Rocker 4.6.1 with GPU enabled

containers/rocker_ml_cuda/README.md

@@ -0,0 +1,45 @@
+# rocker_ml_cuda
+
+GPU-enabled RStudio container: `rocker/ml` plus CUDA PyTorch (used from R
+through reticulate), `tabpfn`, and tidymodels packages. Currently in testing
+for the OOD RStudio app.
+
+## Pins
+
+- **Base image:** `rocker/ml` is pinned by digest in `rocker_ml_cuda.def`
+  (it was `py3.14` / `latest` as of 2026-10-04). `rocker/ml` no longer
+  publishes R version tags, so a tag alone would change under us on rebuild.
+- **PyTorch:** `torch==2.14.0` from the `cu126` index. This is the last
+  release with a wheel for Volta (V100) GPUs, so don't upgrade it while
+  V100s are in use.
+- **Driver:** tested on nodes with NVIDIA driver 525.147.05 (CUDA 12.0).
+
+## Build
+
+On a cluster node with apptainer (needs network access):
+
+```
+./build_container.sh
+```
+
+This builds the image, checks that `rserver`, `rsession`, `R`, and
+`rstudio-server` exist inside it, moves it to
+`/hpc/<cluster>/containers/testing/rocker/`, and writes
+`modules/testing/rocker_ml_cuda/<version>.lua` in this repo.
+
+## Check the GPU
+
+```
+apptainer exec --nv /hpc/<cluster>/containers/testing/rocker/rocker_ml_cuda_1.0.0.sif nvidia-smi
+apptainer exec --nv /hpc/<cluster>/containers/testing/rocker/rocker_ml_cuda_1.0.0.sif \
+  /opt/venv/bin/python -c 'import torch; print(torch.cuda.is_available())'
+```
+
+## Notes for OOD
+
+R is installed from apt in this image (`/usr/bin/R`, libR in
+`/usr/lib/R/lib`), not under `/usr/local` like other rocker images. The
+RStudio app's rsession wrapper must also add `/.singularity.d/libs` and
+`/opt/venv/bin` back to the paths after sourcing the host environment, or
+the GPU and the Python venv are not visible in RStudio. See
+`ood/rstudio/template/script.sh.erb`.

