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

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Redundancy-Free High-Performance Dynamic GNN Training with Hierarchical Pipeline Parallelism 23

Redundancy-Free High-Performance Dynamic GNN Training with H...

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32nd International symposium on High-Performance Parallel and distributed computing (HPDC) part of the acm Federated computing Research Conference (FCRC)

作者： Xia, Yaqi Zhang, Zheng Wang, Hulin Yang, Donglin Zhou, Xiaobo Cheng, Dazhao Wuhan Univ Sch Comp Sci Wuhan Peoples R China Nvidia Corp Santa Clara CA USA Univ Macau IOTSC Macau Peoples R China

ISBN: (纸本)9798400701559

Temporal Graph Neural Networks (TGNNs) extend the success of Graph Neural Networks to dynamic graphs. distributed TGNN training requires efficiently tackling temporal dependency, which often leads to excessive cross-device communication that generates significant redundant data. However, existing systems are unable to remove the redundancy in data reuse and transfer, and suffer from severe communication overhead in a distributed setting. This paper presents Sven, an algorithm and system co-designed TGNN training library for the end-to-end performance optimization on multi-node multi-GPU systems. Exploiting dependency patterns of TGNN models and characteristics of dynamic graph datasets, we design redundancy-free data organization and load-balancing partitioning strategies that mitigate the redundant data communication and evenly partition dynamic graphs at the vertex level. Furthermore, we develop a hierarchical pipeline mechanism integrating data prefetching, micro-batch pipelining, and asynchronous pipelining to mitigate the communication overhead. As the first scaling study on the memory-based TGNNs training, experiments conducted on an HPC cluster of 64 GPUs show that Sven can achieve up to 1.7x-3.3x speedup over the state-of-art approaches and a factor of up to 5.26x communication efficiency improvement.

关键词： distributed training dynamic GNN pipeline parallelism

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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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Detection of Global Anomalies on distributed IoT Edges with Device-to-Device Communication 23

Detection of Global Anomalies on Distributed IoT Edges with ...

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International symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile computing (acm MobiHoc)

作者： Ochiai, Hideya Nishihata, Riku Tomiyama, Eisuke Sun, Yuwei Esaki, Hiroshi Univ Tokyo Tokyo Japan

ISBN: (纸本)9781450399265

Anomaly detection is an important function in IoT applications for finding outliers caused by abnormal events. Anomaly detection sometimes comes with high-frequency data sampling which should be carried out at Edge devices rather than Cloud. In this paper, we consider the case that multiple IoT devices are installed in a single remote site and that they collaboratively detect anomalies from the observations with device-to-device communications. For this, we propose a fully distributed collaborative scheme for training distributed anomaly detectors. We introduce the concept of Global Anomaly which sample is not only rare to the local device but rare to all the devices in the target domain. We also propose a distributed threshold-finding algorithm for Global Anomaly detection. With our standard benchmark-based evaluation, we have confirmed that our scheme trained anomaly detectors perfectly across the devices. We have also confirmed that the devices collaboratively found thresholds for Global Anomaly detection with low false positive rates while achieving high true positive rates with few exceptions.

关键词： Anomaly Detection Collaborative Learning Device-to-Device Communication The Internet of Things

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LIBRA: Harvesting Idle Resources Safely and Timely in Serverless Clusters 23

LIBRA: Harvesting Idle Resources Safely and Timely in Server...

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32nd International symposium on High-Performance Parallel and distributed computing (HPDC) part of the acm Federated computing Research Conference (FCRC)

作者： Yu, Hanfei Fontenot, Christian Wang, Hao Li, Jian Yuan, Xu Park, Seung-Jong Louisiana State Univ Baton Rouge LA 70803 USA SUNY Binghamton Binghamton NY USA Univ Louisiana Lafayette Lafayette LA 70504 USA

ISBN: (纸本)9798400701559

Serverless computing has been favored by users and infrastructure providers from various industries, including online services and scientific computing. Users enjoy its auto-scaling and ease-of-management, and providers own more control to optimize their service. However, existing serverless platforms still require users to pre-define resource allocations for their functions, leading to frequent misconfiguration by inexperienced users in practice. Besides, functions' varying input data further escalate the gap between their dynamic resource demands and static allocations, leaving functions either over-provisioned or under-provisioned. This paper presents Libra, a safe and timely resource harvesting framework for multi-node serverless clusters. Libra makes precise harvesting decisions to accelerate function invocations with harvested resources and jointly improve resource utilization by profiling dynamic resource demands and availability proactively. Experiments on OpenWhisk clusters with real-world workloads show that Libra reduces response latency by 39% and achieves 3x resource utilization compared to state-of-the-art solutions.

