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检索条件"任意字段=Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing"

共 1355 条记录，以下是101-110 订阅

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Deterministic Near-Optimal distributed Listing of Cliques 22

Deterministic Near-Optimal Distributed Listing of Cliques

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41st acm symposium on principles of distributed computing, PODC 2022

作者： Censor-Hillel, Keren Leitersdorf, Dean Vulakh, David Technion - Israel Institute of Technology Haifa Israel Massachusetts Institute of Technology CambridgeMA United States

ISBN: (纸本)9781450392624

The importance of classifying connections in large graphs has been the motivation for a rich line of work on distributed subgraph finding that has led to exciting recent breakthroughs. A crucial aspect that remained open was whether deterministic algorithms can be as efficient as their randomized counterparts, where the latter are known to be tight up to polylogarithmic factors. We give deterministic distributed algorithms for listing cliques of size p in n1 - 2/p + o(1) rounds in the Congest model. For triangles, our n1/3+o(1) round complexity improves upon the previous state of the art of n2/3+o(1) rounds [Chang and Saranurak, FOCS 2020]. For cliques of size p ≥ 4, ours are the first non-trivial deterministic distributed algorithms. Given known lower bounds, for all values p ≥ 3 our algorithms are tight up to a no(1) subpolynomial factor, which comes from the deterministic routing procedure we use. © 2022 acm.

关键词： congest distributed graph algorithms cliques

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From Switch Scheduling to Datacenter Scheduling: Matching-Coordinated Greed is Good 22

From Switch Scheduling to Datacenter Scheduling: Matching-Co...

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acm symposium on principles of distributed computing (PODC)

作者： Agarwal, Rachit Rajakrishnan, Shijin Shmoys, David B. Cornell Univ Ithaca NY 14850 USA

ISBN: (纸本)9781450392624

Packet scheduling over a switch (interconnect) fabric is a wellstudied problem in distributed computing, with known near-optimal distributed bipartite matching based protocols. We initiate a theoretical study of distributed flow scheduling in datacenter networks. Building upon the observation that modern datacenter networks use Clos-like topologies similar to switch fabrics, we introduce a new k-sparse flow-matching (k-SFM) problem, a variant of the classical matching problem that captures the unique constraints imposed by flow scheduling in datacenter networks. In the k-SFM problem, we are given a weighted graph and an integer k. The goal is to assign a fractional flow value to each edge under the following three constraints: (1) for each edge, the assigned flow value is no greater than its input weight;(2) for each vertex, the sum of flow values assigned to edges incident to the vertex is at most the capacity of the vertex;and (3) for each vertex, at most k incident edges are assigned a non-zero flow value. The goal is to compute a feasible solution with the largest total fractional weight. We design centralized and distributed algorithms for the k-SFM problem on bipartite graphs. For the centralized setting, we present a greedy 1/2-approximation algorithm. For the distributed setting, we present three algorithms under the CONGEST model: a randomized 1/4-approximation algorithm that runs in O(k log n) rounds, a randomized Omega(1)-approximation algorithm that runs in O(log k log n) rounds, and a deterministic 1/(4 + epsilon)-approximation algorithm that runs in O(k log(2) n log(1/epsilon)) rounds. The key idea in all of our algorithms is that existing approaches for computing maximum-weight matching can be used as a "coordination" mechanism, alongside local and greedy decisions on updating residual weights, to design near-optimal algorithms for the k-SFM problem.

关键词： Datacenter networks Flowscheduling protocols distributed Matching Algorithms

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A Speedup Theorem for Asynchronous Computation with Applications to Consensus and Approximate Agreement 22

A Speedup Theorem for Asynchronous Computation with Applicat...

