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A Near-Optimal Deterministic distributed Synchronizer 23

A Near-Optimal Deterministic Distributed Synchronizer

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42nd acm SIGACT-SIGOPS symposium on principles of distributed computing (PODC)

作者： Ghaffari, Mohsen Trygub, Anton MIT Cambridge MA 02139 USA

ISBN: (纸本)9798400701214

We provide the first deterministic distributed synchronizer with near-optimal time complexity and message complexity overheads. Concretely, given any distributed algorithm A that has time complexity.. and message complexity.. in the synchronous message-passing model (subject to some care in defining the model), the synchronizer provides a distributed algorithm A' that runs in the asynchronous message-passing model with time complexity T . poly(log n) and message complexity (M + m) . poly(log n). Here, n and m denote the number of nodes and edges in the network, respectively. The synchronizer is deterministic in the sense that if algorithm A is deterministic, then so is algorithm A'. Previously, only a randomized synchronizer with near-optimal overheads was known by seminal results of Awerbuch, Patt-Shamir, Peleg, and Saks [STOC 1992] and Awerbuch and Peleg [FOCS 1990]. We also point out and fix some inaccuracies in these prior works. As concrete applications of our synchronizer, we resolve some longstanding and fundamental open problems in distributed algorithms: we get the first asynchronous deterministic distributed algorithms with near-optimal time and message complexities for leader election, breadth-first search tree, and minimum spanning tree computations: these all have message complexity (O) over tilde (m) message complexity. The former two have (O) over tilde (D) time complexity, where D denotes the network diameter, and the latter has (O) over tilde (D + root n) time complexity. All these bounds are optimal up to logarithmic factors. Previously all such near-optimal algorithms were either restricted to the synchronous setting or required randomization.

关键词： synchronizer asynchronous algorithms distributed algorithms

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distributed Delta-Coloring Under Bandwidth Limitations 38

Distributed Delta-Coloring Under Bandwidth Limitations

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38th International symposium on distributed computing, DISC 2024

作者： Halldórsson, Magnús M. Maus, Yannic Reykjavik University Iceland TU Graz Austria

ISBN: (纸本)9783959773522

We consider the problem of coloring graphs of maximum degree ∆ with ∆ colors in the distributed setting with limited bandwidth. Specifically, we give a poly log log n-round randomized algorithm in the CONGEST model. This is close to the lower bound of Ω(log log n) rounds from [Brandt et al., STOC’16], which holds also in the more powerful LOCAL model. The core of our algorithm is a reduction to several special instances of the constructive Lovász local lemma (LLL) and the deg + 1-list coloring problem. © Magnús M. Halldórsson and Yannic Maus.

关键词： Graph algorithms

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Lenzen's distributed Routing Generalized: A Full Characterization of Constant-Time Routability 2024

Lenzen's Distributed Routing Generalized: A Full Characteriz...

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56th Annual acm symposium on Theory of computing (STOC)

作者： Ghaffari, Mohsen Wang, Brandon MIT Cambridge MA 02139 USA

ISBN: (纸本)9798400703836

A celebrated and widely used result of Lenzen and Wattenhofer [STOC'11, PODC'13] shows a constant-round (deterministic) distributed routing algorithm for the complete-graph network: if each node is the source or destination of at most Theta(n) packets, there is a constant-round deterministic distributed algorithm that routes all packets to their destinations in a constant number of rounds, on the complete-graph network. We study generalizations of this result to arbitrary network graphs and show a necessary and sufficient condition for the network so that it can route any such demand in constant rounds distributedly. One can easily see that just for the existence of a constant-round routing for all such demands, it is necessary that any cut's size, when normalized by the number of possible edges in that cut, should be lower bounded by a positive constant. That is, for any partition of nodes with exactly k is an element of [1,n/2] nodes on one side, the cut should have at least Theta(kn) edges. We call this a graph with a positive minimum normalized cut, or a positive graph for short. We show that this necessary condition is also sufficient. In particular, by tightening the Leighton-Rao multicommodity max-flow min-cut theorem for positive graphs, we show the existence of a constant-round routing in positive graphs (assuming the network graph is known globally). Then, as the main technical contribution of this paper, we also show that there is a (deterministic) distributed algorithm that computes such a constant-round routing in constant rounds in these graphs. This result allows us to vastly relax the conditions of the well-studied congested clique model of distributed computing: Any distributed algorithm for the congested clique model can be run in any positive graph network, without any asymptotic slow-down. Our results are in fact more general and they give a distributed routing bound for any network, as a function of its minimum normalized cut size (and without a

关键词： distributed algorithms routing congested clique

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distributed computing Systems and Approaches for Polar Science Research: An Interdisciplinary Systematic Review 24

Distributed Computing Systems and Approaches for Polar Scien...

