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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 21 hours ago
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A JupyterLab extension for displaying dashboards of GPU usage.
- Host: GitHub
- URL: https://github.com/rapidsai/jupyterlab-nvdashboard
- Owner: rapidsai
- License: bsd-3-clause
- Created: 2019-08-12T15:22:10.000Z (over 5 years ago)
- Default Branch: branch-0.13
- Last Pushed: 2024-11-27T14:37:21.000Z (16 days ago)
- Last Synced: 2024-12-05T11:05:07.760Z (8 days ago)
- Language: TypeScript
- Size: 13.4 MB
- Stars: 614
- Watchers: 19
- Forks: 78
- Open Issues: 36
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
Awesome Lists containing this project
- awesome-jupyter-resources - GitHub - 42% open · ⏱️ 23.06.2022): (JupyterLab扩展)
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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
## 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.
### 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.
### 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
#### Dark Theme
## 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.