Analysis of Global and Local Synchronization in Parallel Computing

被引:9
|
作者
Cicirelli, Franco [1 ]
Giordano, Andrea [1 ]
Mastroianni, Carlo [1 ]
机构
[1] ICAR CNR, I-87036 Arcavacata Di Rende, Italy
关键词
Algebra; Computational modeling; Simulation; Parallel processing; Probabilistic logic; Random variables; Synchronization; Parallel computing; efficiency; synchronization; CELLULAR-AUTOMATA; PERFORMANCE PREDICTION; MODEL; SIMULATION; INTERNET; PROGRAMS; THINGS; SPACE; TIMES; FLOW;
D O I
10.1109/TPDS.2020.3037469
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In a parallel computing scenario, the synchronization overhead, needed to coordinate the execution on the parallel computing nodes, can significantly impair the overall execution performance. Typically, synchronization is achieved by adopting a global synchronization schema involving all the nodes. In many application domains, though, a looser synchronization schema, namely, local synchronization, can be exploited, in which each node needs to synchronize only with a subset of the other nodes. In this work, we compare the performance of global and local synchronization using the efficiency, i.e., the ratio between the useful computing time and the total computing time, including the synchronization overhead, as a key performance indicator. We present an analytical study of the asymptotic behavior of the efficiency when the number of nodes increases. As an original contribution, we prove, using the Max-Plus algebra, that there is a non-zero lower bound on the efficiency in the case of local synchronization and we present a statistical procedure to find a value of this bound. This outcome marks a significant advantage of local synchronization with respect to global synchronization, for which the efficiency tends to zero when increasing the number of nodes.
引用
收藏
页码:988 / 1000
页数:13
相关论文
共 50 条
  • [31] Ultrafast synchronization via local observation
    Zhang, Hai-Tao
    Fan, Ming-Can
    Wu, Yue
    Gao, Jianxi
    Stanley, H. Eugene
    Zhou, Tao
    Yuan, Ye
    NEW JOURNAL OF PHYSICS, 2019, 21 (01)
  • [32] Transient induced global response synchronization
    Sulis W.
    1600, WITPress (11): : 712 - 721
  • [33] A common parallel computing framework for modeling hydrological processes of river basins
    Wang, Hao
    Fu, Xudong
    Wang, Guangqian
    Li, Tiejian
    Gao, Jie
    PARALLEL COMPUTING, 2011, 37 (6-7) : 302 - 315
  • [34] Leveraging parallel computing in multibody dynamics
    Negrut, Dan
    Tasora, Alessandro
    Mazhar, Hammad
    Heyn, Toby
    Hahn, Philipp
    MULTIBODY SYSTEM DYNAMICS, 2012, 27 (01) : 95 - 117
  • [35] Synchronization of the vibration system excited by four eccentric rotors with parallel and coplanar rotational axis
    Chen, Xiaozhe
    Ban, Mutian
    Shi, Weiye
    Liu, Junqi
    JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, 2024, 38 (06) : 2817 - 2829
  • [36] Synchronization mechanisms in local neural networks in the neocortex. Modeling and experimental studies
    Marchenko V.G.
    Saltykov K.A.
    Neuroscience and Behavioral Physiology, 2011, 41 (5) : 459 - 466
  • [37] Parallel computing of local mesh finite element method
    Yagawa, G
    COMPUTATIONAL MECHANICS, VOLS 1 AND 2, PROCEEDINGS: NEW FRONTIERS FOR THE NEW MILLENNIUM, 2001, : 17 - 26
  • [38] Progress in global parallel computing research: a bibliometric approach
    Zhongqiu Liu
    Yaolin Liu
    Yangjie Guo
    Hua Wang
    Scientometrics, 2013, 95 : 967 - 983
  • [39] Synchronization through communication in a massively parallel processor array
    Butts, Mike
    IEEE MICRO, 2007, 27 (05) : 32 - 40
  • [40] Global synchronization of stochastic delayed complex networks
    Song, Bo
    Park, Ju H.
    Wu, Zheng-Guang
    Zhang, Ya
    NONLINEAR DYNAMICS, 2012, 70 (04) : 2389 - 2399