perun
Calculates the energy consumption of Python scripts by sampling usage statistics from your hardware components.
https://github.com/helmholtz-ai-energy/perun
Category: Consumption
Sub Category: Computation and Communication
Keywords
benchmarking command-line-tool energy energy-monitor hpc mpi python
Keywords from Contributors
parallel
Last synced: about 21 hours ago
JSON representation
Repository metadata
Perun is a Python package that measures the energy consumption of your applications.
- Host: GitHub
- URL: https://github.com/helmholtz-ai-energy/perun
- Owner: Helmholtz-AI-Energy
- License: bsd-3-clause
- Created: 2022-08-10T13:53:19.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2025-11-24T22:28:46.000Z (30 days ago)
- Last Synced: 2025-11-29T17:44:10.673Z (25 days ago)
- Topics: benchmarking, command-line-tool, energy, energy-monitor, hpc, mpi, python
- Language: Python
- Homepage: https://perun.readthedocs.io/en/latest/
- Size: 652 KB
- Stars: 88
- Watchers: 4
- Forks: 6
- Open Issues: 20
- Releases: 38
-
Metadata Files:
- Readme: README.rst
- Changelog: CHANGELOG.md
- License: LICENSE
- Citation: CITATION.cff
README.rst
.. image:: https://raw.githubusercontent.com/Helmholtz-AI-Energy/perun/main/docs/images/full_logo.svg
| |fair-software| |openssf| |zenodo| |license| |docs|
| |pypi-version| |python-version| |pypi-downloads| |black| |codecov|
.. |fair-software| image:: https://img.shields.io/badge/fair--software.eu-%E2%97%8F%20%20%E2%97%8F%20%20%E2%97%8F%20%20%E2%97%8F%20%20%E2%97%8F-green
:target: https://fair-software.eu
.. |openssf| image:: https://bestpractices.coreinfrastructure.org/projects/7253/badge
:target: https://bestpractices.coreinfrastructure.org/projects/7253
.. |zenodo| image:: https://zenodo.org/badge/523363424.svg
:target: https://zenodo.org/badge/latestdoi/523363424
.. |pypi-version| image:: https://img.shields.io/pypi/v/perun
.. |pypi-downloads| image:: https://img.shields.io/pypi/dm/perun
.. |black| image:: https://img.shields.io/badge/code%20style-black-000000.svg
:target: https://github.com/psf/black
.. |codecov| image:: https://codecov.io/gh/Helmholtz-AI-Energy/perun/graph/badge.svg?token=9O6FSJ6I3G
:target: https://codecov.io/gh/Helmholtz-AI-Energy/perun
.. |python-version| image:: https://img.shields.io/badge/Python-3.9+-blue.svg
:target: https://www.python.org/downloads/
.. |license| image:: https://img.shields.io/badge/License-BSD_3--Clause-blue.svg
:target: https://opensource.org/licenses/BSD-3-Clause
.. |docs| image:: https://readthedocs.org/projects/perun/badge/?version=latest
:target: https://perun.readthedocs.io/en/latest/?badge=latest
===============================================================
*perun* is a Python package that calculates the energy consumption of Python scripts by sampling usage statistics from your Intel, Nvidia or AMD hardware components. It can handle MPI applications, gather data from hundreds of nodes, and accumulate it efficiently. *perun* can be used as a command-line tool or as a function decorator in Python scripts.
Check out the `docs `_ or a working `example `_!
Key Features
------------
- Measures energy consumption of Python scripts and binaries, supporting different hardware configurations
- Capable of handling MPI applications, gathering data from hundreds of nodes efficiently
- Monitor individual functions using decorators
- Tracks energy usage of the application over multiple executions
- Easy to benchmark applications and functions
- Experimental!: Can monitor any non-distributed command line application
-----------------------------------------------------------------
Quick Start
-----------
Installation
^^^^^^^^^^^^
From PyPI:
.. code:: console
$ pip install perun
Extra dependencies like *nvidia-smi*, *rocm-smi* and *mpi4py* can be installed using pip as well:
.. code:: console
$ pip install perun[nvidia, rocm, mpi]
From Github:
.. code:: console
$ pip install git+https://github.com/Helmholtz-AI-Energy/perun
Command Line
^^^^^^^^^^^^
To use *perun* as a command-line tool:
.. code:: console
$ perun monitor path/to/your/script.py [args]
*perun* will output two files, an HDF5 style containing all the raw data that was gathered, and a text file with a summary of the results.
