Status of issues
Features, bugs, and enhancements.
The ESMF-Profiler project is designed to take trace binary output and display it in a web based GUI.
To collect a binary trace, set the environment variables to the values below:
export ESMF_RUNTIME_PROFILE=ON
export ESMF_RUNTIME_PROFILE_OUTPUT="BINARY SUMMARY"
-
Clone the latest stable branch from the esmf-profiler repository.
-
cd into the appliction path
cd esmf-profiler
- Ensure that the
install_dependencies.sh
andinstall.sh
have executable permissions
chmod +x ./install_dependencies.sh
chmod +x ./install.sh
- Execute both scripts as shown below. A
venv
folder will be created on success.
./install_dependencies.sh && ./install.sh
- Activate the virtual environment.
source ./venv/bin/activate
- For pre-release, install the esmf-profiler using pip editable install. Running tests require access to PyPi Public Repositories. This step is optional, but encouraged. Some HPC platforms do not have open internet access, so will not be able to install the tests.
pip install -e . or pip install -e .[test] // to run tests
- Confirm the installation was successful. If so, you should now be able to type
esmf-profiler
into your terminal and see the help output.
python -m pytest // optional, to run tests
esmf-profiler
ℹ️ If using C-Shell, deactivate then reactivate the virtual environment to run the applicication.
A Dockerfile is included in the repository to allow users using Docker to install the application with ease.
-
Clone the latest stable branch from the esmf-profiler repository.
-
cd into the appliction path
cd esmf-profiler
- Build the image
docker build -t esmf-profiler-image .
- Run the application in the image. For example, assuming your binary traces are in
./traces
docker run -it -v $(pwd)/traces:/home/traces esmf-profiler-image esmf-profiler -t /home/traces -n 'profilename' -o /home/traces/output
This will spin up an esmf-profiler-image and mount ./traces
from client to host.
Here, output is being directed to /home/traces/output
.
esmf-profiler
command has your client folder as it's root (./traces
in the example). Otherwise, the output will not persist to your client machine after the application has run.
You can see the help menu displayed below after installation by running ```esmf-profiler``` with no arguments.
usage: esmf-profiler [-h] -t TRACEDIR -n NAME -o OUTDIR [-p PUSH] [-v] [-s]
ESMF Profiler
optional arguments:
-h, --help show this help message and exit
-t TRACEDIR, --tracedir TRACEDIR
directory containing the ESMF trace
-n NAME, --name NAME name to use for the generated profile
-o OUTDIR, --outdir OUTDIR
path to output directory
-p PUSH, --push PUSH git url of remote repository where to push profile
-v, --verbose enable verbose output
-s, --serve start a local server to host the profile results
esmf-profiler -t ./fresh_traces -n "build_abc123" -o "output" -s
This is the most common way to use the profiler. It requires some simple user permissions on the server you're running the application on.
You're telling the application to:
- -t ./freshtraces The traces to run on are contained in fresh_traces, a subdirectory of the current working directory
- -n "build_abc123 Name the output (the profile) "build_abc123". This will be used for titles, directories, links, etc. in the GUI and file structure.
- -o "output" Send the output to output a directory that will be created (if no already exists) in the current working directory. All output will be sent there.
- -s On success, start an ultra-light-weight python native web server at 0.0.0.0:8000
esmf-profiler -t ./fresh_traces -n "build_abc123" -o "output" -p '[email protected]:user_name/repo_name.git'
This example will run the processing work locally as the first example, but then publish the results to the repository at [email protected]:user_name/repo_name.git
.
To view the profile on GitHub.io, you need to explicitly turn on "GitHub Pages" within the target repository. Refer to the Quickstart for Github Pages for details on how to turn on "Pages" within your repository.
docker build -t esmf-profiler-image .
docker run -it -v $(pwd)/traces:/home/traces esmf-profiler-image esmf-profiler -t /home/traces -n 'my_profile' -o /home/traces/output
This example utitilizes the [Dockerfile] for those leveraging Docker.
The image is built first, then <current_working_directory>/traces
is mounted to /home/traces
on the virtual machine.
Commands are the same for local and docker installations.
Here, we're telling the application to:
- -t ./freshtraces The traces to run on are contained in /home/traces (locally, $pwd and traces)
- -n "build_abc123 Name the output (the profile) "my_profile".
- -o "/home/traces/output The target for the output of the applications. **This must be a directory mounted via the
docker run
command as discussed above. Otherwise, the results will not persists after the docker run command has completed.
ℹ️ All dependencies are installed using any of the installation methods in Quick Start section. This section is primarly for reference and historical purposes.
There are some package managers that install Babeltrace2.
https://babeltrace.org/#bt2-get
However, you need to make sure the Python bindings are included.
Prereqs:
- glibc-2.0 (Ubuntu:
sudo apt-get install libglib2.0
) - swig (Ubuntu:
sudo apt-get install swig
)
Download: https://www.efficios.com/files/babeltrace/babeltrace2-2.0.4.tar.bz2
Note: Babeltrace2 appears to require the GNU compiler >9.0 - there are failures with Intel.
cd /path/to/babeltrace2-2.0.4
./configure --prefix=/path/to/babeltrace2/INSTALL/2.0.4 --enable-python-bindings --enable-python-plugins --disable-debug-info --enable-compile-warnings=no
make -j4
make install
# set up PYTHONPATH so that the bt2 module is available
export PYTHONPATH=/path/to/babeltrace2/INSTALL/2.0.4/lib/python3.5/site-packages
# if installed in non-standard place, you need to set LD_LIBRARY_PATH:
export LD_LIBRARY_PATH=/path/to/babeltrace2/INSTALL/2.0.4/lib
module load gnu/9.1.0 python/3.7.9
SWIG is needed for the build process and is not in the default Cheyenne PATH. Download: http://prdownloads.sourceforge.net/swig/swig-4.0.2.tar.gz
./configure --prefix=/glade/u/home/dunlap/bt/INSTALL/swig-4.0.2
make
make install
export PATH=/glade/u/home/dunlap/bt/INSTALL/swig-4.0.2/bin:$PATH
Install babeltrace2
cd /path/to/babeltrace2-2.0.4
./configure --prefix=/glade/u/home/dunlap/bt/INSTALL/babeltrace2-2.0.4 --enable-python-bindings --enable-python-plugins --disable-debug-info
make -j6
make install
# set LD_LIBRARY_PATH so Python3 can find the dynamic library
export LD_LIBRARY_PATH=/glade/u/home/dunlap/bt/INSTALL/babeltrace2-2.0.4/lib:$LD_LIBRARY_PATH
https://docs.pytest.org/en/6.2.x/ https://code.visualstudio.com/docs/python/testing http://www.swig.org/Doc4.0/SWIGDocumentation.html