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Communication-Efficient Accurate Statistical Estimation

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION 2023年第542期118卷 1000-1010页

作者： Fan, Jianqing Guo, Yongyi Wang, Kaizheng Princeton Univ Dept ORFE Princeton NJ 08544 USA Columbia Univ Dept IEOR New York NY 10027 USA

When the data are stored in a distributed manner, direct applications of traditional statistical inference procedures are often prohibitive due to communication costs and privacy concerns. This article develops and investigates two communication-efficient accurate statistical estimators (CEASE), implemented through iterative algorithms for distributed optimization. In each iteration, node machines carry out computation in parallel and communicate with the central processor, which then broadcasts aggregated information to node machines for new updates. The algorithms adapt to the similarity among loss functions on node machines, and converge rapidly when each node machine has large enough sample size. Moreover, they do not require good initialization and enjoy linear converge guarantees under general conditions. The contraction rate of optimization errors is presented explicitly, with dependence on the local sample size unveiled. In addition, the improved statistical accuracy per iteration is derived. By regarding the proposed method as a multistep statistical estimator, we show that statistical efficiency can be achieved in finite steps in typical statistical applications. In addition, we give the conditions under which the one-step CEASE estimator is statistically efficient. Extensive numerical experiments on both synthetic and real data validate the theoretical results and demonstrate the superior performance of our algorithms.

关键词： Communication efficiency Distributed statistical estimation multi-round algorithms Penalized likelihood

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Scheduling divisible workloads on heterogeneous platforms

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PARALLEL COMPUTING 2003年第9期29卷 1121-1152页

作者： Beaumont, O Legrand, A Robert, Y CNRS UMR 5800 LaBRI F-33405 Talence France Ecole Normale Super Lyon CNRS INRIA LIP F-69364 Lyon 07 France

In this paper, we discuss several algorithms for scheduling divisible workloads on heterogeneous systems. Our main contributions are (i) new optimality results for single-round algorithms and (ii) the design of an asymptotically optimal multi-round algorithm. This multi-round algorithm automatically performs resource selection, a difficult task that was previously left to the user. Because it is periodic, it is simpler to implement, and more robust to changes in the speeds of the processors and/or communication links. On the theoretical side, to the best of our knowledge, this is the first published result assessing the absolute performance of a multi-round algorithm. On the practical side, extensive simulations reveal that our multi-round algorithm outperforms existing solutions on a large variety of platforms, especially when the communication-to-computation ratio is not very high (the difficult case). (C) 2003 Elsevier B.V. All rights reserved.

关键词： scheduling divisible tasks multi-round algorithms asymptotical optimality

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UMR2: A better and more realistic scheduling algorithm for the Grid

UMR2: A better and more realistic scheduling algorithm for t...

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18th IASTED International Conference on Parallel and Distributed Computing and Systems

作者： Loc, Nguyen The Elnaffar, Said Katayama, Takuya Bao, Ho Tu JAIST 1-1 Asahidai Nomi Ishikawa 9231292 Japan UAE Univ Coll IT Al Ain U Arab Emirates

ISBN: (纸本)9780889866386

Numerous studies have been targeting the problem of scheduling divisible workloads in distributed computing environments. The UMR (Uniform multi-round) algorithm stands out from all others by being the first close-form optimal scheduling algorithm. However, present algorithms, including the UMR, do not pay due attention to optimizing the set of workers that get selected to participate in processing workload chunks. In addition to the absence of a good resource selection policy, the UMR relies primarily in its computation on the CPU speed and overlooks the role of other key parameters such as network bandwidth. In this paper, we propose an extended version of UMR, called UMR2, that overcomes these limitations and adopts a worker selection policy that aims at minimizing the makespan. We, theoretically and experimentally, show that UMR2 is superior to UMR, specifically in a WAN computing platform such as the Grid.

关键词： divisible loads multi-round algorithms Grid computing

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Scheduling divisible workloads on heterogeneous platforms

Scheduling divisible workloads on heterogeneous platforms

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Workshop on Parallel Matrix algorithms and Applications (PMAA 02)

作者： Beaumont, O Legrand, A Robert, Y CNRS UMR 5800 LaBRI F-33405 Talence France Ecole Normale Super Lyon CNRS INRIA LIP F-69364 Lyon 07 France

关键词： scheduling divisible tasks multi-round algorithms asymptotical optimality

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