHOWING 1-10 OF 25 REFERENCES

    KADABRA is an ADaptive Algorithm for Betweenness via Random Approximation

    VIEW 6 EXCERPTS
    HIGHLY INFLUENTIAL

    Scalable and High Performance Betweenness Centrality on the GPU

    • Adam McLaughlin, David A. Bader
    • Computer Science
    • SC14: International Conference for High Performance Computing, Networking, Storage and Analysis
    • 2014
    VIEW 1 EXCERPT