User-guide.md

@@ -203,6 +203,18 @@ mpirun -np 64 singularity exec $IMAGE $EAR_INSTALL_PATH/bin/erun \
 Note that the example exports `APPTAINERENV_EAR_REPORT_ADD` to set the environment variable [`EAR_REPORT_ADD`](EAR-environment-variables#report-plug-ins) to load [`sysfs`](Report#sysfs-report-plugin) report plug-in.
 See [next section](#runtime-report-plug-ins) about report plug-ins.
 
+## Using EARL through the COMPSs Framework 
+
+COMP Superscalar ([COMPSs](https://compss-doc.readthedocs.io/en/latest/index.html)) is a task-based programming model which aims to ease the development of applications for distributed infrastructures, such as large High-Performance clusters (HPC), clouds and container managed clusters.
+COMPSs provides a programming interface for the development of the applications and a runtime system that exploits the inherent parallelism of applications at execution time.
+**Since version 5.0 EAR supports monitoring and optimization of workflows** and the COMPSs Framework includes the integration with EAR.
+Check out the [dedicated section](https://compss-doc.readthedocs.io/en/latest/Sections/05_Tools/05_EAR.html#) from the official COMPSs documentation for more information about how to measure the energy consumption of your workflows.
+
+EARL loading is **only available** using `enqueue_compss` and with Python applications.
+The command has the flag `--ear` which you can set either a boolean (i.e., *true* or *false*) or a string value.
+The latter can be any of the [job submission flags](ear-job-submission-flags).
+See the [example](https://compss-doc.readthedocs.io/en/latest/Sections/05_Tools/05_EAR.html#example) provided by the COMPSs documentation.
+
 # Retrieving EAR data
 
 As a job accounting and monitoring tool, EARL collects some metrics that you can
@@ -293,21 +305,21 @@ plug-in by typing `srun --help`.
 
 The [EAR configuration file](www.example.org) supports the specification of *EAR authorized users*,
 who can ask for a more privileged submission options. The most relevant ones are the possibility
-to ask for a specific optimisation policy and a specific CPU frequency. Contact
-with sysadmin or helpdesk team to become an authorized user.
+to ask for a specific optimisation policy and a specific CPU frequency.
+
+> Contact with the sys admin or helpdesk team to become an authorized user.
 
 - The `--ear-policy=policy_name` flag asks for _policy_name_ policy. Type `srun --help` to see policies currently installed in your system.
 - The `--ear-cpufreq=value` (_value_ must be given in kHz) asks for a specific CPU frequency.
 
 ## GPU frequency selection
 
-EAR version 3.4 and upwards supports GPU monitoring for NVIDIA devices from the
-point of view of the application and node monitoring. GPU frequency optimization
-is not yet supported. **Authorized** users can ask for a specific GPU frequency
-by setting the `SLURM_EAR_GPU_DEF_FREQ` environment variable, giving the desired
-GPU frequency expressed in kHz.
+EAR **version 3.4 and upwards** supports GPU monitoring for NVIDIA devices from the point of view of the application and node monitoring.
+GPU frequency optimization is not supported yet.
+**Authorized** users can ask for a specific GPU frequency by setting the `SLURM_EAR_GPU_DEF_FREQ` environment variable, giving the desired GPU frequency expressed in kHz.
 Only one frequency for all GPUs is now supported.
-Contact with sysadmin or helpdesk team to become an authorized user.
+
+> Contact with sys admin or helpdesk team to become an authorized user.
 
 To see the list of available frequencies of the GPU you will work on, you can type the following command:
 ```