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Title: Evaluating Trade-offs in Potential Exascale Interconnect Topologies

Abstract

This study looks at the high-level trade-offs for interconnect architectures that are likely to be available in HPC machines in the 2021-2022 timeframe. The study uses multiple simulation models to look at the effects of varying machine size, injection bandwidth and topology for a selected set of benchmark communication patterns. The studies show the sensitivity of various applications to these network parameters. This study can help inform decisions on node size versus number of nodes, which topology is most efficient for our applications, how much injection bandwidth to provision, etc. These simulations only look at interconnects with maximally configured global bandwidth, and studies of networks configured with less will be the subject of future milestones.

Authors:
 [1]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1468904
Report Number(s):
LLNL-TR-756549
944065
DOE Contract Number:  
AC52-07NA27344
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Bhatele, A. Evaluating Trade-offs in Potential Exascale Interconnect Topologies. United States: N. p., 2018. Web. doi:10.2172/1468904.
Bhatele, A. Evaluating Trade-offs in Potential Exascale Interconnect Topologies. United States. doi:10.2172/1468904.
Bhatele, A. Mon . "Evaluating Trade-offs in Potential Exascale Interconnect Topologies". United States. doi:10.2172/1468904. https://www.osti.gov/servlets/purl/1468904.
@article{osti_1468904,
title = {Evaluating Trade-offs in Potential Exascale Interconnect Topologies},
author = {Bhatele, A.},
abstractNote = {This study looks at the high-level trade-offs for interconnect architectures that are likely to be available in HPC machines in the 2021-2022 timeframe. The study uses multiple simulation models to look at the effects of varying machine size, injection bandwidth and topology for a selected set of benchmark communication patterns. The studies show the sensitivity of various applications to these network parameters. This study can help inform decisions on node size versus number of nodes, which topology is most efficient for our applications, how much injection bandwidth to provision, etc. These simulations only look at interconnects with maximally configured global bandwidth, and studies of networks configured with less will be the subject of future milestones.},
doi = {10.2172/1468904},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {8}
}