nvgpu | NVIDIA GPU tools - monitoring on CLI & web app | GPU library

by rossumai Python Version: 0.10.0 License: MIT

X-Ray Key Features Code Snippets(3)Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | nvgpu Summary

nvgpu is a Python library typically used in Hardware, GPU, Deep Learning, Tensorflow applications. nvgpu has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install nvgpu' or download it from GitHub, PyPI.

It provides information about GPUs and their availability for computation. Often we want to train a ML model on one of GPUs installed on a multi-GPU machine. Since TensorFlow allocates all memory, only one such process can use the GPU at a time. Unfortunately nvidia-smi provides only a text interface with information about GPUs. This packages wraps it with an easier to use CLI and Python interface. It's a quick and dirty solution calling nvidia-smi and parsing its output. We can take one or more GPUs availabile for computation based on relative memory usage, ie. it is OK with Xorg taking a few MB. In addition we have a fancy table of GPU with more information taken by python binding to NVML. For easier monitoring of multiple machines it's possible to deploy agents (that provide the GPU information in JSON over a REST API) and show the aggregated status in a web application.

Support

Quality

Security

License

Reuse

Support

nvgpu has a low active ecosystem.

It has 75 star(s) with 20 fork(s). There are 10 watchers for this library.

It had no major release in the last 12 months.

There are 13 open issues and 10 have been closed. On average issues are closed in 542 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of nvgpu is 0.10.0

Quality

nvgpu has 0 bugs and 0 code smells.

Security

nvgpu has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

nvgpu code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

nvgpu is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

nvgpu releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

nvgpu saves you 108 person hours of effort in developing the same functionality from scratch.

It has 277 lines of code, 23 functions and 8 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed nvgpu and discovered the below as its top functions. This is intended to give you an instant insight into nvgpu implemented functionality, and help decide if they suit your requirements.

Return a response of the agents
Return machine status
Get the status of a device
Format a pandas table
Download the GPU status
Format reports to ansi format
Parse command line
Converts ANSI text to HTML
Create a pandas dataframe
List all available devices
Context manager
Download reports from the given hosts
Return a list of available gpu cores
Run a command and return the output
Return information about the GPUs
Get machine status
Parse command line arguments
Prints a pretty list of all the gpuses
Get all the agents

Get all kandi verified functions for this library.

nvgpu Key Features

No Key Features are available at this moment for nvgpu.

nvgpu Examples and Code Snippets

nvgpu,Usage examples

Python

Lines of Code : 42

License : Permissive (MIT)

Copy

# grab all available GPUs
CUDA_VISIBLE_DEVICES=$(nvgpu available)

# grab at most available GPU
CUDA_VISIBLE_DEVICES=$(nvgpu available -l 1)

$ nvgpu list
    status    type                 util.      temp.    MHz  users    since    pids    cmd
--  -

nvgpu,Installing as a service

Python

Lines of Code : 20

License : Permissive (MIT)

Copy

# create an unprivileged system user
sudo useradd -r nvgpu

sudo vi /etc/systemd/system/nvgpu-agent.service

sudo vi /etc/nvgpu.conf

AGENTS = [
         # direct access without using HTTP
         'self',
         'http://node01:1080',
         'htt

nvgpu,Web application with agents,Master

Python

Lines of Code : 8

License : Permissive (MIT)

Copy

# nvgpu_master.cfg
AGENTS = [
         'self', # node01 - master - direct access without using HTTP
         'http://node02:1080',
         'http://node03:1080',
         'http://node04:1080',
]

NVGPU_CLUSTER_CFG=/path/to/nvgpu_master.cfg FLASK_APP=

Community Discussions

Trending Discussions on nvgpu

nvidia-smi command not found on DJI Manifold 2G NVIDIA Jetson TX2

pip install --upgrade pip and pip install --upgrade setuptools both failed with error code 1

QUESTION

nvidia-smi command not found on DJI Manifold 2G NVIDIA Jetson TX2

Asked 2021-Dec-13 at 09:05

Upon running nvidia-smi through terminal, i am met with nvidia-smi command not found However, i am aware that jetpack 3.3 (the nvidia drivers) have already been installed. Has anyone encountered similar problems with Nvidia jetson tx2 ?

...

ANSWER

Answered 2021-Dec-09 at 19:41

I think that nvidia-smi is only available so far for NVIDIA discrete GPUs, but Jetsons have an integrated GPU (sharing physical memory with system).

You can find details about your GPU specs with deviceQuery utility in CUDA samples:

Source https://stackoverflow.com/questions/70283859

QUESTION

pip install --upgrade pip and pip install --upgrade setuptools both failed with error code 1

Asked 2021-Dec-06 at 08:48

i encountered errors with trying to upgrade pip, and its setup tools. Appended below are the errors.

pip install -upgrade pip failing

...

ANSWER

Answered 2021-Dec-06 at 08:48

I have had this issue before. pip requires the latest version of python to be working properly to work, however certain CPU architectures don't fully support it. you say your using an ARM based CPU which I think requires a different way of installing python. Pip will throw syntax errors when python is incompatible with your CPU arch. You may need to look into emulators or upgrading hardware.

Source https://stackoverflow.com/questions/70242603

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install nvgpu

You can install using 'pip install nvgpu' or download it from GitHub, PyPI.
You can use nvgpu like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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