关键词： serverless computing resource harvesting

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Auto-HPCnet: An Automatic Framework to Build Neural Network-based Surrogate for High-Performance computing Applications 23

Auto-HPCnet: An Automatic Framework to Build Neural Network-...

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32nd International symposium on High-Performance Parallel and distributed computing (HPDC) part of the acm Federated computing Research Conference (FCRC)

作者： Dong, Wenqian Kestor, Gokcen Li, Dong Florida Int Univ Miami FL 33199 USA Univ Calif Merced Miami FL 95343 USA Pacific Northwest Natl Lab Richland WA 99352 USA

ISBN: (纸本)9798400701559

High-performance computing communities are increasingly adopting Neural Networks (NN) as surrogate models in their applications to generate scientific insights. Replacing an execution phase in the application with NN models can bring significant performance improvement. However, there is a lack of tools that can help domain scientists automatically apply NN-based surrogate models to HPC applications. We introduce a framework, named Auto-HPCnet, to democratize the usage of NN-based surrogates. Auto-HPCnet is the first end-to-end framework that makes past proposals for the NN-based surrogate model practical and disciplined. Auto-HPCnet introduces a workflow to address unique challenges when applying the approximation, such as feature acquisition and meeting the application-specific constraint on the quality of final computation outcome. We show that Auto-HPCnet can leverage NN for a set of HPC applications and achieve 5.50x speedup on average (up to 16.8x speedup and with data preparation cost included) while meeting the application-specific constraint on the final computation quality.

关键词： Scientific Machine Learning Neural Architecture Search Surrogate Model Construction Bayesian Optimization

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proceedings - 2024 IEEE 24th International symposium on Cluster, Cloud and Internet computing, CCGrid 2024

Proceedings - 2024 IEEE 24th International Symposium on Clus...

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24th IEEE/acm International symposium on Cluster, Cloud and Internet computing, CCGrid 2024

ISBN: (纸本)9798350395662

The proceedings contain 75 papers. The topics discussed include: accelerating large language model training with hybrid GPU-based compression;demystifying swarm learning: an emerging decentralized federated learning system;IDIOMS: index-powered distributed object-centric metadata search for scientific data management;Brug: an adaptive memory (re-)allocator;MDSTGCN : multi-scale dynamic spatial-temporal graph convolution network with edge feature embedding for traffic forecasting;fair, efficient multi-resource scheduling for stateless serverless functions with Anubis;STRonG: system topology risk analysis on graphs;federated semi-supervised learning with local and global updating frequency optimization;and towards better QoS and lower costs of P4 EIP gateway at the edge.

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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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TailClipper: Reducing Tail Response Time of distributed Services Through System-Wide Scheduling 15

TailClipper: Reducing Tail Response Time of Distributed Serv...

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15th Annual acm symposium on Cloud computing, SoCC 2024

作者： Ng, Nathan Souza, Abel Ali-Eldin, Ahmed Irwin, David Towsley, Don Shenoy, Prashant University of Massachusetts Amherst United States University of California Santa Cruz United States Chalmers University of Technology Sweden

