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Parallel Metric Tree Embedding based on an Algebraic View on Moore-Bellman-Ford

Published: 11 July 2016 Publication History

Abstract

A metric tree embedding of expected stretch α maps a weighted n-node graph G = (V, E, w) to a weighted tree T = (VT, ET, wT) with V ⊆ VT, and dist(v, w, G) ≤ dist(v, w, T) and E[dist(v, w, T)] ≤ α dist(v, w, G) for all v, w ∈ V. Such embeddings are highly useful for designing fast approximation algorithms, as many hard problems are easy to solve on tree instances. However, to date the best parallel polylog n depth algorithm that achieves an asymptotically optimal expected stretch of α ∈ Ω(log n) uses Ω(n2) work and requires a metric as input.
In this paper, we show how to achieve the same guarantees using Ω(m1+ε) work, where $m$ is the number of edges of G and ε >0 is an arbitrarily small constant. Moreover, one may reduce the work further to Ω(m + n1+ε), at the expense of increasing the expected stretch α to Ω(ε-1 log n) using the spanner construction of Baswana and Sen as preprocessing step.
Our main tool in deriving these parallel algorithms is an algebraic characterization of a generalization of the classic Moore-Bellman-Ford algorithm. We consider this framework, which subsumes a large variety of previous "Moore-Bellman-Ford-flavored" algorithms, to be of independent interest.

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cover image ACM Conferences
SPAA '16: Proceedings of the 28th ACM Symposium on Parallelism in Algorithms and Architectures
July 2016
492 pages
ISBN:9781450342100
DOI:10.1145/2935764
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Published: 11 July 2016

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Author Tags

  1. congruence relation on semimodules
  2. distributed algorithm
  3. parallel algorithm
  4. randomized algorithm
  5. tree embedding

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