Tracks computational resources of a process and its child processes, most prominently GPU RAM, as well as RAM and compute time.
Project description
Description
The gpu_tracker package provides a Tracker class and a commandline-interface that tracks (profiles) the usage of compute time, maximum RAM, and maximum GPU RAM. The compute time is a measurement of the real time taken by the task as opposed to the CPU-utilization time. The GPU tracking is for Nvidia GPUs and uses the nvidia-smi command, assuming the Nvidia drivers have been installed. Computational resources are tracked throughout the duration of a context manager or the duration of explicit calls to the start() and stop() methods of the Tracker class. The gpu-tracker command-line interface alternatively tracks the computational-resource-usage of an arbitrary shell command.
Documentation
The complete documentation for the gpu_tracker package, including tutorials, can be found here.
Installation
Requires python 3.10 and above.
Install on Linux, Mac OS X
python3 -m pip install gpu-tracker
Install on Windows
py -3 -m pip install gpu-tracker
PyPi
See our PyPi page here.
Questions, Feature Requests, and Bug Reports
Please submit any questions or feature requests you may have and report any potential bugs/errors you observe on our GitHub issues page.
GitHub Repository
Code is available on GitHub: https://github.com/MoseleyBioinformaticsLab/gpu_tracker.
Project details
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