Brief Announcement: Massively Parallel Approximate Distance Sketches

Authors Michael Dinitz, Yasamin Nazari



PDF
Thumbnail PDF

File

LIPIcs.DISC.2019.42.pdf
  • Filesize: 290 kB
  • 3 pages

Document Identifiers

Author Details

Michael Dinitz
  • Johns Hopkins University, Baltimore, MD, United States
Yasamin Nazari
  • Johns Hopkins University, Baltimore, MD, United States

Cite AsGet BibTex

Michael Dinitz and Yasamin Nazari. Brief Announcement: Massively Parallel Approximate Distance Sketches. In 33rd International Symposium on Distributed Computing (DISC 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 146, pp. 42:1-42:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)
https://doi.org/10.4230/LIPIcs.DISC.2019.42

Abstract

Data structures that allow efficient distance estimation have been extensively studied both in centralized models and classical distributed models. We initiate their study in newer (and arguably more realistic) models of distributed computation: the Congested Clique model and the Massively Parallel Computation (MPC) model. In MPC we give two main results: an algorithm that constructs stretch/space optimal distance sketches but takes a (small) polynomial number of rounds, and an algorithm that constructs distance sketches with worse stretch but that only takes polylogarithmic rounds. Along the way, we show that other useful combinatorial structures can also be computed in MPC. In particular, one key component we use is an MPC construction of the hopsets of Elkin and Neiman (2016). This result has additional applications such as the first polylogarithmic time algorithm for constant approximate single-source shortest paths for weighted graphs in the low memory MPC setting.

Subject Classification

ACM Subject Classification
  • Theory of computation → Massively parallel algorithms
Keywords
  • Distance Sketches
  • Massively Parallel Computation
  • Congested Clique

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads

References

  1. M. Dinitz A. Sarma and G. Pandurangan. Efficient distributed computation of distance sketches in networks. Distributed Computing, 2015. Google Scholar
  2. M. Elkin and O. Neiman. Hopsets with constant hopbound, and applications to approximate shortest paths. In FOCS, 2016. Google Scholar
  3. S. Friedrichs and C. Lenzen. Parallel metric tree embedding based on an algebraic view on moore-bellman-ford. Journal of the ACM (JACM), 2018. Google Scholar
  4. P. Koutris P. Beame and D. Suciu. Communication steps for parallel query processing. In PODS, 2013. Google Scholar
  5. M. Thorup and U. Zwick. Approximate distance oracles. Journal of the ACM (JACM), 2005. Google Scholar
  6. E. Pavlov Z. Lotker, B. Patt-Shamir and D. Peleg. Minimum-weight spanning tree construction in O (log log n) communication rounds. SIAM Journal on Computing, 2005. Google Scholar
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail