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2 changes: 1 addition & 1 deletion docs/faq/faq.md
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Expand Up @@ -78,7 +78,7 @@ In summary, while HAMi's own priority serves a different, device-specific purpos

- **KubeVirt & Kata Containers**: Incompatible due to their reliance on virtualization for resource isolation, whereas HAMi’s GPU Device Plugin depends on direct GPU mounting into containers. Supporting these would require adapting the device allocation logic, balancing performance overhead and implementation complexity. HAMi prioritizes high-performance scenarios with direct GPU mounting and thus does not currently support these virtualization solutions.

## Why are there [HAMI-core Warn(...)] logs in my Pod's output? Can I disable them?
## Why are there [HAMi-core Warn(...)] logs in my Pod's output? Can I disable them?

This is normal and can be ignored. If needed, disable the logs by setting the environment variable `LIBCUDA_LOG_LEVEL=0` in the container.

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3 changes: 1 addition & 2 deletions docs/key-features/device-sharing.md
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Expand Up @@ -20,5 +20,4 @@ HAMi's device sharing enables:

## Benefits {#benefits}

By leveraging these features, HAMi enhances resource efficiency and security in shared-device environments.
Organizations can optimize their AI infrastructure for greater flexibility and performance while meeting diverse computational demands.
These features improve resource efficiency and isolation in shared-device environments across diverse device types and workloads.
2 changes: 1 addition & 1 deletion docs/userguide/hami-webui-user-guide.md
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Expand Up @@ -77,4 +77,4 @@ HAMi WebUI provides a visualization solution centered on GPU resources, enabling
- Analyze resource usage
- Locate issues and optimize resource usage

In production environments, WebUI can significantly reduce the complexity of GPU operations and management.
In production environments, WebUI reduces the overhead of GPU operations and management.
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