{"id":13442993,"url":"https://github.com/Kaixhin/dockerfiles","last_synced_at":"2025-03-20T15:31:44.155Z","repository":{"id":27971260,"uuid":"31464477","full_name":"Kaixhin/dockerfiles","owner":"Kaixhin","description":"Compilation of Dockerfiles with automated builds enabled on the Docker Registry","archived":false,"fork":false,"pushed_at":"2019-08-02T23:04:31.000Z","size":422,"stargazers_count":505,"open_issues_count":4,"forks_count":127,"subscribers_count":32,"default_branch":"master","last_synced_at":"2024-10-28T06:00:22.818Z","etag":null,"topics":["cuda","deep-learning","docker","dockerfiles","machine-learning","vnc"],"latest_commit_sha":null,"homepage":"https://hub.docker.com/u/kaixhin/","language":"Dockerfile","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Kaixhin.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.md","code_of_conduct":null,"threat_model":null,"audit":null,"citation":"CITATION.md","codeowners":null,"security":null,"support":null}},"created_at":"2015-02-28T14:12:33.000Z","updated_at":"2024-10-22T09:55:16.000Z","dependencies_parsed_at":"2022-08-31T13:55:07.353Z","dependency_job_id":null,"html_url":"https://github.com/Kaixhin/dockerfiles","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Kaixhin%2Fdockerfiles","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Kaixhin%2Fdockerfiles/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Kaixhin%2Fdockerfiles/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Kaixhin%2Fdockerfiles/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Kaixhin","download_url":"https://codeload.github.com/Kaixhin/dockerfiles/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244640085,"owners_count":20485980,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["cuda","deep-learning","docker","dockerfiles","machine-learning","vnc"],"created_at":"2024-07-31T03:01:54.496Z","updated_at":"2025-03-20T15:31:43.805Z","avatar_url":"https://github.com/Kaixhin.png","language":"Dockerfile","readme":"[![MIT License](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE.md)\n\ndockerfiles\n===========\n\nCompilation of Dockerfiles with automated builds enabled on the [Docker Hub](https://hub.docker.com/u/kaixhin/). **Not suitable for production environments.** These images are under continuous development, so breaking changes may be introduced.\n\nNearly all images are based on Ubuntu Core 14.04 LTS, built with minimising size/layers and [best practices](https://docs.docker.com/engine/userguide/eng-image/dockerfile_best-practices/) in mind. Dependencies are indicated left to right e.g. cuda-vnc is VNC built on top of CUDA. Explicit dependencies are excluded.\n\n\u003c!--\nUp-to-date builds\n-----------------\n\nSome builds based on certain software have builds that are triggered on schedule via a cron script to stay up to date on a weekly basis. These are:\n\n- [Brainstorm](https://github.com/IDSIA/brainstorm)\n- [Caffe](https://github.com/BVLC/caffe)\n- [DIGITS](https://github.com/NVIDIA/DIGITS)\n- [FGLab](https://github.com/Kaixhin/FGLab)/[FGMachine](https://github.com/Kaixhin/FGMachine)\n- [Keras](https://github.com/fchollet/keras)\n- [Lasagne](https://github.com/Lasagne/Lasagne)\n- [MXNet](https://github.com/dmlc/mxnet)\n- [neon](https://github.com/NervanaSystems/neon)\n- [Pylearn2](https://github.com/lisa-lab/pylearn2)\n- [Theano](https://github.com/Theano/Theano)\n- [Torch](https://github.com/torch/distro)\n--\u003e\n\nGraphical applications\n----------------------\n\nStarting graphical (X11) applications is possible with the following commands:\n\n```sh\ndocker run -it `# Running interactively, but can be replaced with -d for daemons` \\\n  -e DISPLAY `# Pass $DISPLAY` \\\n  -v=/tmp/.X11-unix:/tmp/.X11-unix `# Pass X11 socket` \\\n  --ipc=host `# Allows MIT-SHM` \\\n  \u003cimage\u003e\n```\n\nGeneral information on running desktop applications with Docker can be found [in this blog post](https://blog.jessfraz.com/post/docker-containers-on-the-desktop/). You probably will also need to configure the X server host (`xhost`) to [give access](http://wiki.ros.org/docker/Tutorials/GUI). For hardware acceleration on Linux, it is possible to use `nvidia-docker` (with an image built for NVIDIA Docker), although OpenGL is [not fully supported](https://github.com/NVIDIA/nvidia-docker/issues/11).