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@ARTICLE{Mohr:187234,
author = {Mohr, Bernd},
title = {{S}calable parallel performance measurement and analysis
tools - state-of-the-art and future challenges},
journal = {Supercomputing frontiers and innovations},
volume = {1},
number = {2},
issn = {2313-8734},
address = {Chelyabinsk},
publisher = {South Ural State University},
reportid = {FZJ-2015-00907},
pages = {108-123},
year = {2014},
abstract = {Current large-scale HPC systems consist of complex
configurations with a huge number of potentially
heterogeneous components. As the systems get larger, their
behavior becomes more and more dynamic and unpredictable
because of hard- and software re-configurations due to
faultrecovery and power usage optimizations. Deep software
hierarchies of large, complex system software and middleware
components are required to operate such systems. Therefore,
porting, adapting and tuning applications to today's complex
systems is a complicated and time-consumingtask.
Sophisticated integrated performance measurement, analysis,
and optimization capabilities are required to efficiently
utilize such systems. This article will summarize the
state-of-the-art of scalable and portable parallel
performance tools and the challenges these tools are facing
on future extreme-scale and big data systems.},
cin = {JSC},
ddc = {004},
cid = {I:(DE-Juel1)JSC-20090406},
pnm = {411 - Computational Science and Mathematical Methods
(POF2-411) / ATMLPP - ATML Parallel Performance (ATMLPP)},
pid = {G:(DE-HGF)POF2-411 / G:(DE-Juel-1)ATMLPP},
typ = {PUB:(DE-HGF)16},
doi = {10.14529/jsfi140207},
url = {https://juser.fz-juelich.de/record/187234},
}