Join GitHub today
GitHub is home to over 28 million developers working together to host and review code, manage projects, and build software together.Sign up
CUDA images come in three flavors and are available through the NVIDIA public hub repository.
base: starting from CUDA 9.0, contains the bare minimum (libcudart) to deploy a pre-built CUDA application.
Use this image if you want to manually select which CUDA packages you want to install.
runtime: extends the
baseimage by adding all the shared libraries from the CUDA toolkit.
Use this image if you have a pre-built application using multiple CUDA libraries.
devel: extends the
runtimeimage by adding the compiler toolchain, the debugging tools, the headers and the static libraries.
Use this image to compile a CUDA application from sources.
Running a CUDA container requires a machine with at least one CUDA-capable GPU and a driver compatible with the CUDA toolkit version you are using.
The machine running the CUDA container only requires the NVIDIA driver, the CUDA toolkit doesn't have to be installed.
NVIDIA drivers are backward-compatible with CUDA toolkits versions
|CUDA toolkit version||Driver version||GPU architecture|
|6.5||>= 340.29||>= 2.0 (Fermi)|
|7.0||>= 346.46||>= 2.0 (Fermi)|
|7.5||>= 352.39||>= 2.0 (Fermi)|
|8.0||== 361.93 or >= 375.51||== 6.0 (P100)|
|8.0||>= 367.48||>= 2.0 (Fermi)|
|9.0||>= 384.81||>= 3.0 (Kepler)|
|9.1||>= 387.26||>= 3.0 (Kepler)|
# Running an interactive CUDA session isolating the first GPU docker run -ti --rm --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=0 nvidia/cuda # Querying the CUDA 7.5 compiler version docker run --rm --runtime=nvidia nvidia/cuda:7.5-devel nvcc --version
Check the DockerHub