Verify CUDA Installation

The following verification steps only apply to the cuda (full) installations and require nodes with physical NVIDIA GPU hardware.

Verify driver version by looking at: /proc/driver/nvidia/version:
```
cat /proc/driver/nvidia/version
```
Verify the CUDA Toolkit version
```
nvcc -V
```
Verify that the CUDA runtime can detect the installed GPUs by compiling and executing NVIDIA’s deviceQuery sample.

CUDA Samples 12.8 and later require CMake 3.20 or later. Select a CUDA Samples release that is compatible with the Toolkit version reported by nvcc -V. Replace <samples-tag> below with that release tag (for example, v13.3 for CUDA 13.3).

The sample’s top-level directory has changed between releases. The git ls-files command below locates it without hard-coding that directory.
- Clone the selected release and build only deviceQuery:
```
git clone --branch <samples-tag> --depth 1 \
  https://github.com/NVIDIA/cuda-samples.git
cd cuda-samples
sample_dir=$(dirname "$(git ls-files '*/1_Utilities/deviceQuery/CMakeLists.txt')")
cmake -S "$sample_dir" -B build \
  -DCMAKE_BUILD_TYPE=Release \
  -DCMAKE_RUNTIME_OUTPUT_DIRECTORY="$PWD/build" \
  -DCMAKE_RUNTIME_OUTPUT_DIRECTORY_RELEASE="$PWD/build"
cmake --build build --target deviceQuery --config Release --parallel
```
- Run the deviceQuery sample:
```
./build/deviceQuery
```
  Confirm that the output lists each expected GPU and ends with Result = PASS.

Note

CUDA Samples releases before 12.8 use release-specific Makefiles. Follow the build instructions in the README shipped with the selected tag instead of the CMake commands above.

Note

NVIDIA removed bandwidthTest from CUDA Samples 12.9 because it did not produce accurate results. Use NVBandwidth when bandwidth measurements are required.