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Title: Using Simulation to Examine the Effect of MPI Message Matching Costs on Application Performance

Abstract

Attaining high performance with MPI applications requires efficient message matching to minimize message processing overheads and the latency these overheads introduce into application communication. We use a validated simulation-based approach to examine the relationship between MPI message matching performance and application time-to-solution. Specifically, we examine how the performance of several important HPC workloads is affected by the time required for matching. Our analysis yields several important contributions: (i) the performance of current workloads is unlikely to be significantly affected by MPI matching unless match queue operations get much slower or match queues get much longer; (ii) match queue designs that provide sublinear performance as a function of queue length are unlikely to yield much benefit unless match queue lengths increase dramatically; and (iii) we provide guidance on how long the mean time per match attempt may be without significantly affecting application performance. The results and analysis in this paper provide valuable guidance on the design and development of MPI message match queues.

Authors:
 [1];  [1];  [1];  [1];  [1]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Center for Computing Research
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1502976
Report Number(s):
SAND-2019-3029J
Journal ID: ISSN 0167-8191; 673544
Grant/Contract Number:  
NA0003525
Resource Type:
Accepted Manuscript
Journal Name:
Parallel Computing
Additional Journal Information:
Journal Volume: 84; Journal ID: ISSN 0167-8191
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Levy, Scott, Ferreira, Kurt B., Schonbein, Whit, Grant, Ryan E., and Dosanjh, Matthew G. F.. Using Simulation to Examine the Effect of MPI Message Matching Costs on Application Performance. United States: N. p., 2019. Web. doi:10.1016/j.parco.2019.02.008.
Levy, Scott, Ferreira, Kurt B., Schonbein, Whit, Grant, Ryan E., & Dosanjh, Matthew G. F.. Using Simulation to Examine the Effect of MPI Message Matching Costs on Application Performance. United States. doi:10.1016/j.parco.2019.02.008.
Levy, Scott, Ferreira, Kurt B., Schonbein, Whit, Grant, Ryan E., and Dosanjh, Matthew G. F.. Wed . "Using Simulation to Examine the Effect of MPI Message Matching Costs on Application Performance". United States. doi:10.1016/j.parco.2019.02.008.
@article{osti_1502976,
title = {Using Simulation to Examine the Effect of MPI Message Matching Costs on Application Performance},
author = {Levy, Scott and Ferreira, Kurt B. and Schonbein, Whit and Grant, Ryan E. and Dosanjh, Matthew G. F.},
abstractNote = {Attaining high performance with MPI applications requires efficient message matching to minimize message processing overheads and the latency these overheads introduce into application communication. We use a validated simulation-based approach to examine the relationship between MPI message matching performance and application time-to-solution. Specifically, we examine how the performance of several important HPC workloads is affected by the time required for matching. Our analysis yields several important contributions: (i) the performance of current workloads is unlikely to be significantly affected by MPI matching unless match queue operations get much slower or match queues get much longer; (ii) match queue designs that provide sublinear performance as a function of queue length are unlikely to yield much benefit unless match queue lengths increase dramatically; and (iii) we provide guidance on how long the mean time per match attempt may be without significantly affecting application performance. The results and analysis in this paper provide valuable guidance on the design and development of MPI message match queues.},
doi = {10.1016/j.parco.2019.02.008},
journal = {Parallel Computing},
number = ,
volume = 84,
place = {United States},
year = {2019},
month = {2}
}

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This content will become publicly available on February 27, 2020
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