Skip to search boxSkip to navigationSkip to main content

On the distributed complexity of large-scale graph computations

  • University of Houston
    ,
  • City University of Hong Kong
    ,
  • University of Padua
Scholary Output:
Contribution to journal
Article
Peer-review

Open access

Abstract

Motivated by the increasing need to understand the distributed algorithmic foundations of large-scale graph computations, we study some fundamental graph problems in a message-passing model for distributed computing where k ≥ 2 machines jointly perform computations on graphs with n nodes (typically, n ≫ k). The input graph is assumed to be initially randomly partitioned among the k machines, a common implementation in many real-world systems. Communication is point-to-point, and the goal is to minimize the number of communication rounds of the computation. Our main contribution is the General Lower Bound Theorem, a theorem that can be used to show non-trivial lower bounds on the round complexity of distributed large-scale data computations. This result is established via an information-theoretic approach that relates the round complexity to the minimal amount of information required by machines to solve the problem. Our approach is generic, and this theorem can be used in a “cookbook” fashion to show distributed lower bounds for several problems, including non-graph problems. We present two applications by showing (almost) tight lower bounds on the round complexity of two fundamental graph problems, namely, PageRank computation and triangle enumeration. These applications show that our approach can yield lower bounds for problems where the application of communication complexity techniques seems not obvious or gives weak bounds, including and especially under a stochastic partition of the input. We then present distributed algorithms for PageRank and triangle enumeration with a round complexity that (almost) matches the respective lower bounds; these algorithms exhibit a round complexity that scales superlinearly in k, improving significantly over previous results [Klauck et al., SODA 2015]. Specifically, we show the following results: • PageRank: We show a lower bound of Ω (n/k2 ) rounds and present a distributed algorithm that computes an approximation of the PageRank of all the nodes of a graph in Õ (n/k2 ) rounds. • Triangle enumeration: We show that there exist graphs with m edges where any distributed algorithm requires Ω (m/k5/3 ) rounds. This result also implies the first non-trivial lower bound of Ω (n1/3 ) rounds for the congested clique model, which is tight up to logarithmic factors. We then present a distributed algorithm that enumerates all the triangles of a graph in Õ (m/k5/3 + n/k4/3 ) rounds.

Publication Information

Output type

Scholary Output:
Contribution to journal
Article
Peer-review

Original language

English (US)

Article number

7

Journal (Volume, Issue Number)

ACM Transactions on Parallel Computing (Volume 8, Issue 2)

Publication milestones

  • Published - 06/2021

Publication status

Published - 06/2021

ISSN

2329-4949

Publication IDs

  • Scopus: 85113500275

Publication metrics

Metrics

Fractional count
1
Fractional count
0.33
Fractional count
2
Fractional count
0.67
Fractional count
1
Fractional count
1
Scopus
citations

PlumX, opens in new tab

Captures
2
Citation count
12

Funding Details

A preliminary version of this work [56]appearedinthe Proceedings of the 30th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA’18). This work was supported, in part, by NSF grants CCF-1527867, CCF-1540512, IIS-1633720, CCF-1717075, by BSF grants 2008348 and 2016419, by University of Padova grant BIRD197859/19, by a grant from the City University of Hong Kong [Project No. 7200639/CS], and by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China [Project No. CityU11213620]. Authors’ addresses: G. Pandurangan, Department of Computer Science, University of Houston, 3551 Cullen Blvd, Houston, TX 77204, USA; email: [email protected]; P. Robinson, Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong; email: [email protected]; M. Scquizzato, Department of Mathematics, University of Padova, Via Trieste 63, 35121 Padova, Italy; email: [email protected]. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]. © 2021 Association for Computing Machinery. 1539-9087/2021/06-ART7 $15.00 https://doi.org/10.1145/3460900
FundersFunding numbers
NSF
CCF-1527867, 1717075, CCF-1540512, IIS-1633720, CCF-1717075
H2020
715672
City University of Hong Kong
7200639/CS
BSF
2016419, 2008348
UNIPD
BIRD197859/19
RGC, UGC
CityU11213620