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@ARTICLE{Hermanns:861285,
author = {Hermanns, Marc-André and Hjelm, Nathan T. and Knobloch,
Michael and Mohror, Kathryn and Schulz, Martin},
title = {{T}he ${MPI}_{T}$ {E}vents {I}nterface: {A}n {E}arly
{E}valuation and {O}verview of the {I}nterface},
journal = {Parallel computing},
volume = {85},
issn = {0167-8191},
address = {Amsterdam [u.a.]},
publisher = {North-Holland, Elsevier Science},
reportid = {FZJ-2019-01782},
pages = {119-130},
year = {2019},
abstract = {Understanding the behavior of parallel applications that
use the Message Passing Interface (MPI) is critical for
optimizing communication performance. Performance tools for
MPI currently rely on the PMPI Profiling Interface or the
MPI Tool Information Interface, $MPI_T,$ for portably
collecting information for performance measurement and
analysis. While tools using these interfaces have proven to
be extremely valuable for performance tuning, these
interfaces only provide synchronous information, i.e., when
an MPI or an $MPI_T$ function is called. There is currently
no option for collecting information about asynchronous
events from within the MPI library. In this work we propose
a callback-driven interface for event notification from MPI
implementations. Our approach is integrated in the existing
$MPI_T$ interface and provides a portable API for tools to
discover and register for events of interest. We implement
our $MPI_T$ Events interface in Open MPI and demonstrate its
functionality and usability with a small logging tool (MEL)
as well as an early integration into the comprehensive
measurement infrastructure Score-P.},
cin = {JSC / JARA-HPC},
ddc = {620},
cid = {I:(DE-Juel1)JSC-20090406 / $I:(DE-82)080012_20140620$},
pnm = {511 - Computational Science and Mathematical Methods
(POF3-511) / ATMLPP - ATML Parallel Performance (ATMLPP)},
pid = {G:(DE-HGF)POF3-511 / G:(DE-Juel-1)ATMLPP},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000471087700011},
doi = {10.1016/j.parco.2018.12.006},
url = {https://juser.fz-juelich.de/record/861285},
}