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https://github.com/rapidsai/jupyterlab-nvdashboard

A JupyterLab extension for displaying dashboards of GPU usage.
https://github.com/rapidsai/jupyterlab-nvdashboard

Last synced: about 2 months ago
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A JupyterLab extension for displaying dashboards of GPU usage.

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README 

        
# JupyterLab NVdashboard



NVDashboard is a JupyterLab extension for displaying GPU usage dashboards. It enables JupyterLab users to visualize system hardware metrics within the same interactive environment they use for development. Supported metrics include:



- GPU-compute utilization

- GPU-memory consumption

- PCIe throughput

- NVLink throughput



## Demo



![JupyterLab-nvdashboard Demo](https://raw.githubusercontent.com/rapidsai/jupyterlab-nvdashboard/HEAD/docs/_images/screencast1.gif)



## Table of Contents



- [New Features](#new-features)

  - [Brush for Time Series Charts](#brush-for-time-series-charts)

  - [Synced Tooltips](#synced-tooltips)

  - [Theme Compatibility](#theme-compatibility)

- [Version Compatibility](#version-compatibility)

- [Requirements](#requirements)

- [Installation](#installation)

- [Troubleshoot](#troubleshoot)

- [Contributing](#contributing-developers-guide)

- [Future Improvements](#future-improvements)



## New Features



JupyterLab-nvdashboard v4 brings a host of new features, improved backend architecture, and enhanced frontend components for an even better user experience.

Explore the exciting updates below.



### Brush for Time Series Charts



Introducing a powerful brushing feature for time series charts. Users can easily inspect past events by selecting a specific time range, providing more granular control over data exploration.



![JupyterLab-nvdashboard Demo1](https://raw.githubusercontent.com/rapidsai/jupyterlab-nvdashboard/HEAD/docs/_images/screencast2.gif)



### Synced Tooltips



For pages with multiple charts, JupyterLab-nvdashboard now offers synchronized tooltips for timestamps across all charts. This feature enhances the user's ability to analyze data cohesively and understand relationships between different data points.



![JupyterLab-nvdashboard Demo4](https://raw.githubusercontent.com/rapidsai/jupyterlab-nvdashboard/HEAD/docs/_images/screenshot3.png)



### Theme Compatibility



Seamless integration with JupyterLab themes is now a reality. The extension adapts its colors and aesthetics based on whether the user is in a light or dark theme, ensuring a consistent and visually appealing experience.



#### Light Theme



![JupyterLab-nvdashboard Demo3](https://raw.githubusercontent.com/rapidsai/jupyterlab-nvdashboard/HEAD/docs/_images/screenshot2.png)



#### Dark Theme



![JupyterLab-nvdashboard Demo2](https://raw.githubusercontent.com/rapidsai/jupyterlab-nvdashboard/HEAD/docs/_images/screenshot1.png)



## Version Compatibility



JupyterLab-nvdashboard v4 is designed exclusively for JupyterLab v4 and later versions. To ensure continued support for JupyterLab v3 users, we will maintain the previous version separately (branch-0.9).



## Requirements



- JupyterLab >=4

- pynvml

- psutil



## Installation



### Conda



```bash

# nightly version (for jupyterlab>=4)

conda install -c rapidsai-nightly -c conda-forge jupyterlab-nvdashboard



# stable version (for jupyterlab<4)

conda install -c rapidsai -c conda-forge jupyterlab-nvdashboard

```



### PyPI



```bash

# nightly version (for jupyterlab>=4)

pip install --extra-index-url https://pypi.anaconda.org/rapidsai-wheels-nightly/simple --pre jupyterlab_nvdashboard



# stable version (for jupyterlab<4)

pip install jupyterlab_nvdashboard

```



## Troubleshoot



If you are seeing the frontend extension, but it is not working, check

that the server extension is enabled:



```bash

jupyter server extension list

```



If the server extension is installed and enabled, but you are not seeing

the frontend extension, check the frontend extension is installed:



```bash

jupyter labextension list

```



## Contributing Developers Guide



For more details, check out the [contributing guide](./CONTRIBUTING.md).



## Future Improvements



While we've introduced a range of exciting features in this release, we understand that there are always opportunities for improvement. We have noted a request to add cell execution markers to the charts. Due to the complexities associated with asynchronous cells, we have decided to defer this feature to a future update. Rest assured, we will explore this enhancement in subsequent releases.