improve readability and grammer of some sentences

Author: cerlane

.github/actions/spelling/allow.txt

@@ -93,7 +93,7 @@ Piz
 Plesset
 Podladchikov
 Pulay
-Pypi
+PyPi
 RCCL
 RDMA
 ROCm

docs/software/gssr/containers.md

@@ -30,9 +30,9 @@ RUN pip install gssr
 # Install your application and dependencies as required
 ...
 ```
-As you can see from the above example, gssr can easily be installed with a `RUN pip install gssr` command. Your application and dependencies should be written where the `...` is.
+As you can see from the above example, gssr can easily be installed with a `RUN pip install gssr` command. 
 
-Once your `ContainerFile` is ready, you can build it on any Alps platform with the following commands to create a container with label `mycontainer`.
+Once your `ContainerFile` is ready, you can build it on any Alps platforms with the following commands to create a container with label `mycontainer`.
 
 ```bash
 srun -A {groupID} --pty bash
@@ -47,7 +47,7 @@ Now you should have a sqsh file of your container. Please note that you should r
 
 ## Create CSCS configuration for Container
 
-Now you only need to tell CSCS container engine solution where your container is and how you would like to run it. To do so, you will have to create a`{label}.toml` file in your `$HOME/.edf` directory.
+The next step is to tell CSCS container engine solution where your container is and how you would like to run it. To do so, you will have to create a`{label}.toml` file in your `$HOME/.edf` directory.
 
 ### Example of a `mycontainer.toml` file
 ```
@@ -95,11 +95,11 @@ Now you are ready to submit your sbatch file to slurm with `sbatch` command.
 
 ## Analyze the output
 
-Once your job successfully concluded. You should find a folder named `profile_out_{slurm_jobid}` where `gssr` json output is in. To generate output for analysis.
+Once your job successfully concluded, you should find a folder named `profile_out_{slurm_jobid}` where `gssr` json outputs are in.
 
-To do so, you can do so interactively within your container where `gssr` is installed.
+To analyze the outputs, you can do so interactively within any containers where `gssr` is installed, e.g., `mycontainer` we have in this guide.
 
-To get an interactive session of our container
+To get an interactive session of this container:
 
 ```
 srun -A groupname --environment=mycontainer --pty bash

docs/software/gssr/quickstart.md

@@ -1,55 +1 @@
-[](){#ref-gssr-quickstart}
-# gssr - Quickstart Guide
-
-## Installation
-
-### From Pypi 
-
-`gssr` can be easily installed as follows.:
-
-    pip install gssr
-
-### From GitHub Source
-
-To install directly from the source:
-
-    pip install git+https://github.com/eth-cscs/GPU-saturation-scorer.git
-
-To install from a specific branch, e.g. the development branch, from the source:
-
-    pip install git+https://github.com/eth-cscs/GPU-saturation-scorer.git@dev
-
-To install a specific release tag, e.g. gssr-v0.3, from the source:
-
-    pip install git+https://github.com/eth-cscs/[email protected]
-
-## Profile
-
-### Example
-
-If you are submitting a batch job and the command you are executing is:
-
-    srun python test.py
-
-The corresponding srun command should be modified as follows.:
-
-    srun gssr profile -wrap="python abc.py"
-
-* The `gssr` option to run is `profile`
-* The `"--wrap"` flag will wrap the command that you would like to run
-* The default output directory is `profile_out_{slurm_job_id}`
-* A label to the output data can be set with the `-l` flag
-
-## Analyze
-
-### Metric Output
-The profiled output can be analysed as follows.:
-
-    gssr analyze -i ./profile_out
-
-### PDF File Output with Plots
-
-    gssr analyze -i ./profile_out --report
-
-A/Multiple PDF report(s) will be generated.
-
+### From PyPi