CUDA driver version is insufficient for CUDA runtime version

When you do a “/usr/local/cuda-10.1/extras/demo_suite/deviceQuery”. You might get the errors seemed above

[root@node1 ~]# /usr/local/cuda-10.1/extras/demo_suite/deviceQuery
/usr/local/cuda-10.1/extras/demo_suite/deviceQuery Starting...

CUDA Device Query (Runtime API) version (CUDART static linking)

cudaGetDeviceCount returned 35
-> CUDA driver version is insufficient for CUDA runtime version
Result = FAIL

The Issue may cause some confusion. It is not your libraries. But the it is the Power Setting at the BIOS. Most Servers are configured to be balanced. But for GPGPU, you need to put Power to “Maximum Performance”. For example, for HPE Server, you should put “Static High Performance Mode”

Digital Scalable multi-node training for AI jobs on NVIDIA DGX, OpenShift and Spectrum Scale

Nvidia and IBM did a complex proof-of-concept to demonstrate the scaling of AI workload using Nvidia DGX, Red Hat OpenShift and IBM Spectrum Scale at the example of ResNet-50 and the segmentation of images using the Audi A2D2 dataset. The project team published an IBM Redpaper with all the technical details and will present the key learnings and results.