nvstatsrecorder 0.0.1

NVStatsRecorder

NVStatsRecorder

Simple Python utilities to instrument NVIDIA GPUs, designed to work directly from within Jupyter Notebooks requiring minimal system utilities.

Usage

Installing

pip install nvstatsrecorder

For TensorFlow 2.0 (Keras)

You can easily instrument your TF 2.0 (Keras) model training, if you are using model.fit(). Otherwise, view the next section if you are using custom training loops.

Example

from nvstatsrecorder.callbacks import NVStats, NVLinkStats

nv_stats = NVStats(gpu_index=0, interval=1)
nvlink_stats = NVLinkStats("jovyan", gpus=[0,1,2,3])

model.fit(train_dataset,epochs=2,
          callbacks=[nv_stats, nvlink_stats])

gpu_data = nv_stats.data
nvlink_data = nvlink_stats.data

# you can also access the internal recorder object

nv_stats_recorder = nv_stats.recorder
nvlink_stats_recorder = nvlink_stats.recorder

For any Python code

You can manually start and stop NVStatsRecorder or NVLinkStatsRecorder to instrument any Python code that uses GPU (e.g. PyTorch, MXNet, PyCUDA etc.)

Example

from nvstatsrecorder.recorders import NVStatsRecorder, NVLinkStatsRecorder

# initialize recorders
nv_stats_recorder = NVStatsRecorder(gpu_index=0)
nvlink_stats_recorder = NVLinkStatsRecorder(SUDO_PASSWORD, gpus=[0,1,2,3])

# start recorders
nv_stats_recorder.start(interval=1)
nvlink_stats_recorder.start(interval=1)

# run your code here

# stop recorders
nv_stats_recorder.stop()
nvlink_stats_recorder.stop()

# get data from recorders
gpu_data = nv_stats_recorder.get_data()
nvlink_data = nvlink_stats_recorder.get_data()

Plotting Graphs

nv_stats_recorder.plot_gpu_util(smooth=3)
nvlink_stats_recorder.plot_nvlink_traffic(smooth=3)

Development

# build pip wheel and install
python3 setup.py sdist bdist_wheel
pip install dist/nvstatsrecorder-*-py3-none-any.whl

Support

• Core Maintainer: Timothy Liu (tlkh)
• This is not an official NVIDIA product!
• The website, its software and all content found on it are provided on an “as is” and “as available” basis. NVIDIA/NVAITC does not give any warranties, whether express or implied, as to the suitability or usability of the website, its software or any of its content. NVIDIA/NVAITC will not be liable for any loss, whether such loss is direct, indirect, special or consequential, suffered by any party as a result of their use of the libraries or content. Any usage of the libraries is done at the user’s own risk and the user will be solely responsible for any damage to any computer system or loss of data that results from such activities.
• Please open an issue if you encounter problems or have a feature request