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acm symposium on principles of distributed computing (PODC)

作者： Fraigniaud, Pierre Paz, Ami Rajsbaum, Sergio Univ Paris Cite IRIF Paris France CNRS Paris France Univ Nacl Autonoma Mexico Inst Matemat Mexico City Mexico

ISBN: (纸本)9781450392624

We study two fundamental problems of distributed computing, consensus and approximate agreement, through a novel approach for proving lower bounds and impossibility results, that we call the asynchronous speedup theorem. For a given n-process task Pi and a given computational model M, we define a new task, called the closure of Pi with respect to M. The asynchronous speedup theorem states that if a task Pi is solvable in t >= 1 rounds in M, then its closure w.r.t. M is solvable in t - 1 rounds in... We prove this theorem for iterated models, as long as the model allows solo executions. We illustrate the power of our asynchronous speedup theorem by providing a new proof of the wait-free impossibility of consensus using read/write registers, and a new proof of the wait-free impossibility of solving consensus using registers and test&set objects for n > 2. The proof is merely by showing that, in each case, the closure of consensus (w.r.t. the corresponding model) is consensus itself. Our main application is the study of the power of additional objects, namely test&set and binary consensus, for wait-free solving approximate agreement faster. By analyzing the closure of approximate agreement w.r.t. each of the two models, we show that while these objects are more powerful than read/write registers from the computability perspective, they are not more powerful as far as helping solving approximate agreement faster is concerned.

关键词： Lower Bounds distributed Algorithms Consensus Approximate Agreement Combinatorial Topology

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Universally-Optimal distributed Exact Min-Cut 22

Universally-Optimal Distributed Exact Min-Cut

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acm symposium on principles of distributed computing (PODC)

作者： Ghaffari, Mohsen Zuzic, Goran MIT Cambridge MA 02139 USA Swiss Fed Inst Technol Zurich Switzerland

ISBN: (纸本)9781450392624

We present a universally-optimal distributed algorithm for the exact weighted min-cut. The algorithm is guaranteed to complete in (O) over tilde (D + root n) rounds on every graph, recovering the recent result of Dory, Efron, Mukhopadhyay, and Nanongkai [STOC'21], but runs much faster on structured graphs. Specifically, the algorithm completes in (O) over tilde (D) rounds on (weighted) planar graphs or, more generally, any (weighted) excluded-minor family. We obtain this result by designing an aggregation-based algorithm: each node receives only an aggregate of the messages sent to it. While somewhat restrictive, recent work shows any such black-box algorithm can be simulated on any minor of the communication network. Furthermore, we observe this also allows for the addition of (a small number of) arbitrarily-connected virtual nodes to the network. We leverage these capabilities to design a min-cut algorithm that is significantly simpler compared to prior distributed work. We hope this paper showcases how working within this paradigm yields simple-to-design and ultra-efficient distributed algorithms for global problems. Our main technical contribution is a distributed algorithm that, given any tree T, computes the minimum cut that 2-respects T (i.e., cuts at most 2 edges of T) in universally near-optimal time. Moreover, our algorithm gives a deterministic (O) over tilde (D)-round 2-respecting cut solution for excluded-minor families and a deterministic (O) over tilde (D + root n)-round solution for general graphs, the latter resolving a question of Dory, et al. [STOC'21]

关键词： exact minimum cut distributed algorithms message-passing algorithms CONGEST model minor-aggregation model low-congestion shortcuts universal optimality

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Brief Announcement: Deterministic Consensus and Checkpointing with Crashes: Time and Communication Efficiency 22

Brief Announcement: Deterministic Consensus and Checkpointin...

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acm symposium on principles of distributed computing (PODC)

作者： Chlebus, Bogdan S. Kowalski, Dariusz R. Olkowski, Jan Augusta Univ Sch Comp & Cyber Sci Augusta GA 30912 USA Univ Maryland Dept Comp Sci College Pk MD USA

ISBN: (纸本)9781450392624

We study consensus and checkpointing in synchronous distributed systems. There are n nodes that communicate by sending messages, and any two nodes can communicate directly. The nodes are prone to crashing, with an upper bound t on the number of crashes. Algorithms use overlay networks of choice to save on the amount of communication. We explore using Ramanujan graphs as such overlay networks. We demonstrate that Ramanujan graphs have topological properties conducive to fault-tolerance and time/communication efficiency of distributed algorithms. Our consensus algorithm assumes binary input values, runs in O(t) time and sends O(n+t log t) bits. The algorithm sends the optimum number O(n) of bits for t = O(n/log n), thus for this range of t it improves on the algorithm by Galil, Mayer and Yung [FOCS 1995] that also sends O(n) bits but works in exponential time. The consensus algorithm can be implemented such that a node sends a message to at most one node at a round while maintaining the asymptotic time and communication performance bounds. Our checkpointing algorithm runs in linear time O(n) and with O(n log(7) n) messages. It improves on the most communication-efficient and time-optimal algorithm by Galil, Mayer and Yung [FOCS 1995], which may have O(n(1+epsilon)) messages sent, for any chosen constant epsilon > 0.

