%0 Conference Paper
%A Geimer, Markus
%T Parallel Performance Analysis
%M FZJ-2024-06879
%D 2024
%Z Tutorial slides
%X 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.
%B 3rd natESM Training Workshop
%C 5 Nov 2024 - 6 Nov 2024, Jülich (Germany)
Y2 5 Nov 2024 - 6 Nov 2024
M2 Jülich, Germany
%F PUB:(DE-HGF)31
%9 Talk (non-conference)
%R 10.34734/FZJ-2024-06879
%U https://juser.fz-juelich.de/record/1034058