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DOI: 10.4230/LIPIcs.DISC.2023.23

Conditionally Optimal Parallel Coloring of Forests

Authors: Christoph Grunau, Rustam Latypov, Yannic Maus, Shreyas Pai, and Jara Uitto

Published in: LIPIcs, Volume 281, 37th International Symposium on Distributed Computing (DISC 2023)

Abstract

We show the first conditionally optimal deterministic algorithm for 3-coloring forests in the low-space massively parallel computation (MPC) model. Our algorithm runs in O(log log n) rounds and uses optimal global space. The best previous algorithm requires 4 colors [Ghaffari, Grunau, Jin, DISC'20] and is randomized, while our algorithm are inherently deterministic. Our main technical contribution is an O(log log n)-round algorithm to compute a partition of the forest into O(log n) ordered layers such that every node has at most two neighbors in the same or higher layers. Similar decompositions are often used in the area and we believe that this result is of independent interest. Our results also immediately yield conditionally optimal deterministic algorithms for maximal independent set and maximal matching for forests, matching the state of the art [Giliberti, Fischer, Grunau, SPAA'23]. In contrast to their solution, our algorithms are not based on derandomization, and are arguably simpler.

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Christoph Grunau, Rustam Latypov, Yannic Maus, Shreyas Pai, and Jara Uitto. Conditionally Optimal Parallel Coloring of Forests. In 37th International Symposium on Distributed Computing (DISC 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 281, pp. 23:1-23:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{grunau_et_al:LIPIcs.DISC.2023.23,
  author =	{Grunau, Christoph and Latypov, Rustam and Maus, Yannic and Pai, Shreyas and Uitto, Jara},
  title =	{{Conditionally Optimal Parallel Coloring of Forests}},
  booktitle =	{37th International Symposium on Distributed Computing (DISC 2023)},
  pages =	{23:1--23:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-301-0},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{281},
  editor =	{Oshman, Rotem},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DISC.2023.23},
  URN =		{urn:nbn:de:0030-drops-191494},
  doi =		{10.4230/LIPIcs.DISC.2023.23},
  annote =	{Keywords: massively parallel computation, coloring, forests, optimal}
}

Document

DOI: 10.4230/LIPIcs.DISC.2022.9

Exponential Speedup over Locality in MPC with Optimal Memory

Authors: Alkida Balliu, Sebastian Brandt, Manuela Fischer, Rustam Latypov, Yannic Maus, Dennis Olivetti, and Jara Uitto

Published in: LIPIcs, Volume 246, 36th International Symposium on Distributed Computing (DISC 2022)

Abstract

Locally Checkable Labeling (LCL) problems are graph problems in which a solution is correct if it satisfies some given constraints in the local neighborhood of each node. Example problems in this class include maximal matching, maximal independent set, and coloring problems. A successful line of research has been studying the complexities of LCL problems on paths/cycles, trees, and general graphs, providing many interesting results for the LOCAL model of distributed computing. In this work, we initiate the study of LCL problems in the low-space Massively Parallel Computation (MPC) model. In particular, on forests, we provide a method that, given the complexity of an LCL problem in the LOCAL model, automatically provides an exponentially faster algorithm for the low-space MPC setting that uses optimal global memory, that is, truly linear. While restricting to forests may seem to weaken the result, we emphasize that all known (conditional) lower bounds for the MPC setting are obtained by lifting lower bounds obtained in the distributed setting in tree-like networks (either forests or high girth graphs), and hence the problems that we study are challenging already on forests. Moreover, the most important technical feature of our algorithms is that they use optimal global memory, that is, memory linear in the number of edges of the graph. In contrast, most of the state-of-the-art algorithms use more than linear global memory. Further, they typically start with a dense graph, sparsify it, and then solve the problem on the residual graph, exploiting the relative increase in global memory. On forests, this is not possible, because the given graph is already as sparse as it can be, and using optimal memory requires new solutions.