containers/rocker_ml_cuda/build_container.sh

@@ -0,0 +1,111 @@
+#!/bin/bash -e
+# build GPU-enabled apptainer container for RStudio (rocker/ml + CUDA PyTorch)
+# base image and package pins are in rocker_ml_cuda.def
+
+# specify version
+VERSION="1.0.0"
+IMAGE_NAME="rocker_ml_cuda"
+CONTAINER_NAME=${IMAGE_NAME}_${VERSION}.sif
+
+echo "Building ${CONTAINER_NAME}"
+
+# .def and module file paths below are relative to this directory
+cd "$(dirname "$0")"
+
+# build the container
+module purge
+module load apptainer
+unset APPTAINER_BIND
+apptainer build --fakeroot ${CONTAINER_NAME} ${IMAGE_NAME}.def
+
+# get the paths for rserver, rsession, and R inside the container. We need
+# these for the portal, so it's useful to "precompute" and load
+RSESSION_EXEC="/usr/lib/rstudio-server/bin/rsession"
+RSERVER_EXEC="/usr/lib/rstudio-server/bin/rserver"
+R_EXEC=$(apptainer exec ${CONTAINER_NAME} which R)
+# verify
+for EXEC in ${RSESSION_EXEC} ${RSERVER_EXEC} ${R_EXEC}
+do
+  if ! apptainer exec ${CONTAINER_NAME} test -x ${EXEC} &> /dev/null
+  then
+    echo "${EXEC} not found in the container"
+    exit 12
+  fi
+done
+if ! apptainer exec ${CONTAINER_NAME} which rstudio-server &> /dev/null
+then
+  echo "rstudio-server not found in the container (needed for the OOD idle timeout)"
+  exit 12
+fi
+
+# move container to /hpc/{sys}/containers/testing/ (kept out of the main
+# containers directory while in testing)
+CLUSTER=$(scontrol show config | grep ClusterName | grep -oP '= \K.+')
+if [ "$CLUSTER" = "nvidia" ]; then
+  CLUSTER="mp"
+fi
+CONTAINER_DIR=/hpc/${CLUSTER}/containers/testing/rocker
+mkdir -p ${CONTAINER_DIR}
+mv ${CONTAINER_NAME} ${CONTAINER_DIR}/${CONTAINER_NAME}
+
+# create a module file in ../../modules/ (in the git repo)
+RUN_COMMAND="apptainer run --nv "
+
+mkdir -p ../../modules/testing/${IMAGE_NAME}
+MODULE_FILE=../../modules/testing/${IMAGE_NAME}/${VERSION}.lua
+(
+sed 's/^ \{2\}//' > "$MODULE_FILE" << EOL
+
+  help([[
+  Name: R + CUDA PyTorch
+  Version: ${VERSION}
+  Website: https://www.r-project.org/
+
+  R is a language and environment for statistical computing and graphics.
+  This container includes GPU-enabled PyTorch (via reticulate) for V100 GPUs.
+
+  To use R:
+
+  R -- launches an R terminal
+  Rscript script -- run a script
+
+  ]])
+  whatis("Name: R + CUDA PyTorch")
+  whatis("Version: rocker/ml:py3.14 + torch 2.14.0 (cu126)")
+  whatis("Category: R")
+  whatis("URL: https://hub.docker.com/r/rocker/ml")
+  whatis("Description: Provides access to R and Rstudio with GPU-enabled PyTorch through a Rocker container built with Apptainer")
+  family("R")
+
+  always_load('apptainer')
+  local sif_file = '${CONTAINER_DIR}/${CONTAINER_NAME}'
+
+  local work_dir = '/work'
+  local lustre_work = '/lustre/work/client'
+  local scratch_dir = os.getenv("SCRATCH")
+  local home = os.getenv("HOME")
+  local user_libs = pathJoin(home, 'R/${IMAGE_NAME}/${VERSION}')
+
+  function build_command(app)
+    local cmd        = '${RUN_COMMAND} --env R_LIBS_USER=' .. user_libs .. ' -B ' .. scratch_dir .. ',' .. work_dir .. ',' .. lustre_work .. ' ' .. sif_file .. ' ' .. app
+    local sh_ending  = ' "\$@"'
+    local csh_ending = ' \$*'
+    local sh_cmd     = cmd .. sh_ending
+    local csh_cmd    = cmd .. csh_ending
+    set_shell_function(app, sh_cmd, csh_cmd)
+  end
+
+  setenv('CONTAINER_RSESSION', '${RSESSION_EXEC}')
+  setenv('CONTAINER_RSERVER', '${RSERVER_EXEC}')
+  setenv('CONTAINER_R', '${R_EXEC}')
+  setenv('CONTAINER_IMAGE', '${CONTAINER_DIR}/${CONTAINER_NAME}')
+  setenv('R_LIBS_USER', user_libs)
+  unsetenv('XDG_RUNTIME_DIR')
+
+  build_command('R')
+  build_command('Rscript')
+EOL
+)
+
+echo "Container: ${CONTAINER_DIR}/${CONTAINER_NAME}"
+echo "Module:    ${MODULE_FILE}"

containers/rocker_ml_cuda/rocker_ml_cuda.def

@@ -0,0 +1,22 @@
+Bootstrap: docker
+# rocker/ml:py3.14 (== latest as of 2026-10-04), pinned by digest because
+# rocker/ml no longer publishes R version tags
+From: rocker/ml@sha256:77443c5ff6422556809910000db4fb3576cb00609f39474bdb9f04edc3eeddca
+
+%labels
+    Author Mateo Langston Smith <mlangstonsmith@smu.edu>
+    Version 1.0.0
+
+%post
+    export DEBIAN_FRONTEND=noninteractive
+
+    # GPU PyTorch for V100 (cu126; 2.14.0 is the last release with a Volta wheel)
+    /opt/venv/bin/pip install --no-cache-dir torch==2.14.0 --index-url https://download.pytorch.org/whl/cu126
+    /opt/venv/bin/pip install --no-cache-dir tabpfn
+
+    # R packages (uses the image's default CRAN/binary repo settings)
+    Rscript -e 'install.packages(c("tidymodels","probably","ranger","tictoc","modeldata","Lahman","tabpfn"))'
+
+%environment
+    export CUDA_MODULE_LOADING=LAZY
+    export RETICULATE_PYTHON=/opt/venv/bin/python

