https://github.com/iterait/dockerfiles

Iterait various public dockerfiles
https://github.com/iterait/dockerfiles

dockerfile dockerhub

Last synced: 11 months ago
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Iterait various public dockerfiles

• Host: GitHub
• URL: https://github.com/iterait/dockerfiles
• Owner: iterait
• License: other
• Created: 2018-09-06T11:58:08.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2024-04-08T08:22:10.000Z (almost 2 years ago)
• Last Synced: 2024-04-08T09:53:59.393Z (almost 2 years ago)
• Topics: dockerfile, dockerhub
• Language: Shell
• Size: 113 KB
• Stars: 3
• Watchers: 9
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# dockerfiles

[![Development Status](https://img.shields.io/badge/status-Regular-brightgreen.svg?style=flat)]()

[![Master Developer](https://img.shields.io/badge/master-Petr%20Bělohlávek-lightgrey.svg?style=flat)]()

This is a repository contaning the open-source docker images provided by Iterait a.s.

We use nvidia-docker instead of regular docker in order to enhance GPU support.

However, regular docker might be used as well.

## DockerHub

All built images are stored in [Iterait DockerHub](https://hub.docker.com/r/iterait/).

| CPU-only image                  | GPU enabled image               | Description                         |

| ------------------------------- | ------------------------------- | ----------------------------------- |

| `iterait/archlinux:latest`      | `iterait/archlinux:cuda`        | Base ArchLinux setup with `yay`.    |

| `iterait/archlinux-dev:latest`  | `iterait/archlinux-dev:cuda`    | `iterait/archlinux` + `base-devel`. |

| `iterait/tensorflow:latest`     | `iterait/tensorflow:cuda`       | `iterait/archlinux` + `tensorflow`. |

## Build

Build all the images by running:

```

./build.sh

```

## Run

Running the container without GPU support is straightforward.

```bash

$ docker run -it  /bin/bash

```

To run the container with GPU support, we recommend using `nvidia-docker`.

The following example demonstrates the employment of two GPUs and executing `bash`.

```bash

$ docker run --runtime=nvidia \

    -e NVIDIA_VISIBLE_DEVICES=0,1 \

    -it :cuda /bin/bash

```