Comments (1)
The list of CVEs above also report for new version v0.14.5
from k8s-device-plugin.
Related Issues (20)
- How to solve could not load NVML library: libnvidia-ml.so.1 HOT 23
- undefined variable "$hasServiceAccount" HOT 4
- Is nvidia container runtime necessary for app pod when using cdi-annotations strategy? HOT 5
- More flexible time-slicing strategy configuration
- an amazon machine image (AMI HOT 1
- an amazon machine image (AMI) that meets the prequites of k8s-device-plugin HOT 2
- How to trigger gpu failure, the gpu count of node's allocatable field will be dynamically decrease HOT 4
- Unable to install in Ubuntu 20.04 a nvidia container toolkit with version < 1.14.4 HOT 15
- GPU health status exposure and remediation methods HOT 1
- GPU distribution wrong after reboot node HOT 2
- GPU allocation does not respect NVLink HOT 5
- A pod can access all gpu resources even if no nvidia.com/gpu is configed. HOT 1
- Using CUDA MPS to enable GPU sharing, the pod occupies all GPU memory. HOT 11
- 0/1 nodes are available: 1 Insufficient nvidia.com/gpu HOT 2
- Limiting GPU Resource Usage per Docker Container with MPS Daemon
- K8s 1.24 failed to schedule using GPU-(error code CUDA driver HOT 6
- Access NVIDIA GPUs in K8s in a non-privileged container
- can't install 0.15.0-rc.2 HOT 3
- Device plugin does not start on MIG-enabled host due to insufficient permissions HOT 6
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