ISBN: (纸本)9798400712869

Reducing tail latency has become a crucial issue for optimizing the performance of online cloud services and distributed applications. In distributed applications, there are many causes of high end-to-end tail latency, including operating system delays, request re-ordering due to fan-out/fanin, and network congestion. Although recent research has focused on reducing tail latency for individual application components, such as by replicating requests and scheduling, in this paper, we argue for a holistic approach for reducing the end-to-end tail latency across application components. We propose TailClipper, a distributed scheduler that tags each arriving request with an arrival timestamp, and propagates it across the microservices' call chain. TailClipper then uses arrival timestamps to implement an oldest request first scheduler that combines global first-come first serve with a limited form of processor sharing to reduce end-to-end tail latency. In doing so, TailClipper can counter the performance degradation caused by request reordering in multi-tiered and microservices-based applications. We implement TailClipper as a userspace Linux scheduler and evaluate it using cloud workload traces and a real-world microservices application. Compared to state-of-the-art schedulers, our experiments reveal that TailClipper improves the 99th percentile response time by up to 81%, while also improving the mean response time and the system throughput by up to 54% and 29% respectively under high loads. © 2024 Owner/Author.

关键词： Response time (computer systems)

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Asymmetric Failure Assumptions for Reliable distributed Systems 12

Asymmetric Failure Assumptions for Reliable Distributed Syst...

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12th Workshop on principles and Practice of Consistency for distributed Data, PaPoC 2025

作者： Senn, Michael Cachin, Christian University of Bern Bern Switzerland

ISBN: (纸本)9798400715587

In distributed computing, quorum systems are one way to formalize the kind of failures a system aims to tolerate. These assumptions can be either be global and shared by all processes, or processes can be allowed a degree of freedom in making assumptions based on their personal beliefs. In either case, a quorum system's consistency property provides a foundation for building protocols with provable properties. In this work we extend existing models of asymmetric trust, targeted at systems with Byzantine faults, by introducing a weaker quorum consistency property, aimed for example at systems that are subject to crashes only. We then show that a system which complies with only this weaker consistency property is at most as powerful as one with an easily constructed global failure assumption. © 2025 Copyright is held by the owner/author(s).

关键词： Grid computing

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The Power of Multi-step Vizing Chains 2023

The Power of Multi-step Vizing Chains

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55th Annual acm symposium on Theory of computing (STOC) part of the acm Federated computing Research Conference (FCRC)

作者： Christiansen, Aleksander Bjorn Grodt Tech Univ Denmark Lyngby Denmark

ISBN: (纸本)9781450399135

Recent papers have addressed different variants of the (Delta + 1)-edge-colouring problem by concatenating or gluing together many Vizing chains to form what Bernshteyn coined multi-step Vizing chains. In this paper, we consider the most general definition of this term and apply different multi-step Vizing chain constructions to prove combinatorial properties of edge-colourings that lead to (improved) algorithms for computing edge-colouring across different models of computation. This approach seems especially powerful for constructing augmenting subgraphs which respect some notion of locality. First, we construct strictly local multi-step Vizing chains and use them to show a local version of Vizing's Theorem thus confirming a recent conjecture of Bonamy, Delcourt, Lang and Postle. That is, we show that there exists a proper edge-colouring of a graph such that every edge uv. receives a colour from the list {1, 2, ..., max{d (u), d (v)} + 1}. Our proof is constructive and also implies an O(n(2)Delta.) time algorithm for computing such a colouring. Then, we show that for any uncoloured edge there exists an augmenting subgraph of size O (Delta(7) log n), answering an open problem of Bernshteyn. Chang, He, Li, Pettie and Uitto show a lower bound of Omega(Delta log n/Delta) for the size of augmenting subgraphs, so the upper bound is asymptotically tight up to. factors. These ideas also extend to give a faster deterministic LOCAL algorithm for (Delta+ 1)-edge-colouring running in (O) over tilde (poly(Delta) log(6) n) rounds. These results improve the dependency on log.. compared to the recent breakthrough result of Bernshteyn, who showed the existence of augmenting subgraphs of size O (Delta(6) log(2) n), and used these to give the first (Delta + 1)-edge-colouring algorithm in the LOCAL model running in.. (poly(Delta, log n)) rounds. Finally for dynamic graphs, we show how to maintain a(1 + epsilon) Delta-edge-colouring fully adaptive to Delta in O(epsilon(-6) log(9) n lo

关键词： edge-colouring distributed algorithms dynamic algorithms

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