Advances in Topology-Aware Scheduling in Multidimensional Torus-Based Systems

被引:0
|
作者
Li, Kangkang [1 ]
Malawski, Maciej [2 ]
Oleksy, Piotr [2 ]
Nabrzyski, Jarek [1 ]
机构
[1] Univ Notre Dame, Dept Comp Sci & Engn, Notre Dame, IN 46556 USA
[2] AGH Univ Sci & Technol, Dept Comp Sci, Krakow, Poland
基金
美国国家科学基金会;
关键词
Topology-aware; torus-based; job scheduling; job mapping; ALLOCATION; ALGORITHMS; PROCESSOR; STRATEGIES;
D O I
10.3233/978-1-61499-816-7-93
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Communication networks in recent high performance computing machines often have multi-dimensional torus topologies, which influences the way jobs should be scheduled into the system. With the rapid growth of the size of modern HPC system's interconnect, network contention has become a critical issue for the performance of parallel jobs, especially for those which are communicationintensive and not tolerant to inter-job interference. Moreover, to improve the runtime consistency, a contiguous allocation strategy is usually adopted, and each job is allocated a convex prism. However, using this strategy brings in internal and external fragmentation, which can degrade the system utilization. To this end, in this work, we investigate and develop various strategies in topology-aware job scheduling strategies for multidimensional torus-based systems, with the objective of improving job performance and system utilization.
引用
收藏
页码:93 / 118
页数:26
相关论文
共 50 条
  • [1] Topology-aware Job Allocation in 3D Torus-based HPC Systems with Hard Job Priority Constraints
    Li, Kangkang
    Malawski, Maciej
    Nabrzyskil, Jarek
    [J]. INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE (ICCS 2017), 2017, 108 : 515 - 524
  • [2] Topology-Aware OpenMP Process Scheduling
    Thoman, Peter
    Moritsch, Hans
    Fahringer, Thomas
    [J]. BEYOND LOOP LEVEL PARALLELISM IN OPENMP: ACCELERATORS, TASKING AND MORE, PROCEEDINGS, 2010, 6132 : 96 - 108
  • [3] Effects of Topology-Aware Allocation Policies on Scheduling Performance
    Antonio Pascual, Jose
    Navaridas, Javier
    Miguel-Alonso, Jose
    [J]. JOB SCHEDULING STRATEGIES FOR PARALLEL PROCESSING, 2009, 5798 : 138 - 156
  • [4] Topology-Aware Job Scheduling for Machine Learning Cluster
    Lu, Jingyuan
    Li, Peng
    Wang, Kun
    Feng, Huibin
    Guo, Enting
    Wang, Xiaoyan
    Guo, Song
    [J]. 2019 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2019,
  • [5] Topology-Aware Scheduling Framework for Microservice Applications in Cloud
    Li, Xin
    Zhou, Junsong
    Wei, Xin
    Li, Dawei
    Qian, Zhuzhong
    Wu, Jie
    Qin, Xiaolin
    Lu, Sanglu
    [J]. IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2023, 34 (05) : 1635 - 1649
  • [6] A Topology-Aware Reliable Broadcast Scheme for Multidimensional VANET Scenarios
    Liu, Fengrui
    Huang, Chuanhe
    Fan, Xiying
    [J]. COLLABORATIVE COMPUTING: NETWORKING, APPLICATIONS AND WORKSHARING, COLLABORATECOM 2017, 2018, 252 : 275 - 285
  • [7] Topology-Aware Reliability Optimization for Multiprocessor Systems
    Meng, Jie
    Kaplan, Fulya
    Hsieh, Mingyu
    Coskun, Ayse K.
    [J]. 2012 IEEE/IFIP 20TH INTERNATIONAL CONFERENCE ON VLSI AND SYSTEM-ON-CHIP (VLSI-SOC), 2012, : 243 - U348
  • [8] Topology-Aware GPU Scheduling for Learning Workloads in Cloud Environments
    Amaral, Marcelo
    Polo, Jorda
    Carrera, David
    Seelam, Seetharami
    Steinder, Malgorzata
    [J]. SC'17: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE FOR HIGH PERFORMANCE COMPUTING, NETWORKING, STORAGE AND ANALYSIS, 2017,
  • [9] Topology-aware Transmission Scheduling for Highway Wireless Sensor Networks
    Bagaria, Devang
    Wang, Kuang-Ching
    Chowdhury, Mashrur
    [J]. 2009 IEEE 34TH CONFERENCE ON LOCAL COMPUTER NETWORKS (LCN 2009), 2009, : 770 - +
  • [10] Polaris Scheduler: SLO- and Topology-aware Microservices Scheduling at the Edge
    Pusztai, Thomas
    Nastic, Stefan
    Morichetta, Andrea
    Pujol, Victor Casamayor
    Raith, Philipp
    Dustdar, Schahram
    Vij, Deepak
    Xiong, Ying
    Zhang, Zhaobo
    [J]. 2022 IEEE/ACM 15TH INTERNATIONAL CONFERENCE ON UTILITY AND CLOUD COMPUTING, UCC, 2022, : 61 - 70