关键词： distributed algorithm message passing synchrony node crash consensus checkpointing Ramanujan graph runtime performance communication performance

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Brief Announcement: Almost Universally Optimal distributed Laplacian Solver 22

Brief Announcement: Almost Universally Optimal Distributed L...

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acm symposium on principles of distributed computing (PODC)

作者： Anagnostides, Ioannis Lenzen, Christoph Haeupler, Bernhard Zuzic, Goran Gouleakis, Themis Carnegie Mellon Univ Pittsburgh PA 15213 USA CISPA Helmholtz Ctr Informat Secur Saarbrucken Germany Swiss Fed Inst Technol Zurich Switzerland Natl Univ Singapore Singapore Singapore

ISBN: (纸本)9781450392624

This paper refines the distributed Laplacian solver recently developed by Forster, Goranci, Liu, Peng, Sun, and Ye (FOCS '21) via the Ghaffari-Haeupler framework (SODA '16) of low-congestion shortcuts. Specifically, if is an element of > 0 is the error of the Laplacian solver, we obtain two main results. First, in the supported version of the CONGEST model, we establish an almost universally optimal Laplacian solver. Namely, we show that any Laplacian system on an..-node graph with shortcut quality SQ(G) can be solved after n(o)( 1) SQ(G) log(1/is an element of) rounds, almost matching our lower bound of e Omega( SQ(G)) rounds on any graph G Our techniques also imply almost universally optimal Laplacian solvers in the full generality of CONGEST, conditional on the efficient construction of shortcuts. In particular, they unconditionally imply a novel Dn(o)(1) log( 1/is an element of) Laplacian solver for excluded-minor graphs with hop-diameter... 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 nodecapacitated clique (NCC) model. In this model, we show the existence of a Laplacian solver with round complexity Dn(o)(1) log( 1/is an element of). The unifying thread of these results, and our main technical contribution, is the development of nearly-optimal distributed algorithms for a novel congested generalization of the standard part-wise aggregation problem. This primitive accelerates the Laplacian solver of Forster, Goranci, Liu, Peng, Sun, and Ye, and we believe it will find further applications in the future.

关键词： distributed algorithms Laplacian solvers universal optimality Hybrid model

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Equitable Student Persistence in computing Research Through distributed Career Mentorship 2023

Equitable Student Persistence in Computing Research Through ...

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54th Annual acm SIGCSE Technical symposium on Computer Science Education (SIGCSE TS)

作者： Davis, Sloan Rorrer, Audrey Grainger, Cori Moghadam, Sepi Hejazi Google Mountain View CA 94043 USA UNC Charlotte Charlotte NC USA

ISBN: (纸本)9781450394314

Google's CS Research Mentorship Program (CSRMP) cultivates pursuit and persistence in the computing research trajectory for students from historically marginalized groups through virtual career mentorship from industry professionals, a peer community, and just-in-time resources. Since 2018, 287 Google mentors have engaged 1,018 students from 247 institutions in the U.S. and Canada. The program employs socioemotional support and advocacy to navigate systemic barriers by validating students' intersectional identities in order to improve outcomes in core constructs for students: self-efficacy, sense of belonging, research skills, motivation to pursue graduate school and research careers, and intersectional capital. Evaluation outcomes from 400 matched respondents (68% response rate) indicate that CSRMP affects positive, statistically significant change in those constructs that largely persists across demographic subgroups. 80% aim to pursue computing research careers, and significantly fewer students are undecided about their future career. We were also able to identify disaggregated learnings: Black, Indigenous, and Latinx students are significantly less likely to submit to a research conference, and students from Historically Marginalized Groups (defined within) are significantly less likely to apply to a CS graduate program. We discuss key design elements of the program, how the findings are informing future iterations, and the potential for the model to scale.

