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Scalasca
(Scalasca 2.2.2, revision 13327)
Scalable Performance Analysis of Large-Scale Applications
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The results of the runtime summarization and/or the automatic trace analysis are stored in one or more reports (i.e., CUBE4 files) in the measurement experiment directory. These reports can be postprocessed and examined using the scalasca -examine
(or short square
) command, providing an experiment directory name as argument:
% scalasca -examine [options] <experiment_name>
Postprocessing is done the first time an experiment is examined, before launching the Cube analysis report browser. If the scalasca -examine
command is provided with an already processed experiment directory, or with a CUBE4 file specified as argument, the viewer is launched immediately.
Instead of interactively examining the measurement analysis results, a textual score report can also be obtained using the -s
option without launching the viewer:
% scalasca -examine -s <experiment_name>
This score report comes from the scorep-score
utility and provides a breakdown of the different types of regions included in the measurement and their estimated associated trace buffer capacity requirements, aggregate trace size and largest process trace buffer size (max_buf
), which can be used to set up a filtering file and to determine an appropriate SCOREP_TOTAL_MEMORY
setting for a subsequent trace measurement. See Section Optimizing the measurement configuration for more details.
The Cube viewer can also be directly used on an experiment archive – opening a dialog window to choose one of the contained CUBE4 files – or an individual CUBE4 file as shown below:
% cube <experiment_name> % cube <file>.cubex
However, keep in mind that no postprocessing is performed in this case, so that only a subset of Scalasca's analyses and metrics may be shown.
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Jülich Supercomputing Centre
Copyright © 2009–2015 German Research School for Simulation Sciences GmbH, Laboratory for Parallel Programming |