5 merge requests!368Update prace.md to document the change from qprace to qprod as the default...,!367Update prace.md to document the change from qprace to qprod as the default...,!366Update prace.md to document the change from qprace to qprod as the default...,!323extended-acls-storage-section,!67Remark
@@ -6,7 +6,7 @@ CUBE is a graphical performance report explorer for displaying data from Score-P
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@@ -6,7 +6,7 @@ CUBE is a graphical performance report explorer for displaying data from Score-P
-**performance metric**, where a number of metrics are available, such as communication time or cache misses,
-**performance metric**, where a number of metrics are available, such as communication time or cache misses,
-**call path**, which contains the call tree of your program
-**call path**, which contains the call tree of your program
-s**ystem resource**, which contains system's nodes, processes and threads, depending on the parallel programming model.
-**system resource**, which contains system's nodes, processes and threads, depending on the parallel programming model.
Each dimension is organized in a tree, for example the time performance metric is divided into Execution time and Overhead time, call path dimension is organized by files and routines in your source code etc.
Each dimension is organized in a tree, for example the time performance metric is divided into Execution time and Overhead time, call path dimension is organized by files and routines in your source code etc.
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@@ -27,7 +27,7 @@ Currently, there are two versions of CUBE 4.2.3 available as [modules](../../env
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@@ -27,7 +27,7 @@ Currently, there are two versions of CUBE 4.2.3 available as [modules](../../env
CUBE is a graphical application. Refer to Graphical User Interface documentation for a list of methods to launch graphical applications on Anselm.
CUBE is a graphical application. Refer to Graphical User Interface documentation for a list of methods to launch graphical applications on Anselm.
!!! Note "Note"
!!! Note
Analyzing large data sets can consume large amount of CPU and RAM. Do not perform large analysis on login nodes.
Analyzing large data sets can consume large amount of CPU and RAM. Do not perform large analysis on login nodes.
After loading the appropriate module, simply launch cube command, or alternatively you can use scalasca -examine command to launch the GUI. Note that for Scalasca datasets, if you do not analyze the data with scalasca -examine before to opening them with CUBE, not all performance data will be available.
After loading the appropriate module, simply launch cube command, or alternatively you can use scalasca -examine command to launch the GUI. Note that for Scalasca datasets, if you do not analyze the data with scalasca -examine before to opening them with CUBE, not all performance data will be available.
