wattameter 0.8.0

Python package for monitoring and recording power usage, energy consumption, and performance metrics from hardware components such as GPUs and CPUs

wattameter is a Python package for monitoring and recording power usage over time, among other metrics. It enables time series data collection on hardware components such as CPUs and GPUs.

Current Features

• Track power usage for CPU (using RAPL) and GPU (using nvidia-ml-py)
• Track GPU utilization and temperature
• Periodically log time series data to file
• Customizable logging and output options
• Command-line interface for easy usage
• Integration with SLURM for HPC environments

Installation

You can install wattameter via pip:

pip install wattameter

Optional extras

Some features (notably the post-processing utilities that use pandas) are optional and not required for the core runtime. To enable post-processing functionality, install the optional extra:

pip install wattameter[postprocessing]
# or just
pip install pandas

Usage

As a Python module

from wattameter import Tracker
from wattameter.readers import NVMLReader

tracker = Tracker(
    reader=NVMLReader((Power,)),
    dt_read=0.1,  # Time interval for reading power data (seconds)
    freq_write=600,  # Frequency (# reads) for writing power data to file
    output="power_log.txt",
)
tracker.start()
# ... your code ...
tracker.stop()

# ... or ...

with Tracker(
    reader=NVMLReader((Power,)),
    dt_read=0.1,
    freq_write=600,
    output="power_log.txt",
) as tracker:
    # ... your code ...

Command-line interface

wattameter --tracker 0.1,nvml-power,rapl --tracker 1.0,nvml-util --suffix test --id 0 --freq-write 600 --log-level info

Option	Short	Default	Description
--tracker		0.1,nvml-power,rapl	Tracker specification: dt_read,metric1,metric2,... where dt_read is the time interval in seconds between readings. Available metrics: rapl (CPU energy), nvml-energy (GPU energy), nvml-power (GPU power), nvml-temp (GPU temperature), nvml-util (GPU utilization), nvml-nvlink (GPU NVLink throughput). Can be specified multiple times to create multiple trackers with different configurations.
--suffix	-s	None	Suffix for output files
--id	-i	UUID	Identifier for the experiment
--freq-write	-f	3600	Frequency (# reads) for writing data to file
--log-level	-l	warning	Logging level: debug, info, warning, error, critical
--help	-h		Show the help message and exit

Command-line interface with SLURM

For usage within SLURM jobs, we recommend using our utility functions start_wattameter and stop_wattameter in slurm.sh. Follow the example examples/slurm.sh, i.e.,

# In a Python environment with wattameter installed,
# load wattameter slurm utilities
WATTAPATH=$(python -c 'import wattameter; import os; print(os.path.dirname(wattameter.__file__))')
source "${WATTAPATH}/utils/slurm.sh"

# Run wattameter on all nodes
start_wattameter

# Input your job commands here
# ...

# Stop wattameter on all nodes
stop_wattameter

All options are the same as the regular command-line interface. The script will automatically handle the output file naming based on the provided SLURM_JOB_ID and node information.

Contributing

Contributions are welcome! Please open issues or submit pull requests.

Documentation

The API documentation is available at https://nrel.github.io/WattAMeter/.

License

See the LICENSE file for details.

---

NREL Software Record number: SWR-25-101