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24th IEEE/acm International symposium on Cluster, Cloud, and Internet computing (CCGrid)

作者： Kathiravelu, Pradeeban Birmingham, Ryan Univ Alaska Anchorage Anchorage AK 99508 USA Emory Univ Atlanta GA 30322 USA

ISBN: (纸本)9798350377521;9798350377514

Polar science is an umbrella term for several research disciplines practiced in Earth's polar regions and other planets. Polar science research includes studies performed on land (such as geology and archeology on the circumpolar tundra), air (atmospheric research), sky (planetary observations due to dark, clear, and clean skies during the polar nights), and ocean (marine studies in the Arctic and the Southern Oceans). Many polar science research works look into overlapping complementary studies. distributed computing is a discipline of computer science that involves computations across multiple distinct physically separated computing resources, such as computer clusters, clouds, and the edge. distributed computing has enabled efficient, scalable, and elastic execution of complex computational problems on utility hardware without expecting access to expensive infrastructure or supercomputers. In this paper, we screen 770 for the interdisciplinary research of distributed computing used in or developed for polar science. After systematically removing the irrelevant studies, we assess the full text of 72 papers to understand the distributed systems research landscape for polar science. We then specifically study 22 polar science research works that develop or heavily utilize distributed computing frameworks or principles in detail. Our study finds distributed execution frameworks instrumental for polar science due to the complex and real-time computational needs, coupled with the remote location requiring efficient network bandwidth availability and usage to access remote resources.

关键词： Computer Networks distributed computing distributed Systems Environmental Systems Polar Science

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Brief Announcement: On the Limits of Information Spread by Memory-less Agents 24

Brief Announcement: On the Limits of Information Spread by M...

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43rd acm SIGACT-SIGOPS symposium on principles of distributed computing, PODC 2024

作者： D'Archivio, Niccolò Vacus, Robin Coati Inria d'Université Côte d'Azur Sophia Antipolis France Bocconi Institute for Data Science and Analytics Milan Italy

ISBN: (纸本)9798400706684

We address the self-stabilizing bit-dissemination problem, designed to capture the challenges of spreading information and reaching consensus among entities with minimal cognitive and communication capacities. Specifically, a group of n agents is required to adopt the correct opinion, initially held by a single informed individual, choosing from two possible opinions. In order to make decisions, agents are restricted to observing the opinions of a few randomly sampled agents, and lack the ability to communicate further and to identify the informed individual. Additionally, agents cannot retain any information from one round to the next. According to a recent publication in SODA (2024), a logarithmic convergence time without memory is achievable in the parallel setting (where agents are updated simultaneously), as long as the number of samples is at least(Formula presented.). However, determining the minimal sample size for an efficient protocol to exist remains a challenging open question. As a preliminary step towards an answer, we establish the first lower bound for this problem in the parallel setting. Specifically, we demonstrate that it is impossible for any memory-less protocol with constant sample size, to converge with high probability in less than an almost-linear number of rounds. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to acm.

关键词： distributed computer systems

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Brief Announcement: Decreasing Verification Radius in Local Certification 38

Brief Announcement: Decreasing Verification Radius in Local ...

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38th International symposium on distributed computing, DISC 2024

作者： Křišťan, Jan Matyáš Sedláček, Josef Erik Faculty of Information Technology Czech Technical University Prague Czech Republic

ISBN: (纸本)9783959773522

This paper deals with local certification, specifically locally checkable proofs: given a graph property, the task is to certify whether a graph satisfies the property. The verification of this certification needs to be done locally without the knowledge of the whole graph. We examine the trade-off between the visibility radius and the size of certificates. We describe a procedure that decreases the radius by encoding the neighbourhood of each vertex into its certificate. We also provide a corresponding lower bound on the required certificate size increase, showing that such an approach is close to optimal. © Jan Matyáš Křišťan and Josef Erik Sedláček.

关键词： distributed computer systems

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PPoPP 2025 - proceedings of the 2025 30th acm SIGPLAN Annual symposium on principles and Practice of Parallel Programming

PPoPP 2025 - Proceedings of the 2025 30th ACM SIGPLAN Annual...

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30th acm SIGPLAN Annual symposium on principles and Practice of Parallel Programming, PPoPP 2025

ISBN: (纸本)9798400714436

The proceedings contain 49 papers. The topics discussed include: Semi-StructMG: a fast and scalable semi-structured algebraic multigrid;LibRTS: a spatial indexing library by ray tracing;high-performance visual semantics compression for AI-driven science;COMPSO: optimizing gradient compression for distributed training with second-order optimizers;TurboFFT: co-designed high-performance and fault-tolerant fast Fourier transform on GPUs;Helios: efficient distributed dynamic graph sampling for online GNN inference;triangle counting on tensor cores;AC-Cache: a memory-efficient caching system for small objects via exploiting access correlations;magneto: accelerating parallel structures in DNNsvia co-optimization of operators;and FlashSparse: minimizing computation redundancy for fast sparse matrix multiplications on tensor cores.