modules/testing/rocker_ml_cuda/1.0.0.lua

@@ -0,0 +1,49 @@
+
+help([[
+Name: R + CUDA PyTorch
+Version: 1.0.0
+Website: https://www.r-project.org/
+
+R is a language and environment for statistical computing and graphics.
+This container includes GPU-enabled PyTorch (via reticulate) for V100 GPUs.
+
+To use R:
+
+R -- launches an R terminal
+Rscript script -- run a script
+
+]])
+whatis("Name: R + CUDA PyTorch")
+whatis("Version: rocker/ml:py3.14 + torch 2.14.0 (cu126)")
+whatis("Category: R")
+whatis("URL: https://hub.docker.com/r/rocker/ml")
+whatis("Description: Provides access to R and Rstudio with GPU-enabled PyTorch through a Rocker container built with Apptainer")
+family("R")
+
+always_load('apptainer')
+local sif_file = '/hpc/m3/containers/testing/rocker/rocker_ml_cuda_1.0.0.sif'
+
+local work_dir = '/work'
+local lustre_work = '/lustre/work/client'
+local scratch_dir = os.getenv("SCRATCH")
+local home = os.getenv("HOME")
+local user_libs = pathJoin(home, 'R/rocker_ml_cuda/1.0.0')
+
+function build_command(app)
+  local cmd        = 'apptainer run --nv  --env R_LIBS_USER=' .. user_libs .. ' -B ' .. scratch_dir .. ',' .. work_dir .. ',' .. lustre_work .. ' ' .. sif_file .. ' ' .. app
+  local sh_ending  = ' "$@"'
+  local csh_ending = ' $*'
+  local sh_cmd     = cmd .. sh_ending
+  local csh_cmd    = cmd .. csh_ending
+  set_shell_function(app, sh_cmd, csh_cmd)
+end
+
+setenv('CONTAINER_RSESSION', '/usr/lib/rstudio-server/bin/rsession')
+setenv('CONTAINER_RSERVER', '/usr/lib/rstudio-server/bin/rserver')
+setenv('CONTAINER_R', '/usr/bin/R')
+setenv('CONTAINER_IMAGE', '/hpc/m3/containers/testing/rocker/rocker_ml_cuda_1.0.0.sif')
+setenv('R_LIBS_USER', user_libs)
+unsetenv('XDG_RUNTIME_DIR')
+
+build_command('R')
+build_command('Rscript')

ood/rstudio/form.yml.erb

@@ -65,6 +65,9 @@ attributes:
       <%- if CheckAccounts.Accounts.any? { |word| word.include?("kbnk") } | CheckAccounts.Accounts.any? { |word| word.include?("jlagrone") }-%>
       - [ "R 4.5.1 (custom kbnk)", "kbnk/R/4.5.1" ]
       <%- end -%>
+      <%- if CheckAccounts.Accounts.any? { |word| word.include?("csouth") } | CheckAccounts.Accounts.any? { |word| word.include?("jlagrone") }-%>
+      - [ "4.6.1 + GPU", "/hpc/m3/hpc_docs/modules/testing/rocker_ml_cuda/1.0.0.lua" ]
+      <%- end -%>
   environment:
     widget: text_area
     label: "Custom Environment Settings"
@@ -80,7 +83,7 @@ attributes:
       [SLURM partition]: https://southernmethodistuniversity.github.io/hpc_docs/about/queues.html#m3-queues
     options:
     <%- CheckQueues.Queues.each do |q| -%>
-      <%- if q[4].to_i == 0 -%> #disable gpu queues
+      <%- if q[4].to_i == 0 || CheckAccounts.Accounts.any? { |word| word.include?("csouth") } || CheckAccounts.Accounts.any? { |word| word.include?("jlagrone") } -%> #disable gpu queues (except for GPU testers)
       - ["<%= q[0] %>", "<%= q[0] %>",
         data-max-bc-num-hours: "<%= q[1] %>",
         data-max-bc-num-cores: "<%= q[2] %>",

ood/rstudio/template/script.sh.erb

@@ -53,6 +53,15 @@ sed 's/^ \{2\}//' > "${RSESSION_WRAPPER_FILE}" << EOL
 
   # make sure the container libR is visible inside container
   export LD_LIBRARY_PATH="/usr/local/lib/R/lib${LD_LIBRARY_PATH:+":$LD_LIBRARY_PATH"}"
+<%- if context.r_module.include?("rocker_ml_cuda") -%>
+
+  # environment.txt and the line above replace the container's paths, so
+  # restore libR (apt-installed in this image), the host driver libs bound
+  # by --nv, and the image's python venv (CUDA comes from pip wheels there)
+  export LD_LIBRARY_PATH="/usr/lib/R/lib:/.singularity.d/libs:\${LD_LIBRARY_PATH}"
+  export PATH="/opt/venv/bin:\${PATH}:/usr/lib/rstudio-server/bin/quarto/bin"
+  export CUDA_MODULE_LOADING="\${CUDA_MODULE_LOADING:-LAZY}"
+<%- end -%>
 
   # Log all output from this script
   export RSESSION_LOG_FILE="${PWD}/rsession.log"
@@ -195,7 +204,7 @@ unset APPTAINER_BIND
 
 export APPTAINERENV_XDG_CONFIG_DIRS="/etc/"
 export APPTAINERENV_RSTUDIO_CONFIG_DIRS=$RSTUDIO_CONFIG_DIRS
-apptainer exec \
+apptainer exec <%= context.bc_num_gpus.to_i > 0 ? "--nv" : "" %> \
   -B ${TMPDIR}:/tmp \
   -B ${TMPDIR}/run:/run \
   -B ${TMPDIR}/var/lib:/var/lib/rstudio-server \