关键词： computing research graduate school mentorship equity capital intersectionality

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PPoPP 2022 - proceedings of the 27th acm SIGPLAN symposium on principles and Practice of Parallel Programming

PPoPP 2022 - Proceedings of the 27th ACM SIGPLAN Symposium o...

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27th acm SIGPLAN symposium on principles and Practice of Parallel Programming, PPoPP 2022

ISBN: (纸本)9781450392044

The proceedings contain 46 papers. The topics discussed include: stream processing with dependency-guided synchronization;mashup: making serverless computing useful for HPC workflows via hybrid execution;parallel block-delayed sequences;near-optimal sparse Allreduce for distributed deep learning;Vapro: performance variance detection and diagnosis for production-run parallel applications;interference relation-guided SMT solving for multi-threaded program verification;extending the limit of molecular dynamics with ab initio accuracy to 10 billion atoms;scaling graph traversal to 281 trillion edges with 40 million cores;asymmetry-aware scalable locking;the performance power of software combining in persistence;and multi-queues can be state-of-the-art priority schedulers.

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Brief Announcement: distributed Algorithms for Minimum Dominating Set Problem and Beyond, a New Approach 36

Brief Announcement: Distributed Algorithms for Minimum Domin...

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36th International symposium on distributed computing, DISC 2022

作者： Alipour, Sharareh Salari, Mohammadhadi Tehran Institute for Advanced Studies Iran Simon Fraser University Burnaby Canada

ISBN: (纸本)9783959772556

In this paper, we study the minimum dominating set (MDS) problem and the minimum total dominating set (MTDS) problem. We propose a new idea to compute approximate MDS and MTDS. This new approach can be implemented in a distributed model or parallel model. We also show how to use this new approach in other related problems such as set cover problem and k-distance dominating set problem. © Sharareh Alipour and Mohammadhadi Salari.

关键词： distributed computer systems

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Reducing carbon emissions of distributed systems: a multi-objective approach 24

Reducing carbon emissions of distributed systems: a multi-ob...

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20th Brazilian symposium on Informations Systems (SBSI) - Perspectives and Trends in Information Systems in Digital Agriculture

作者： Almeida, Guilherme do O, Marcelo T. Francesquini, Emilio Cordeiro, Daniel Univ Sao Paulo Escola Artes Ciencias & Humanidades Sao Paulo SP Brazil Univ Fed ABC Ctr Matemat Comp & Cognicao Santo Andre SP Brazil

ISBN: (纸本)9798400709968

Context The growing usage of platforms for distributed computing and their workloads are requiring more energy to power data centers, and the current consumption is already high. The increasing availability of green energy sources brings opportunities to reduce carbon emissions. Problem It is hard to create software aiming for both performance (makespan) and low brown energy usage. To reduce carbon emissions on distributed platforms, developers need an easy way to program efficiently applications and achieve these objectives. Solution Using OpenMP is an easy way to create and run distributed applications. This paper proposes the use of OpenMP with a new energy-aware scheduling algorithm that aims to minimize brown energy consumption and makespan. IS theory Our multiobjective algorithm (G-MOHEFT) deals with Complexity theory to leverage the Dynamic capabilities of modern distributed platforms. The algorithm implements a heuristic for adapting and redistributing workloads accordingly to different scenarios. Method Containers were used to simulate a distributed OpenMP Cluster (OMPC) platform. Different simulations using previously measured data were used to distribute workloads in different combinations of green energy availability. Summary of Results We study the solution tradeoffs obtained using G-MOHEFT, which varies from saving none to some brown energy consumption by keeping the same or increasing the makespan in exchange. Depending on the scenario, it could even reduce the brown energy consumption to zero. Contributions and impacts to IS Developers can use our algorithm to easily develop distributed software with a reduced carbon footprint using OpenMP in OMPC.

关键词： Tasks scheduling Green energy distributed computing Parallel computing OpenMP

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