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Brief Announcement: Discrete Incremental Voting 23

Brief Announcement: Discrete Incremental Voting

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42nd acm SIGACT-SIGOPS symposium on principles of distributed computing (PODC)

作者： Cooper, Colin Radzik, Tomasz Shiraga, Takeharu Kings Coll London London England Chuo Univ Tokyo Japan

ISBN: (纸本)9798400701214

We consider a type of pull voting suitable for discrete numeric opinions which can be compared on a linear scale, for example, 1 ('disagree strongly'), 2 ('disagree'), . . . , 5 ('agree strongly'). On observing the opinion of a random neighbour, a vertex changes its opinion incrementally towards the value of the neighbour's opinion, if different. For opinions drawn from a set {1, 2, . . . , k}, the opinion of the vertex would change by +1 if the opinion of the neighbour is larger, or by -1, if it is smaller. It is not clear how to predict the outcome of this process, but we observe that the total weight of the system, that is, the sum of the individual opinions of all vertices, is a martingale. This allow us analyse the outcome of the process on some classes of dense expanders such as clique graphs k(n) and random graphs G(n,p) for suitably large p. If the average of the original opinions satisfies i <= c <= i + 1 for some integer i, then the asymptotic probability that opinion i wins is i + 1 - c, and the probability that opinion i + 1 wins is c - i. With high probability, the winning opinion cannot be other than i or i + 1. To contrast this, we show that for a path and opinions 0, 1, 2 arranged initially in non-decreasing order along the path, the outcome is very different. Any of the opinions can win with constant probability, provided that each of the two extreme opinions 0 and 2 is initially supported by a constant fraction of vertices.

关键词： Random distributed processes Pull voting

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POSTER: Pattern-Aware Sparse Communication for Scalable Recommendation Model Training 24

POSTER: Pattern-Aware Sparse Communication for Scalable Reco...

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29th acm SIGPLAN Annual symposium on principles and Practice of Parallel Programming (PPoPP)

作者： He, Jiaao Chen, Shengqi Zhai, Jidong Tsinghua Univ Beijing Peoples R China

ISBN: (纸本)9798400704352

Recommendation models are an important category of deep learning models whose size is growing enormous. They consist of a sparse part with TBs of memory footprint and a dense part that demands PFLOPs of computing capability to train. Unfortunately, the high sparse communication cost to re-organize data for different parallel strategies of the two parts impedes the scalability in training. Based on observations of sparse access patterns, we design a two-fold fine-grained parallel strategy to accelerate sparse communication. A performance model is built to select an optimal set of items that are replicated across all GPUs so that all-to-all communication volume is reduced, while keeping memory consumption acceptable. The all-to-all overhead is further reduced by parallel scheduling techniques. In our evaluation on 32 GPUs over real-world datasets, 2.16- 16.8x end-to-end speedup is achieved over the baselines.

关键词： distributed Deep Learning Parallelism

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Optimal Load-Balanced Scalable distributed Agreement 2024

Optimal Load-Balanced Scalable Distributed Agreement

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56th Annual acm symposium on Theory of computing (STOC)

作者： Gelles, Yuval Komargodski, Ilan Hebrew Univ Jerusalem Jerusalem Israel NTT Res Sunnyvale CA USA

ISBN: (纸本)9798400703836

We consider the fundamental problem of designing classical consensus-related distributed abstractions for large-scale networks, where the number of parties can be huge. Specifically, we consider tasks such as Byzantine Agreement, Broadcast, and Committee Election, and our goal is to design scalable protocols in the sense that each honest party processes and sends a number of bits which is sub-linear in n, the total number of parties. In this work, we construct the first such scalable protocols for all of the above tasks. In our protocols, each party processes and sends (O) over tilde (root n) bits throughout (O) over tilde (1) rounds of communication, and correctness is guaranteed for at most 1/3-epsilon fraction of static byzantine corruptions for every constant epsilon > 0 (in the full information model). All previous protocols for the considered agreement tasks were non-scalable, either because the communication complexity was linear or because the computational complexity was super polynomial. We complement our result with a matching lower bound showing that any Byzantine Agreement protocol must have Omega(root n) complexity in our model. Previously, the state of the art was the well-known (Omega) over tilde((3)root n) lower bound of Holtby, Kapron, and King (distributed computing, 2008).

关键词： Byzantine Agreement Consensus Broadcast Leader Election

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