.. code:: text
PERUN REPORT
App name: finetune_qa_accelerate
First run: 2023-08-15T18:56:11.202060
Last run: 2023-08-17T13:29:29.969779
RUN ID: 2023-08-17T13:29:29.969779
+-----------+------------------------+-----------+-------------+--------------+-------------+-------------+-------------+---------------+-------------+
| Round # | Host | RUNTIME | ENERGY | CPU_POWER | CPU_UTIL | GPU_POWER | GPU_MEM | DRAM_POWER | MEM_UTIL |
+===========+========================+===========+=============+==============+=============+=============+=============+===============+=============+
| 0 | hkn0432.localdomain | 995.967 s | 960.506 kJ | 231.819 W | 3.240 % | 702.327 W | 55.258 GB | 29.315 W | 0.062 % |
| 0 | hkn0436.localdomain | 994.847 s | 960.469 kJ | 235.162 W | 3.239 % | 701.588 W | 56.934 GB | 27.830 W | 0.061 % |
| 0 | All | 995.967 s | 1.921 MJ | 466.981 W | 3.240 % | 1.404 kW | 112.192 GB | 57.145 W | 0.061 % |
The application has been run 7 times. In total, it has used 3.128 kWh, released a total of 1.307 kgCO2e into the atmosphere, and you paid 1.02 € in electricity for it.
Binary support (experimental)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
*perun* is capable of monitoring simple applications written in other languages:
.. code:: console
$ perun monitor --binary path/to/your/executable [args]
Function Monitoring
^^^^^^^^^^^^^^^^^^^
Using a function decorator
.. code:: python
import time
from perun import monitor
@monitor()
def main(n: int):
time.sleep(n)
After running with ``perun monitor``, the report will contain:
.. code:: text
Monitored Functions
+-----------+----------------------------+---------------------+------------------+--------------------+------------------+-----------------------+
| Round # | Function | Avg Calls / Rank | Avg Runtime | Avg Power | Avg CPU Util | Avg GPU Mem Util |
+===========+============================+=====================+==================+====================+==================+=======================+
| 0 | main | 1 | 993.323±0.587 s | 964.732±0.499 W | 3.244±0.003 % | 35.091±0.526 % |
| 0 | prepare_train_features | 88 | 0.383±0.048 s | 262.305±19.251 W | 4.541±0.320 % | 3.937±0.013 % |
| 0 | prepare_validation_features| 11 | 0.372±0.079 s | 272.161±19.404 W | 4.524±0.225 % | 4.490±0.907 % |
MPI
^^^
*perun* is compatible with MPI applications using ``mpi4py``:
.. code:: console
$ mpirun -n 8 perun monitor path/to/your/script.py
Docs
----
See the `documentation `_ or `examples `_ for more details.
Citing perun
------------
If you found *perun* useful, please cite the conference paper:
::
Gutiérrez Hermosillo Muriedas, J.P., Flügel, K., Debus, C., Obermaier, H., Streit, A., Götz, M.:
perun: Benchmarking Energy Consumption of High-Performance Computing Applications.
In: Cano, J., Dikaiakos, M.D., Papadopoulos, G.A., Pericàs, M., and Sakellariou, R. (eds.)
Euro-Par 2023: Parallel Processing. pp. 17–31. Springer Nature Switzerland, Cham (2023).
https://doi.org/10.1007/978-3-031-39698-4_2
.. code-block:: bibtex
@InProceedings{10.1007/978-3-031-39698-4_2,
author="Guti{\'e}rrez Hermosillo Muriedas, Juan Pedro
and Fl{\"u}gel, Katharina
and Debus, Charlotte
and Obermaier, Holger
and Streit, Achim
and G{\"o}tz, Markus",
editor="Cano, Jos{\'e}
and Dikaiakos, Marios D.
and Papadopoulos, George A.
and Peric{\`a}s, Miquel
and Sakellariou, Rizos",
title="perun: Benchmarking Energy Consumption of High-Performance Computing Applications",
booktitle="Euro-Par 2023: Parallel Processing",
year="2023",
publisher="Springer Nature Switzerland",
address="Cham",
pages="17--31",
isbn="978-3-031-39698-4"
}
Citation (CITATION.cff)
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: perun
message: 'If you use this software, please cite the paper.'
