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# Scalasca
## Introduction
[Scalasca][a] is a software tool that supports the performance optimization of parallel programs by measuring and analyzing their runtime behavior. The analysis identifies potential performance bottlenecks – in particular those concerning communication and synchronization – and offers guidance in exploring their causes.
Scalasca supports profiling of MPI, OpenMP and hybrid MPI+OpenMP applications.
## Installed Versions
For the current list of installed versions, use:
```console
$ ml av Scalasca
```
## Usage
Profiling a parallel application with Scalasca consists of three steps:
1. Instrumentation, compiling the application such way, that the profiling data can be generated.
1. Runtime measurement, running the application with the Scalasca profiler to collect performance data.
1. Analysis of reports
### Instrumentation
Instrumentation via `scalasca -instrument` is discouraged. Use [Score-P instrumentation][5].
### Runtime Measurement
After the application is instrumented, runtime measurement can be performed with the `scalasca -analyze` command. The syntax is:
`scalasca -analyze [scalasca options] [launcher] [launcher options] [program] [program options]`
An example:
```console
$ scalasca -analyze mpirun -np 4 ./mympiprogram
```
Some notable Scalasca options are:
* `-t` enables trace data collection. By default, only summary data are collected.
* `-e <directory>` specifies a directory to which the collected data is saved. By default, Scalasca saves the data to a directory with the scorep\_ prefix, followed by the name of the executable and the launch configuration.
!!! note
Scalasca can generate a huge amount of data, especially if tracing is enabled. Consider saving the data to a scratch directory.
For the analysis, you must have the [Score-P][5] and [CUBE][6] modules loaded. The analysis is done in two steps. First, the data is preprocessed and then, the CUBE GUI tool is launched.
$ scalasca -examine [options] <experiment_directory>
```
If you do not wish to launch the GUI tool, use the `-s` option:
```console
$ scalasca -examine -s <experiment_directory>
```
Alternatively, you can open CUBE and load the data directly from here. Keep in mind that in this case, the pre-processing is not done and not all metrics will be shown in the viewer.
Refer to the [CUBE documentation][6] on usage of the GUI viewer.
## References
1. [http://www.scalasca.org/][a]
[1]: ../../modules-matrix.md
[2]: ../compilers.md
[5]: score-p.md