Coloring Fast with Broadcasts
April 19, 2023 Β· Declared Dead Β· π ACM Symposium on Parallelism in Algorithms and Architectures
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Maxime Flin, Mohsen Ghaffari, MagnΓΊs M. HalldΓ³rsson, Fabian Kuhn, Alexandre Nolin
arXiv ID
2304.09844
Category
cs.DC: Distributed Computing
Cross-listed
cs.DS
Citations
8
Venue
ACM Symposium on Parallelism in Algorithms and Architectures
Last Checked
4 months ago
Abstract
We present an $O(\log^3\log n)$-round distributed algorithm for the $(Ξ+1)$-coloring problem, where each node broadcasts only one $O(\log n)$-bit message per round to its neighbors. Previously, the best such broadcast-based algorithm required $O(\log n)$ rounds. If $Ξ\in Ξ©(\log^{3} n)$, our algorithm runs in $O(\log^* n)$ rounds. Our algorithm's round complexity matches state-of-the-art in the much more powerful CONGEST model [HalldΓ³rsson et al., STOC'21 & PODC'22], where each node sends one different message to each of its neighbors, thus sending up to $Ξ(n\log n)$ bits per round. This is the best complexity known, even if message sizes are unbounded. Our algorithm is simple enough to be implemented in even weaker models: we can achieve the same $O(\log^3\log n)$ round complexity if each node reads its received messages in a streaming fashion, using only $O(\log^3 n)$-bit memory. Therefore, we hope that our algorithm opens the road for adopting the recent exciting progress on sublogarithmic-time distributed $(Ξ+1)$-coloring algorithms in a wider range of (theoretical or practical) settings.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Distributed Computing
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Reproducing GW150914: the first observation of gravitational waves from a binary black hole merger
R.I.P.
π»
Ghosted
MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems
R.I.P.
π»
Ghosted
Adaptive Federated Learning in Resource Constrained Edge Computing Systems
R.I.P.
π»
Ghosted
Edge Intelligence: Paving the Last Mile of Artificial Intelligence with Edge Computing
R.I.P.
π»
Ghosted
iFogSim: A Toolkit for Modeling and Simulation of Resource Management Techniques in Internet of Things, Edge and Fog Computing Environments
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted