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THE RUN-TIME EFFICIENCY OF PARALLEL asynchronous algorithms

IEEE TRANSACTIONS ON COMPUTERS 1991年第11期40卷 1260-1266页

作者： DUBOIS, M BRIGGS, FA TANDEM COMP INC AUSTINTX 78728

Parallel asynchronous algorithms have been designed to reduce the run-time overhead caused by barrier synchronizations in many numerical and nonnumerical algorithms for multiprocessors. In these algorithms, critical sections are still needed for accessing shared writable data. The run-time efficiency of parallel asynchronous algorithms is mostly affected by the scheduling overhead, by the sharing of critical sections, and by shared-memory conflicts. At the software level, the concurrent accessing of critical sections results in the familiar lock-out problem;at the hardware level, memory access conflicts cause each processor to idle in wait cycles. A simple model to estimate the combined effects of hardware and software contention on the efficiency of asynchronous algorithms is presented in this paper.

关键词： asynchronous algorithms BARRIER SYNCHRONIZATION MEMORY ACCESS CONTENTION MIMD MULTIPROCESSORS PROCESSOR EFFICIENCY SCHEDULING SOFTWARE LOCKOUT

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asynchronous algorithms for Computing Equilibrium Prices in a Capital Asset Pricing Model

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ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH 2019年第5期36卷

作者： Tong, Jun Hu, Jianqiang You, Jianxin Shanghai Univ Sch Management Shanghai 200444 Peoples R China Fudan Univ Dept Management Sci Shanghai 200433 Peoples R China Tongji Univ Sch Econ & Management Shanghai 200092 Peoples R China

In this paper, we extend the work of [Tong, J, J Hu and J flu (2017). Computing equilibrium prices for a capital asset pricing model with heterogeneous beliefs and margin-requirement constraints. European Journal of Operational Research, 256(1), 24-34] and develop various asynchronous algorithms to calculate the equilibrium asset prices in a heterogeneous capital asset pricing model. These asynchronous algorithms are based on different asynchronous updating schemes such as delayed updating, cyclic updating, fixed-length updating and random updating. In addition to potential benefits of improving computational efficiency, these asynchronous updating schemes also reflect several scenarios in financial markets in which investors may receive asset pricing information with various degrees of delays and their preferences on how and when to rebalance their portfolios may also be different. The proofs for the convergence of these algorithms are given. Numerical experiments are also provided to compare these algorithms and they show that these asynchronous algorithms work quite well.

关键词： asynchronous algorithms optimization algorithms computational methods stochastic systems

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Improving Parallelism and Locality with asynchronous algorithms

Improving Parallelism and Locality with Asynchronous Algorit...

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15th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming

作者： Liu, Lixia Li, Zhiyuan Purdue Univ Dept Comp Sci W Lafayette IN 47907 USA

ISBN: (纸本)9781605587080

As multicore chips become the main building blocks for high performance computers, many numerical applications face a performance impediment due to the limited hardware capacity to move data between the CPU and the off-chip memory. This is especially true for large computing problems solved by iterative algorithms because of the large data set typically used. Loop tiling, also known as loop blocking, was shown previously to be an effective way to enhance data locality, and hence to reduce the memory bandwidth pressure, for a class of iterative algorithms executed on a single processor. Unfortunately, the tiled programs suffer from reduced parallelism because only the loop iterations within a single tile can be easily parallelized. In this work, we propose to use the asynchronous model to enable effective loop tiling such that both parallelism and locality can be attained simultaneously. asynchronous algorithms were previously proposed to reduce the communication cost and synchronization overhead between processors. Our new discovery is that carefully controlled asynchrony and loop tiling can significantly improve the performance of parallel iterative algorithms on multicore processors due to simultaneously attained data locality and loop-level parallelism. We present supporting evidence from experiments with three well-known numerical kernels.

关键词： asynchronous algorithms loop tiling parallel numerical programs data locality memory performance

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asynchronous algorithms for approximate distributed constraint optimization with quality bounds 10

Asynchronous algorithms for approximate distributed constrai...

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Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1

作者： Christopher Kiekintveld Zhengyu Yin Atul Kumar Milind Tambe University of Southern California

ISBN: (纸本)9780982657119

Distributed Constraint Optimization (DCOP) is a popular framework for cooperative multi-agent decision making. DCOP is NP-hard, so an important line of work focuses on developing fast incomplete solution algorithms for large-scale applications. One of the few incomplete algorithms to provide bounds on solution quality is k-size optimality, which defines a local optimality criterion based on the size of the group of deviating agents. Unfortunately, the lack of a general-purpose algorithm and the commitment to forming groups based solely on group size has limited the use of k-size *** paper introduces t-distance optimality which departs from k-size optimality by using graph distance as an alternative criteria for selecting groups of deviating agents. This throws open a new research direction into the tradeoffs between different group selection and coordination mechanisms for incomplete DCOP algorithms. We derive theoretical quality bounds for t-distance optimality that improve known bounds for k-size optimality. In addition, we develop a new efficient asynchronous local search algorithm for finding both k-size and t-distance optimal solutions --- allowing these concepts to be deployed in real applications. Indeed, empirical results show that this algorithm significantly outperforms the only existing algorithm for finding general k-size optimal solutions, which is also synchronous. Finally, we compare the algorithmic performance of k-size and t-distance optimality using this algorithm. We find that t-distance consistently converges to higher-quality solutions in the long run, but results are mixed on convergence speed; we identify cases where k-size and t-distance converge faster.

关键词： distributed constraint optimization DALO bounds asynchronous algorithms t-distance optimality approximate DCOP incomplete experimentation k-optimality

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Simple Synchronous and asynchronous algorithms for Distributed Minimax Optimization

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SICE Journal of Control, Measurement, and System Integration 2017年第6期10卷 557-562页

作者： Kenta Hanada Ryosuke Morita Takayuki Wada Yasumasa Fujisaki Graduate School of Information Science and Technology Osaka University Faculty of Engineering Gifu University

Synchronous and asynchronous algorithms are presented for distributed minimax optimization. The objective here is to realize the minimization of the maximum of component functions over the standard multi-agent network, where each node of the network knows its own function and it exchanges its decision variable with its neighbors. In fact, the proposed algorithms are standard consensus and gossip based subgradient methods, while the original minimax optimization is recast as minimization of the sum of component functions by using a p-norm approximation. A scalable step size depending on the approximation ratio p is also presented in order to avoid slow convergence. Numerical examples illustrate that the algorithms with this step size work well even in the high approximation ratios.

关键词： distributed algorithms minimax optimization synchronous algorithms asynchronous algorithms

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asynchronous parallel algorithms for nonconvex optimization

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MATHEMATICAL PROGRAMMING 2020年第1-2期184卷 121-154页

作者： Cannelli, Loris Facchinei, Francisco Kungurtsev, Vyacheslav Scutari, Gesualdo Purdue Univ Sch Ind Engn W Lafayette IN 47907 USA Univ Roma La Sapienza Dept Comp Control & Management Engn Antonio Ruber Rome Italy Czech Tech Univ Fac Elect Engn Dept Comp Sci Prague Czech Republic

We propose a new asynchronous parallel block-descent algorithmic framework for the minimization of the sum of a smooth nonconvex function and a nonsmooth convex one, subject to both convex and nonconvex constraints. The proposed framework hinges on successive convex approximation techniques and a novel probabilistic model that captures key elements of modern computational architectures and asynchronous implementations in a more faithful way than current state-of-the-art models. Other key features of the framework are: (1) it covers in a unified way several specific solution methods;(2) it accommodates a variety of possible parallel computing architectures;and (3) it can deal with nonconvex constraints. Almost sure convergence to stationary solutions is proved, and theoretical complexity results are provided, showing nearly ideal linear speedup when the number of workers is not too large.

关键词： asynchronous algorithms Nonconvex constraints Parallel methods Probabilistic model

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Timing models and local stopping criteria for asynchronous iterative algorithms

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JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING 1999年第3期58卷 446-465页

作者： Blathras, K Szyld, DB Shi, Y Temple Univ Philadelphia PA 19122 USA

asynchronous iterative algorithms can reduce much of the data dependencies associated with synchronization barriers. The reported study investigates the potentials of asynchronous iterative algorithms by quantifying the critical parallel processing factors. Specifically, a time complexity-based analysis method is used to understand the inherent interdependencies between computing and communication overheads for the parallel asynchronous algorithm. The results show, not only that the computational experiments closely match the analytical results, but also that the use of asynchronous iterative algorithms can be beneficial for a vast number of parallel processing environments. The choice of local stopping criteria that is critically important to the overall system performance is investigated in depth. (C) 1999 Academic Press.

关键词： timing models asynchronous algorithms parallel iterative methods

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A MODEL OF EFFICIENT asynchronous PARALLEL algorithms ON MULTICOMPUTER SYSTEMS

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PARALLEL COMPUTING 1992年第1期18卷 31-45页

作者： CONFORTI, D GRANDINETTI, L MUSMANNO, R CANNATARO, M SPEZZANO, G TALIA, D CONSORZIO RIC & APPLICAZ INFORMAT LOCAL S STEFANOI-87036 RENDEITALY

This paper describes a methodology for the implementation of asynchronous parallel algorithms on multicomputer systems. The algorithms studied here belong to the class of iterative methods. The proposed methodology is based on the definition of a computational model by which an algorithm is specified as a set of concurrent processes mapped onto a set of processors and communicating by asynchronous message passing. This approach can be appealing and innovative since there is a need to reduce the cost of synchronization that affects synchronous algorithms. As an application of the proposed approach, the implementation on a network of INMOS Transputers of an asynchronous parallel version of the classical Newton method for solving nonlinear optimization problems is described and discussed. In this implementation each computational task of the algorithm is implemented as an Occam process running on a Transputer. The performance results of the numerical experiments are encouraging and show the effectiveness of the proposed approach.

关键词： PARALLEL algorithms asynchronous algorithms MULTICOMPUTER TRANSPUTER OCCAM NONLINEAR OPTIMIZATION NEWTON METHOD

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asynchronous Distributed algorithms for Heading Consensus of Multi-Agent Systems with Communication Delay

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ASIAN JOURNAL OF CONTROL 2013年第2期15卷 430-443页

作者： Li, Qin Jiang, Zhong-Ping Statoil Res Ctr N-3916 Porsgrunn Norway NYU Dept Elect & Comp Engn Polytech Inst Metrotech Ctr 6 Brooklyn NY 11201 USA

In this paper, we propose two asynchronous distributed protocols for the heading consensus of a multi-agent group which cannot access a global coordinate system and a global time. Both the leaderless and leader-following cases are addressed, and inter-agent communication delay is taken into account. It is proved, under some standard connectivity assumptions, that our leaderless algorithm ensures the heading consensus provided the initial headings are not balanced;and the leader-based algorithm guarantees the global heading consensus.

关键词： Multi-agent systems heading consensus asynchronous algorithms

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Evaluation-Time Bias in Quasi-Generational and Steady-State asynchronous Evolutionary algorithms 16

Evaluation-Time Bias in Quasi-Generational and Steady-State ...

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Genetic and Evolutionary Computation Conference (GECCO)

作者： Scott, Eric O. De Jong, Kenneth A. George Mason Univ Dept Comp Sci Fairfax VA 22030 USA

ISBN: (纸本)9781450342063

A number of papers have emerged in the last two years that apply and study asynchronous master-slave evolutionary algorithms based on a steady-state model. These efforts are largely motivated by the observation that, unlike traditional (synchronous) EAs, asynchronous EAs are able to make maximal use of many parallel processors, even when some individuals evaluate more slowly than others. asynchronous EAs do not behave the same as their synchronous counterparts, however, and as of yet there is very little theory that makes it possible to predict how they will perform on new problems. Of some concern is evidence suggesting that the steady-state versions tend to be biased toward regions of the search space where fitness evaluation is cheaper. This has led some authors to suggest a so-called 'quasi-generational' asynchronous EA as an intermediate solution that incurs neither idle time nor significant bias toward fast solutions. We perform experiments with the quasi-generational EA, and show that it does not deliver the promised bene fits: it is, in fact, just as biased toward fast solutions as the steady-state approach is, and it tends to converge even more slowly than the traditional, generational EA.

关键词： Evolutionary algorithms Parallel and Distributed algorithms asynchronous algorithms

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