https://github.com/jbris/stan-cmdstanr-gpu-docker

A Docker image to run Stan, cmdstanr, and brms for Bayesian statistical modelling. GPU support using OpenCL is available.
https://github.com/jbris/stan-cmdstanr-gpu-docker

bayes bayesian-inference brms cmdstan cmdstanr data-science docker posterior probabilistic-programming projpred rstan rstanarm shinystan stan stan-gpu stan-lang stan-math-library tidybayes tidyverse

Last synced: 5 months ago
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A Docker image to run Stan, cmdstanr, and brms for Bayesian statistical modelling. GPU support using OpenCL is available.

• Host: GitHub
• URL: https://github.com/jbris/stan-cmdstanr-gpu-docker
• Owner: JBris
• License: mit
• Created: 2023-06-22T04:00:44.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2025-01-11T12:38:29.000Z (9 months ago)
• Last Synced: 2025-04-08T14:11:45.711Z (6 months ago)
• Topics: bayes, bayesian-inference, brms, cmdstan, cmdstanr, data-science, docker, posterior, probabilistic-programming, projpred, rstan, rstanarm, shinystan, stan, stan-gpu, stan-lang, stan-math-library, tidybayes, tidyverse
• Language: Dockerfile
• Homepage: https://jbris.github.io/stan-cmdstanr-gpu-docker/
• Size: 32.2 KB
• Stars: 5
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md

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README

          
# stan-cmdstanr-gpu-docker

[![pages-build-deployment](https://github.com/JBris/stan-cmdstanr-gpu-docker/actions/workflows/pages/pages-build-deployment/badge.svg?branch=main)](https://github.com/JBris/stan-cmdstanr-gpu-docker/actions/workflows/pages/pages-build-deployment)

## Table of Contents  

- [stan-cmdstanr-gpu-docker](#stan-cmdstanr-gpu-docker)

  - [Table of Contents](#table-of-contents)

    - [Introduction](#introduction)

    - [Stan](#stan)

    - [Docker](#docker)

### Introduction

A Docker image to run Stan, cmdstanr, and brms for Bayesian statistical modelling - with GPU support.

Launch an RStudio webserver using `bash stan_up.sh`.

Execute `bash docker_pull.sh` to pull the image.

To convert the image into an Apptainer image, run `bash apptainer_pull.sh`.

### Stan

The following packages are installed during the image build process:

* [Stan](https://mc-stan.org/)

* [rstan](https://mc-stan.org/users/interfaces/rstan)

* [rstanarm](https://mc-stan.org/rstanarm/)

* [cmdstan](https://mc-stan.org/users/interfaces/cmdstan)

* [brms](https://paul-buerkner.github.io/brms/)

* [posterior](https://mc-stan.org/posterior/)

* [tidybayes](https://mjskay.github.io/tidybayes/)

* [bayesplot](https://mc-stan.org/bayesplot/)

* [posterior](https://mc-stan.org/posterior/)

* [rstantools](https://mc-stan.org/rstantools/)

* [projpred](https://mc-stan.org/projpred/)

* [shinystan](https://mc-stan.org/shinystan/)

The [brms_within_chain_parallelization.R](brms_within_chain_parallelization.R) script can be executed within the Docker container to evaluate whether within-chain parallelization, CmdStan, brms, and OpenCL are working properly.

### Docker

This Docker image extends from `rocker/tidyverse`. [Click this link for more information about the Rocker project.](https://rocker-project.org/images/)

Running the Docker container will launch an RStudio web server. You can access RStudio by visiting localhost:$R_STUDIO_PORT on your web browser. See [.env](.env) for the defined environment variables.

Running docker-compose will bind a volume, mapping the container's `home` directory to a local `r_home` directory.

See the [Dockerfile](Dockerfile) for the instructions executed during the build of the Docker image. 

View [docker-compose.yaml](docker-compose.yaml) to see the definition for the Stan service.