\n\nOn Mac OS X, use XQuartz and [allow connections from network clients](https://blogs.oracle.com/OracleWebCenterSuite/entry/running_gui_applications_on_docker). Then the following can be used:\n\n```sh\ndocker run -it \\\n  -e DISPLAY=`ifconfig en0 | grep inet | awk '$1==\"inet\" {print $2}'`:0 `# Use XQuartz network $DISPLAY` \\\n  --ipc=host \\\n  \u003cimage\u003e\n```\n\nDaemonising containers\n----------------------\n\nMost containers run as a foreground process. To daemonise (in Docker terminology, detach) such a container it is possible to use:\n\n`docker run -d \u003cimage\u003e sh -c \"while true; do sleep 1; done\"`\n\nIt is now possible to access the daemonised container, for example using bash:\n\n`docker exec -it \u003cid\u003e bash`\n\nSibling containers\n------------------\n\nTo start containers on the host from within a docker container, the container requires `docker-engine` installed, with the same API version as the Docker daemon on the host. The Docker socket also needs to be mounted inside the container:\n\n`-v /var/run/docker.sock:/var/run/docker.sock`\n\nCUDA\n----\n\nMany images rely on [CUDA](http://www.nvidia.com/object/cuda_home_new.html). These images are versioned with the corresponding tags, e.g. \"8.0\" and \"7.5\", on the Docker Hub.\n\nThese images need to be run on an Ubuntu host OS with [NVIDIA Docker](https://github.com/NVIDIA/nvidia-docker) installed. The driver requirements can be found on the [NVIDIA Docker wiki](https://github.com/NVIDIA/nvidia-docker/wiki/CUDA#requirements).\n\nDeprecated images\n-----------------\n\n`kaixhin/cuda` and `kaixhin/cudnn` have now been **deprecated** in favour of the official solution ([`nvidia/cuda`](https://hub.docker.com/r/nvidia/cuda/)).\n\nMigration\n---------\n\nIn the future it will hopefully be possible to checkpoint and restore Docker containers easily using [CRIU](http://criu.org/Docker). This would alleviate some issues, such as the inability to restart a VNC image successfully.\n\nAutomated Builds\n----------------\n\n[Automated Builds](https://docs.docker.com/docker-hub/builds/) on the Docker Hub have several advantages, including reproducibility and security. However the build cluster has the following limits for Automated Builds:\n\n- 2 hours\n- 1 CPU\n- 2 GB RAM\n- 512 MB swap\n- 30 GB disk space\n\nThe main tip for keeping within the CPU and memory limits is to reduce parallelism/forking processes. Due to their logging system, redirecting stdout/stderr to /dev/null can potentially save a reasonable amount of memory.\n\nAcknowledgements\n----------------\n\nSome Dockerfiles have been modified from the work of others. The source for these are:\n\n- [CUDA](https://github.com/tleyden/docker)\n- [Samba](https://github.com/dperson/samba)\n- [VNC](https://github.com/dockerfile/ubuntu-desktop)\n\nCitation\n--------\n\nIf you find this useful in research please consider [citing this work](CITATION.md).\n","funding_links":[],"categories":["Dockerfile"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FKaixhin%2Fdockerfiles","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FKaixhin%2Fdockerfiles","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FKaixhin%2Fdockerfiles/lists"}