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A Survey of Communication Performance Models for High-Performance Computing

Published: 05 January 2019 Publication History

Abstract

This survey aims to present the state of the art in analytic communication performance models, providing sufficiently detailed descriptions of particularly noteworthy efforts. Modeling the cost of communications in computer clusters is an important and challenging problem. It provides insights into the design of the communication pattern of parallel scientific applications and mathematical kernels and sets a clear ground for optimization of their deployment in the increasingly complex high-performance computing infrastructure. The survey provides background information on how different performance models represent the underlying platform and shows the evolution of these models over time from early clusters of single-core processors to present-day multi-core and heterogeneous platforms. Prospective directions for future research in the area of analytic communication performance modeling conclude the survey.

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  • (2025)An autotuning approach to select the inter-GPU communication library on heterogeneous systemsThe Journal of Supercomputing10.1007/s11227-024-06794-381:1Online publication date: 1-Jan-2025
  • (2024)Automated Network Performance Characterization for HPC SystemsInternational Journal of Networking and Computing10.15803/ijnc.14.1_214:1(2-25)Online publication date: 2024
  • (2024)Organization of Parallel Computing on Hybrid Computing Clusters Using Fuzzy Intellectual AnalysisPattern Recognition and Image Analysis10.1134/S105466182470046934:3(639-644)Online publication date: 17-Oct-2024
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Published In

cover image ACM Computing Surveys
ACM Computing Surveys  Volume 51, Issue 6
November 2019
786 pages
ISSN:0360-0300
EISSN:1557-7341
DOI:10.1145/3303862
  • Editor:
  • Sartaj Sahni
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 January 2019
Accepted: 01 September 2018
Revised: 01 August 2018
Received: 01 December 2017
Published in CSUR Volume 51, Issue 6

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Author Tags

  1. Communication performance models
  2. analytic modeling
  3. communication performance
  4. high-performance computing

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  • Survey
  • Research
  • Refereed

Funding Sources

  • Science Foundation Ireland (SFI)
  • European Regional Development Fund ”A way to achieve Europe„ (ERDF)
  • Extremadura Local Government
  • EU under the COST Program Action IC1305: Network for Sustainable Ultrascale Computing (NESUS)

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Cited By

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  • (2025)An autotuning approach to select the inter-GPU communication library on heterogeneous systemsThe Journal of Supercomputing10.1007/s11227-024-06794-381:1Online publication date: 1-Jan-2025
  • (2024)Automated Network Performance Characterization for HPC SystemsInternational Journal of Networking and Computing10.15803/ijnc.14.1_214:1(2-25)Online publication date: 2024
  • (2024)Organization of Parallel Computing on Hybrid Computing Clusters Using Fuzzy Intellectual AnalysisPattern Recognition and Image Analysis10.1134/S105466182470046934:3(639-644)Online publication date: 17-Oct-2024
  • (2024)Efficient Inter-Datacenter AllReduce With Multiple TreesIEEE Transactions on Network Science and Engineering10.1109/TNSE.2024.341903011:5(4793-4806)Online publication date: Sep-2024
  • (2024)LLAMP: Assessing Network Latency Tolerance of HPC Applications with Linear ProgrammingSC24: International Conference for High Performance Computing, Networking, Storage and Analysis10.1109/SC41406.2024.00070(1-18)Online publication date: 17-Nov-2024
  • (2024)Graph Computation with Adaptive Granularity2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00169(2123-2136)Online publication date: 13-May-2024
  • (2024)3D Parallelism for Transformers via Integer ProgrammingICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP48485.2024.10446916(6440-6444)Online publication date: 14-Apr-2024
  • (2024)SUARA: A scalable universal allreduce communication algorithm for acceleration of parallel deep learning applicationsJournal of Parallel and Distributed Computing10.1016/j.jpdc.2023.104767183(104767)Online publication date: Jan-2024
  • (2024)Network states-aware collective communication optimizationCluster Computing10.1007/s10586-024-04330-927:5(6869-6887)Online publication date: 1-Aug-2024
  • (2023)Landscape of High-Performance Python to Develop Data Science and Machine Learning ApplicationsACM Computing Surveys10.1145/361758856:3(1-30)Online publication date: 5-Oct-2023
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