English

Coloring Trees in Massively Parallel Computation

Distributed, Parallel, and Cluster Computing 2021-11-02 v2 Data Structures and Algorithms

Abstract

We present O(log2logn)O(\log^2 \log n) time 3-coloring, maximal independent set and maximal matching algorithms for trees in the Massively Parallel Computation (MPC) model. Our algorithms are deterministic, apply to arbitrary-degree trees and work in the low-space MPC model, where local memory is O(nδ)O(n^\delta) for δ(0,1)\delta \in (0,1) and global memory is O(m)O(m). Our main result is the 3-coloring algorithm, which contrasts the randomized, state-of-the-art 4-coloring algorithm of Ghaffari, Grunau and Jin [DISC'20]. The maximal independent set and maximal matching algorithms follow in O(1)O(1) time after obtaining the coloring. The key ingredient of our 3-coloring algorithm is an O(log2logn)O(\log^2 \log n) time adaptation of the rake-and-compress tree decomposition used by Chang and Pettie [FOCS'17], and established by Miller and Reif. When restricting our attention to trees of constant degree, we bring the runtime down to O(loglogn)O(\log \log n).

Keywords

Cite

@article{arxiv.2105.13980,
  title  = {Coloring Trees in Massively Parallel Computation},
  author = {Rustam Latypov and Jara Uitto},
  journal= {arXiv preprint arXiv:2105.13980},
  year   = {2021}
}
R2 v1 2026-06-24T02:34:53.214Z