type: software
authors:
- given-names: Juan Pedro
family-names: Gutiérrez Hermosillo Muriedas
email: juan.muriedas@kit.edu
affiliation: >-
Scientific Computing Center, Karlsruhe Institute of Technology
orcid: 'https://orcid.org/0000-0001-8439-7145'
repository-code: 'https://github.com/Helmholtz-AI-Energy/perun'
repository: 'https://perun.readthedocs.io/en/latest/?badge=latest'
keywords:
- Python
- Energy
- Benchmarking
- HPC
- MPI
license: BSD-3-Clause
preferred-citation:
type: conference-paper
authors:
- given-names: Juan Pedro
family-names: Gutiérrez Hermosillo Muriedas
email: juan.muriedas@kit.edu
affiliation: Karlsruhe Institute of Technology
orcid: 'https://orcid.org/0000-0001-8439-7145'
- given-names: Katharina
family-names: Flügel
- given-names: Charlotte
family-names: Debus
- given-names: Holger
family-names: Obermaier
- given-names: Achim
family-names: Streit
- given-names: Markus
family-names: Götz
title: >-
perun: Benchmarking Energy Consumption of High-Performance Computing
Applications
year: 2023
collection-title: 'Euro-Par 2023: Parallel Processing'
collection-doi: 10.1007/978-3-031-39698-4
doi: 10.1007/978-3-031-39698-4_2
conference:
name: >-
29th International European Conference on Parallel and Distributed
Computing
date-start: "2023-08-28"
date-end: "2017-09-01"
Owner metadata
- Name: Helmholtz AI Energy
- Login: Helmholtz-AI-Energy
- Email: consultant-helmholtz.ai@kit.edu
- Kind: organization
- Description:
- Website: https://www.helmholtz.ai/
- Location: Karlsruhe, Germany
- Twitter:
- Company:
- Icon url: https://avatars.githubusercontent.com/u/72967658?v=4
- Repositories: 9
- Last ynced at: 2023-03-09T07:45:42.630Z
- Profile URL: https://github.com/Helmholtz-AI-Energy
GitHub Events
Total
- Create event: 19
- Release event: 4
- Issues event: 17
- Watch event: 28
- Delete event: 15
- Issue comment event: 31
- Push event: 103
- Pull request review event: 3
- Pull request event: 35
- Fork event: 1
Last Year
- Create event: 13
- Release event: 2
- Issues event: 15
- Watch event: 24
- Delete event: 7
- Issue comment event: 24
- Push event: 75
- Pull request review event: 1
- Pull request event: 24
Committers metadata
Last synced: 2 days ago
Total Commits: 206
Total Committers: 11
Avg Commits per committer: 18.727
Development Distribution Score (DDS): 0.301
Commits in past year: 16
Committers in past year: 5
Avg Commits per committer in past year: 3.2
Development Distribution Score (DDS) in past year: 0.375
| Name | Commits | |
|---|---|---|
| Gutiérrez Hermosillo Muriedas, Juan Pedro | j****m@g****m | 144 |
| github-actions | a****n@g****m | 16 |
| pre-commit-ci[bot] | 6****] | 14 |
| github-actions | g****s@g****m | 11 |
| semantic-release | s****e | 10 |
| dependabot[bot] | 4****] | 6 |
| StepSecurity Bot | b****t@s****o | 1 |
| Markus Goetz | m****n@g****m | 1 |
| JZschache | j****e@p****e | 1 |
| Andreas Fehlner | f****r@a****e | 1 |
| io3047@kit.edu | i****7@u****n | 1 |
Committer domains:
- github.com: 2
- uc2n994.localdomain: 1
- arcor.de: 1
- posteo.de: 1
- stepsecurity.io: 1
Issue and Pull Request metadata
Last synced: 8 days ago
Total issues: 67
Total pull requests: 158
Average time to close issues: 4 months
Average time to close pull requests: 14 days
Total issue authors: 14
Total pull request authors: 7
Average comments per issue: 0.61
Average comments per pull request: 0.34
Merged pull request: 126
Bot issues: 2
Bot pull requests: 62
Past year issues: 15
Past year pull requests: 32
Past year average time to close issues: 12 days
Past year average time to close pull requests: 18 days
Past year issue authors: 5
Past year pull request authors: 5
Past year average comments per issue: 0.93
Past year average comments per pull request: 0.97
Past year merged pull request: 20
Past year bot issues: 0
Past year bot pull requests: 10
Top Issue Authors
- JuanPedroGHM (51)
- Markus-Goetz (4)
