GPU accelerated, multi-arch (linux/amd64
, linux/arm64/v8
) docker images:
Images available for Python versions ≥ 3.11.1.
Build chain
The same as the Python docker stack.
Features
glcr.b-data.ch/cuda/python/ver:*-devel
serves as parent image for
glcr.b-data.ch/jupyterlab/cuda/python/base
.
Otherwise the same as the Python docker stack plus
- CUDA runtime, CUDA math libraries, NCCL and cuDNN
- TensortRT and TensorRT plugin libraries
The same as the Python docker stack plus
- NVIDIA GPU
- NVIDIA Linux driver
- NVIDIA Container Toolkit
ℹ️ The host running the GPU accelerated images only requires the NVIDIA driver, the CUDA toolkit does not have to be installed.
To install the NVIDIA Container Toolkit, follow the instructions for your platform:
latest:
stage 1
docker build \
--build-arg BASE_IMAGE=ubuntu \
--build-arg BASE_IMAGE_TAG=22.04 \
--build-arg CUDA_IMAGE=nvidia/cuda \
--build-arg CUDA_VERSION=12.8.1 \
--build-arg CUDA_IMAGE_SUBTAG=runtime-ubuntu22.04 \
--build-arg PYTHON_VERSION=3.13.2 \
-t cuda/python/ver \
-f ver/latest.Dockerfile .
stage 2
docker build \
--build-arg BUILD_ON_IMAGE=cuda/python/ver \
--build-arg CUDNN_VERSION=9.8.0.87 \
--build-arg CUDNN_CUDA_VERSION_MAJ_MIN=12.0 \
--build-arg CUDA_IMAGE_FLAVOR=runtime \
-t cuda/python/ver \
-f cuda/latest.Dockerfile .
version:
stage 1
docker build \
--build-arg BASE_IMAGE=ubuntu \
--build-arg BASE_IMAGE_TAG=22.04 \
--build-arg CUDA_IMAGE=nvidia/cuda \
--build-arg CUDA_IMAGE_SUBTAG=[cudnn8-]runtime-ubuntu22.04 \
-t cuda/python/ver:MAJOR.MINOR.PATCH \
-f ver/MAJOR.MINOR.PATCH.Dockerfile .
stage 2
docker build \
--build-arg BUILD_ON_IMAGE=cuda/python/ver:MAJOR.MINOR.PATCH \
--build-arg CUDA_IMAGE_FLAVOR=runtime \
-t cuda/python/ver:MAJOR.MINOR.PATCH \
-f cuda/MAJOR.MINOR.PATCH.Dockerfile .
For MAJOR.MINOR.PATCH
≥ 3.11.1
.
self built:
docker run -it --rm \
--gpus '"device=all"' \
cuda/python/ver[:MAJOR.MINOR.PATCH]
from the project's GitLab Container Registries:
docker run -it --rm \
--gpus '"device=all"' \
IMAGE[:MAJOR[.MINOR[.PATCH]]]
IMAGE
being one of
See CUDA Notes for tweaks.