Update doc.zih.tu-dresden.de/docs/software/score_p.md

doc.zih.tu-dresden.de/docs/software/score_p.md

@@ -2,28 +2,28 @@
 
 The Score-P measurement infrastructure is a highly scalable and easy-to-use tool suite for
 profiling, event tracing, and online analysis of HPC applications. Currently, it works with the
-analysis tools Vampir, Scalasca, Periscope, and Tau. Score-P supports lots of features e.g.
+analysis tools Vampir, Scalasca, and Tau. Score-P supports lots of features e.g.
 
-* MPI, SHMEM, OpenMP, pthreads, and hybrid programs
+* MPI, SHMEM, OpenMP, Pthreads, and hybrid programs
 * Manual source code instrumentation
-* Monitoring of CUDA applications
+* Monitoring of CUDA, OpenCL, and OpenACC applications
 * Recording hardware counter by using PAPI library
-* Function filtering and grouping 
+* Function filtering and grouping
 
 Only the basic usage is shown in this Wiki. For a comprehensive Score-P user manual refer to the
-[Score-P website](https://www.vi-hps.org/projects/score-p/).
+[Score-P website](https://score-p.org/).
 
 Before using Score-P, set up the correct environment with
 
 ```Bash
-module load scorep
+module load Score-P
 ```
 
 To make measurements with Score-P, the user's application program needs to be instrumented, i.e., at
 specific important points ("events") Score-P measurement calls have to be activated. By default,
 Score-P handles this automatically. In order to enable instrumentation of function calls, MPI as
-well as OpenMP events, the user only needs to prepend the Score-P wrapper to the usual compiler and
-linker commands. The following sections show some examples depending on the parallelization type of
+well as OpenMP events, the user only needs to prepend the Score-P wrapper to the usual compile and
+link commands. The following sections show some examples depending on the parallelization type of
 the program.
 
 ## Serial Programs
@@ -41,13 +41,13 @@ automatically:
 * original: `mpicc hello.c -o hello`
 * with instrumentation: `scorep mpicc hello.c -o hello`
 
-MPI implementations without own compilers (as on the Altix) require the user to link the MPI library
+MPI implementations without own compilers require the user to link the MPI library
 manually. Even in this case, Score-P will detect MPI parallelization automatically:
 
 * original: `icc hello.c -o hello -lmpi`
 * with instrumentation: `scorep icc hello.c -o hello -lmpi`
 
-However, if Score-P falis to detect MPI parallelization automatically you can manually select MPI
+However, if Score-P fails to detect MPI parallelization automatically you can manually select MPI
 instrumentation:
 
 * original: `icc hello.c -o hello -lmpi`
@@ -90,16 +90,16 @@ After the application run, you will find an experiment directory in your current
 which contains all recorded data.  In general, you can record a profile and/or a event trace.
 Whether a profile and/or a trace is recorded, is specified by the environment variables
 `SCOREP_ENABLE_PROFILING` and `SCOREP_ENABLE_TRACING` (see
-[documentation](https://perftools.pages.jsc.fz-juelich.de/cicd/scorep/tags/scorep-7.0/html/measurement.html)).
+[documentation](https://perftools.pages.jsc.fz-juelich.de/cicd/scorep/tags/latest/html/measurement.html)).
 If the value of this variables is zero or false, profiling/tracing is disabled. Otherwise Score-P
 will record a profile and/or trace. By default, profiling is enabled and tracing is disabled. For
 more information please see
 [the list of Score-P measurement configuration variables]
-(https://perftools.pages.jsc.fz-juelich.de/cicd/scorep/tags/scorep-7.0/html/scorepmeasurementconfig.html)
+(https://perftools.pages.jsc.fz-juelich.de/cicd/scorep/tags/latest/html/scorepmeasurementconfig.html)
 
 You may start with a profiling run, because of its lower space requirements. According to profiling
 results, you may configure the trace buffer limits, filtering or selective recording for recording
 traces.  Score-P allows to configure several parameters via environment variables. After the
-measurement run you can find a scorep.cfg file in your experiment directory which contains the
+measurement run you can find a `scorep.cfg` file in your experiment directory which contains the
 configuration of the measurement run. If you had not set configuration values explicitly, the file
 will contain the default values.