- JZschache (1)
- aweissen1 (1)
- diligent-man (1)
- bom-bahadur (1)
- dependabot[bot] (1)
- janEbert (1)
- chrsigg (1)
- psteinb (1)
- yasintha91 (1)
- TomTheBear (1)
- pre-commit-ci[bot] (1)
- pfackeldey (1)
Top Pull Request Authors
- JuanPedroGHM (90)
- pre-commit-ci[bot] (45)
- dependabot[bot] (17)
- ram-from-tvl (2)
- andife (2)
- JZschache (1)
- step-security-bot (1)
Top Issue Labels
- enhancement (12)
- cx (6)
- bug (5)
- documentation (3)
- dependencies (2)
- Frontend:IO (1)
- Data Model (1)
- good first issue (1)
- Processing (1)
Top Pull Request Labels
- dependencies (16)
- documentation (2)
- cx (2)
Package metadata
- Total packages: 3
-
Total downloads:
- pypi: 380 last-month
- Total dependent packages: 1 (may contain duplicates)
- Total dependent repositories: 1 (may contain duplicates)
- Total versions: 143
- Total maintainers: 1
proxy.golang.org: github.com/Helmholtz-AI-Energy/perun
- Homepage:
- Documentation: https://pkg.go.dev/github.com/Helmholtz-AI-Energy/perun#section-documentation
- Licenses: bsd-3-clause
- Latest release: v0.9.0 (published 7 months ago)
- Last Synced: 2025-12-20T19:06:45.992Z (4 days ago)
- Versions: 44
- Dependent Packages: 0
- Dependent Repositories: 0
-
Rankings:
- Dependent packages count: 6.488%
- Average: 6.707%
- Dependent repos count: 6.926%
proxy.golang.org: github.com/helmholtz-ai-energy/perun
- Homepage:
- Documentation: https://pkg.go.dev/github.com/helmholtz-ai-energy/perun#section-documentation
- Licenses: bsd-3-clause
- Latest release: v0.9.0 (published 7 months ago)
- Last Synced: 2025-12-20T19:06:49.143Z (4 days ago)
- Versions: 44
- Dependent Packages: 0
- Dependent Repositories: 0
-
Rankings:
- Dependent packages count: 6.488%
- Average: 6.707%
- Dependent repos count: 6.926%
pypi.org: perun
Measure the energy used by your MPI+Python applications.
- Homepage: https://github.com/Helmholtz-AI-Energy/perun
- Documentation: https://perun.readthedocs.io
- Licenses: BSD 3-Clause License Copyright (c) 2022, Helmholtz AI Energy All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
- Latest release: 0.9.0 (published 7 months ago)
- Last Synced: 2025-12-20T19:06:44.828Z (4 days ago)
- Versions: 55
- Dependent Packages: 1
- Dependent Repositories: 1
- Downloads: 380 Last month
-
Rankings:
- Dependent packages count: 4.744%
- Stargazers count: 11.253%
- Average: 14.963%
- Downloads: 18.072%
- Forks count: 19.104%
- Dependent repos count: 21.642%
- Maintainers (1)
Dependencies
- black ^22.6.0 develop
- flake8 ^5.0.4 develop
- mypy ^0.971 develop
- pre-commit ^2.20.0 develop
- pytest ^5.2 develop
- PyYAML ^6.0
- click ^8.1.3
- h5py ^3.7.0
- mpi4py ^3.1.3
- py-cpuinfo ^8.0.0
- pyRAPL ^0.2.3
- pynvml ^11.4.1
- python ^3.9
- python-dotenv ^0.20.0
- actions/checkout v2 composite
- relekang/python-semantic-release master composite
- actions/checkout v3 composite
- actions/setup-python v4 composite
- sphinx-autoapi ==2.1.0
- sphinx-rtd-theme ==1.2.0
- Jinja2 ==3.1.2
- MarkupSafe ==2.1.3
- Pillow ==10.0.0
- certifi ==2023.5.7
- charset-normalizer ==3.1.0
- click ==8.1.3
- cmake ==3.26.4
- filelock ==3.12.2
- h5py ==3.9.0
- idna ==3.4
- lit ==16.0.6
- mpmath ==1.3.0
- networkx ==3.1
- numpy ==1.24.4
- nvidia-cublas-cu11 ==11.10.3.66
- nvidia-cuda-cupti-cu11 ==11.7.101
- nvidia-cuda-nvrtc-cu11 ==11.7.99
- nvidia-cuda-runtime-cu11 ==11.7.99
- nvidia-cudnn-cu11 ==8.5.0.96
- nvidia-cufft-cu11 ==10.9.0.58
- nvidia-curand-cu11 ==10.2.10.91
- nvidia-cusolver-cu11 ==11.4.0.1
- nvidia-cusparse-cu11 ==11.7.4.91
- nvidia-nccl-cu11 ==2.14.3
- nvidia-nvtx-cu11 ==11.7.91
- pandas ==2.0.3
- perun ==0.4.0
- psutil ==5.9.5
- py-cpuinfo ==5.0.0
- pynvml ==11.5.0
- python-dateutil ==2.8.2
- pytz ==2023.3
- requests ==2.31.0
- six ==1.16.0
- sympy ==1.12
- torch ==2.0.1
- torchvision ==0.15.2
- triton ==2.0.0
- typing_extensions ==4.7.1
- tzdata ==2023.3
- urllib3 ==2.0.3
Score: 13.028061489103237