Cite as

Alkida Balliu, Sebastian Brandt, Manuela Fischer, Rustam Latypov, Yannic Maus, Dennis Olivetti, and Jara Uitto. Exponential Speedup over Locality in MPC with Optimal Memory. In 36th International Symposium on Distributed Computing (DISC 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 246, pp. 9:1-9:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{balliu_et_al:LIPIcs.DISC.2022.9,
  author =	{Balliu, Alkida and Brandt, Sebastian and Fischer, Manuela and Latypov, Rustam and Maus, Yannic and Olivetti, Dennis and Uitto, Jara},
  title =	{{Exponential Speedup over Locality in MPC with Optimal Memory}},
  booktitle =	{36th International Symposium on Distributed Computing (DISC 2022)},
  pages =	{9:1--9:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-255-6},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{246},
  editor =	{Scheideler, Christian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DISC.2022.9},
  URN =		{urn:nbn:de:0030-drops-172003},
  doi =		{10.4230/LIPIcs.DISC.2022.9},
  annote =	{Keywords: Distributed computing, Locally checkable labeling problems, Trees, Massively Parallel Computation, Sublinear memory}
}

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Brief Announcement

DOI: 10.4230/LIPIcs.DISC.2021.50

Brief Announcement: Memory Efficient Massively Parallel Algorithms for LCL Problems on Trees

Authors: Sebastian Brandt, Rustam Latypov, and Jara Uitto

Published in: LIPIcs, Volume 209, 35th International Symposium on Distributed Computing (DISC 2021)

Abstract

We establish scalable Massively Parallel Computation (MPC) algorithms for a family of fundamental graph problems on trees. We give a general method that, for a wide range of LCL problems, turns their message passing counterparts into exponentially faster algorithms in the sublinear MPC model. In particular, we show that any LCL on trees that has a deterministic complexity of O(n) in the LOCAL model can be sped up to O(log n) (high-complexity regime) in the sublinear MPC model and similarly n^{o(1)} to O(log log n) (intermediate-complexity regime). We emphasize, that we work on bounded degree trees and all of our algorithms work in the sublinear MPC model, where local memory is O(n^δ) for δ < 1 and global memory is O(m). For the high-complexity regime, one key ingredient is a novel pointer-chain technique and analysis that allows us to solve any solvable LCL on trees with a sublinear MPC algorithm with complexity O(log n). For the intermediate-complexity regime, we adapt the approach by Chang and Pettie [FOCS'17], who gave a canonical algorithm for solving LCL problems on trees in the LOCAL model. For the special case of 3-coloring trees, which is a natural LCL problem, we provide a conditional Ω(log log n) lower bound, implying that solving LCL problems on trees with deterministic LOCAL complexity n^{o(1)} requires Θ(log log n) deterministic time in the sublinear MPC model when using a natural family of component-stable algorithms.

Cite as

Sebastian Brandt, Rustam Latypov, and Jara Uitto. Brief Announcement: Memory Efficient Massively Parallel Algorithms for LCL Problems on Trees. In 35th International Symposium on Distributed Computing (DISC 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 209, pp. 50:1-50:4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{brandt_et_al:LIPIcs.DISC.2021.50,
  author =	{Brandt, Sebastian and Latypov, Rustam and Uitto, Jara},
  title =	{{Brief Announcement: Memory Efficient Massively Parallel Algorithms for LCL Problems on Trees}},
  booktitle =	{35th International Symposium on Distributed Computing (DISC 2021)},
  pages =	{50:1--50:4},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-210-5},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{209},
  editor =	{Gilbert, Seth},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DISC.2021.50},
  URN =		{urn:nbn:de:0030-drops-148521},
  doi =		{10.4230/LIPIcs.DISC.2021.50},
  annote =	{Keywords: Distributed computing, Locally checkable labeling problems, Trees, Massively Parallel Computation, Sublinear memory, 3-coloring}
}

3 Search Results for "Latypov, Rustam"

Conditionally Optimal Parallel Coloring of Forests

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Exponential Speedup over Locality in MPC with Optimal Memory

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Brief Announcement: Memory Efficient Massively Parallel Algorithms for LCL Problems on Trees

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