Comments (1)
If nvidia is set as the default runtime in containerd and NVIDIA_VISIBLE_DEVICES is set (e.g. to all in this case), the nvidia runtime makes the required changes to the OCI Runtime spec to ensure that these are injected.
Either use volume mounts for device selection, or use runtime classes to opt-in to GPU usage instead.
from k8s-device-plugin.
Related Issues (20)
- Error in nvidia-device-plugin pod. HOT 2
- Go Package: github.com/opencontainers/runc 1.0.0-rc93 < 1.1.12 - Local Sandbox Bypass Vulnerability HOT 1
- When use MPS, add a initContainers to default set compute model
- update nodelabel for config-manger k8s-device-plugin continuing printing error msg, not stop HOT 1
- allPossibleMigStrategiesAreNone is false when using default values HOT 4
- Fix mode detection on Tegra-based platforms that support NVML HOT 1
- Workloads keep in hang state except cuda-sample:vectoradd under MPS mode HOT 9
- mps server error Failed to start : invalid argument
- nvidia-device-plugin.hasConfigMap returns a string HOT 9
- helm: can't upgrade to 0.15.0 in place due to daemonset label selector change HOT 3
- Addressing several security vulnerabilities in the version v0.15.0
- Failed when deploy via helm HOT 1
- The plugin has already support nvlink? HOT 1
- K3S - Failed to start plugin: error waiting for MPS daemon HOT 6
- Using MPS sharing, the pod running multiple cuda application will exceed resources.limits."nvidia.com/gpu.shared" HOT 2
- Questions about NVIDIA Device Plugin installation error - how to make GPU nodes be preempted by gpu pod scheduling?
- When GPU is MIG mixed model, one pod use two MIG Instance, use nvidia-smi can't find. HOT 2
- Incorrect deviceClassWhitelist configuration is provided HOT 1
- Does not set the right value for nvidia.com/gpu.replicas label when timesharing is enabled
- Change GFD repository image V0.15.0 Helm HOT 8
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