We present $O(\log^2 \log n)$ 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 $O(n^\delta)$ for $\delta \in (0,1)$ and global memory is $O(m)$. 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 $O(1)$ time after obtaining the coloring. The key ingredient of our 3-coloring algorithm is an $O(\log^2 \log n)$ 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 $O(\log \log n)$.
翻译:我们提出了 $O (\ log2\\ log n) 时间 3 彩色, 最大独立和最大匹配算法 。 我们的算法是确定性的, 适用于任意度树和低空间 MPC 模型的工作, 当地记忆是$O (n ⁇ delta) $ delta 美元 (0, 1) 美元, 全球记忆是 $O (m) 美元。 我们的主要结果是 3 彩色算法, 与 Ghaffari、 Grunau 和 Jin [DISC'20] 的随机、 最新四色算法对比。 最大独立和最大匹配算法在获得颜色后以美元计。 我们的3 彩色算法的关键成分是 CHang 和 Pettie [FOCS' 17] 使用 时间调制成的 rake- and- remaine 树解调 [FOCS' 17], 由 Miller 和 Reif 确定。 当我们把注意力限制到 恒定的树木时, 。