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Almost Universally Optimal Distributed Laplacian Solvers via Low-Congestion Shortcuts

Abstract

In this paper, we refine the (almost) \emph{existentially optimal} distributed Laplacian solver recently developed by Forster, Goranci, Liu, Peng, Sun, and Ye (FOCS `21) into an (almost) \emph{universally optimal} distributed Laplacian solver. Specifically, when the topology is known, we show that any Laplacian system on an nn-node graph with \emph{shortcut quality} SQ(G)\text{SQ}(G) can be solved within no(1)SQ(G)log(1/ε)n^{o(1)} \text{SQ}(G) \log(1/\varepsilon) rounds, where ε\varepsilon is the required accuracy. This almost matches our lower bound which guarantees that any correct algorithm on GG requires Ω~(SQ(G))\widetilde{\Omega}(\text{SQ}(G)) rounds, even for a crude solution with ε1/2\varepsilon \le 1/2. Even in the unknown-topology case (i.e., standard CONGEST), the same bounds also hold in most networks of interest. Furthermore, conditional on conjectured improvements in state-of-the-art constructions of low-congestion shortcuts, the CONGEST results will match the known-topology ones. Moreover, following a recent line of work in distributed algorithms, we consider a hybrid communication model which enhances CONGEST with limited global power in the form of the node-capacitated clique (NCC) model. In this model, we show the existence of a Laplacian solver with round complexity no(1)log(1/ε)n^{o(1)} \log(1/\varepsilon). The unifying thread of these results, and our main technical contribution, is the study of novel \emph{congested} generalization of the standard \emph{part-wise aggregation} problem. We develop near-optimal algorithms for this primitive in the Supported-CONGEST model, almost-optimal algorithms in (standard) CONGEST, as well as a very simple algorithm for bounded-treewidth graphs with slightly worse bounds. This primitive can be readily used to accelerate the FOCS`21 Laplacian solver. We believe this primitive will find further independent applications.

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