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检索条件"任意字段=Proceedings of the 2016 ACM Symposium on Principles of Distributed Computing"

共 1394 条记录，以下是41-50 订阅

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distributed Symmetry Breaking on Power Graphs via Sparsification 23

Distributed Symmetry Breaking on Power Graphs via Sparsifica...

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

作者： Maus, Yannic Peltonen, Saku Uitto, Jara Graz Univ Technol Graz Austria Aalto Univ Espoo Finland

ISBN: (纸本)9798400701214

In this paper we present efficient distributed algorithms for classical symmetry breaking problems, maximal independent sets (MIS) and ruling sets, in power graphs. We work in the standard CONGEST model of distributed message passing, where the communication network is abstracted as a graph G. Typically, the problem instance in CONGEST is identical to the communication network G, that is, we perform the symmetry breaking in G. In this work, we consider a setting where the problem instance corresponds to a power graph G(k), where each node of the communication network G is connected to all of its k-hop neighbors. A beta-ruling set is a set of non-adjacent nodes such that each node in.. has a ruling neighbor within beta hops;a natural generalization of an MIS. On top of being a natural family of problems, ruling sets (in power graphs) are well-motivated through their applications in the powerful shattering framework [BEPS Jacm'16, Ghaffari SODA'19] (and others). We present randomized algorithms for computing maximal independent sets and ruling sets of G(k) in essentially the same time as they can be computed in G. Our main contribution is a deterministic poly(k, logn) time algorithm for computing k-ruling sets of G(k), which (for k > 1) improves exponentially on the current state-of-the-art runtimes. Our main technical ingredient for this result is a deterministic sparsification procedure which may be of independent interest. We also revisit the shattering algorithm for MIS [BEPS J'acm'16] and present different approaches for the post-shattering phase. Our solutions are algorithmically and analytically simpler (also in the LOCAL model) than existing solutions and obtain the same runtime as [Ghaffari SODA'16].

关键词： distributed algorithm CONGEST model maximal independent set ruling sets power graphs sparsification shattering

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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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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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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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distributed MIS in O (log log n) Awake Complexity 23

Distributed MIS in O (log log n) Awake Complexity

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

作者： Dufoulon, Fabien Moses, William K., Jr. Pandurangan, Gopal Univ Houston Houston TX 77004 USA Univ Durham Durham England

ISBN: (纸本)9798400701214

Maximal Independent Set (MIS) is one of the fundamental and most well-studied problems in distributed graph algorithms. Even after four decades of intensive research, the best known (randomized) MIS algorithms have O (log n) round complexity on general graphs [Luby, STOC 1986] (where n is the number of nodes), while the best known lower bound is Omega(root logn/log logn) [Kuhn, Moscibroda, Wattenhofer, Jacm 2016]. Breaking past the O (log n) round complexity upper bound or showing stronger lower bounds have been longstanding open problems. E nergy is a premium resource in various settings such as batterypowered wireless networks and sensor networks. The bulk of the energy is used by nodes when they are awake, i.e., when they are sending, receiving, and even just listening for messages. On the other hand, when a node is sleeping, it does not perform any communication and thus spends very little energy. Several recent works have addressed the problem of designing energy-efficient distributed algorithms for various fundamental problems. These algorithms operate by minimizing the number of rounds in which any node is awake, also called the (worst-case) awake complexity. An intriguing open question is whether one can design a distributed MIS algorithm that has significantly smaller awake complexity compared to existing algorithms. In particular, the question of obtaining a distributed MIS algorithm with o (log n) awake complexity was left open in [Chatterjee, Gmyr, Pandurangan, PODC 2020]. Our main contribution is to show that MIS can be computed in awake complexity that is exponentially better compared to the best known round complexity of O( log n) and also bypassing its fundamental Omega(root logn/log log n) round complexity lower bound exponentially. Specifically, we show that MIS can be computed by a randomized distributed (Monte Carlo) algorithm in O (log log n) awake complexity with high probability.1 However, this algorithm has a round complexity that is O ( poly

关键词： Maximal Independent Set Sleeping model energy-efficient awake complexity round complexity trade-offs

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Unintentional Barriers for AP Computer Science principles: A Course Designed for Every Student 2024

Unintentional Barriers for AP Computer Science Principles: A...

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55th acm Technical symposium on Computer Science Education, SIGCSE 2024

作者： McDaniel, Emma L. Christie, Aaja Bourgeois, Anu G. Georgia State University AtlantaGA United States

ISBN: (纸本)9798400704246

In 2016, College Board launched Advanced Placement (AP) Computer Science principles (CSP) as a college-level introductory course to the breadth of Computer Science (CS). This was a joint effort with National Science Foundation to produce a course with a lower barrier of entry to create new pathways of introducing CS to traditionally underrepresented groups in computing;a high school course designed for every student. The sole recommended prerequisite for the course is Algebra I;however, we found that often additional prerequisites and barriers have been imposed. These additional requirements can inadvertently undermine the inclusive vision that underpinned the course's creation. We focus on public high schools in Georgia and discuss different policy barriers that can impact enrollment in AP CSP. © 2024 Owner/Author.

关键词： Students

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proceedings of the Annual acm symposium on principles of distributed computing

Proceedings of the Annual ACM Symposium on Principles of Dis...

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37th acm SIGACT-SIGOPS symposium on principles of distributed computing, PODC 2018

ISBN: (纸本)9781450357951

The proceedings contain 62 papers. The topics discussed include: nesting-safe recoverable linearizability: modular constructions for non-volatile memory;deterministic abortable mutual exclusion with sublogarithmic adaptive RMR complexity;brief announcement: persistent multi-word compare-and-swap;separating lock-freedom from wait-freedom;passing messages while sharing memory;revisionist simulations: a new approach to proving space lower bounds;on the classification of deterministic objects via set agreement power;leveraging indirect signaling for topology inference and fast broadcast;broadcast in radio networks, time vs. energy tradeoffs;round- and message-optimal distributed graph algorithms;improved massively parallel computation algorithms for mismatching, and vertex cover;distributed approximation of minimum k-edge-connected spanning subgraphs;brief announcement: distributed minimum vertex coloring and maximum independent set in chordal graphs;fair leader election for rational agents in asynchronous rings and networks;leader election in well-connected graphs;almost-surely terminating asynchronous byzantine agreement revisited;sublinear message bounds for randomized agreement;tight bounds for asymptotic and approximate consensus;property testing of planarity in the congest model;and locking timestamps versus locking objects.

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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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