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@INPROCEEDINGS{Geimer:1034058,
author = {Geimer, Markus},
title = {{P}arallel {P}erformance {A}nalysis},
reportid = {FZJ-2024-06879},
year = {2024},
note = {Tutorial slides},
abstract = {To effectively harness the computing capabilities of todays
and future supercomputing systems, performance analysis and
optimization should be a regular activity during scientific
software development. Instead of using do-it-yourself
solutions usually based on coarse-grained timers (e.g., time
per timestep or solver iteration), developers of scientific
code bases can resort to a variety of spezialized tools that
have been specifically developed to assist them with this
task. In this tutorial, we will introduce the open-source
tools Score-P and Cube, and explore their usage and
capabilities with a number of hands-on exercises.},
month = {Nov},
date = {2024-11-05},
organization = {3rd natESM Training Workshop, Jülich
(Germany), 5 Nov 2024 - 6 Nov 2024},
subtyp = {Other},
cin = {JSC},
cid = {I:(DE-Juel1)JSC-20090406},
pnm = {5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs)
and Research Groups (POF4-511) / ATMLPP - ATML Parallel
Performance (ATMLPP)},
pid = {G:(DE-HGF)POF4-5112 / G:(DE-Juel-1)ATMLPP},
typ = {PUB:(DE-HGF)31},
doi = {10.34734/FZJ-2024-06879},
url = {https://juser.fz-juelich.de/record/1034058},
}