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Expand Up @@ -199,7 +199,7 @@ HAMi vGPU 是纯软件方案,无硬件要求。NVIDIA MIG 是硬件分区,

## 为什么 nvidia.com/gpumem 限制未生效? {#why-is-my-nvidiagpumem-limit-not-enforced}

最常见的四种原因:设置了 `CUDA_DISABLE_CONTROL=true`、工作负载运行在 Docker-in-Docker 中、应用直接调用 GPU 驱动(绕过了 `libvgpu.so`)、或节点上 `nvidia-container-runtime` 未设为默认运行时。解决步骤参见[排障手册](./troubleshooting)。
最常见的四种原因:设置了 `CUDA_DISABLE_CONTROL=true`、工作负载运行在 Docker-in-Docker 中、应用直接调用 GPU 驱动(绕过了 `libvgpu.so`)、或节点上 `nvidia-container-runtime` 未设为默认运行时。解决步骤参见[排障手册](../troubleshooting/troubleshooting.md)。

## HAMi 是替换 kube-scheduler 还是与其并行运行?

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2 changes: 1 addition & 1 deletion versioned_docs/version-v2.9.0/faq/faq.md
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Expand Up @@ -202,7 +202,7 @@ Use HAMi vGPU when the GPU does not support MIG, workloads need flexible memory

## Why is my nvidia.com/gpumem limit not enforced? {#why-is-my-nvidiagpumem-limit-not-enforced}

The four most common causes: `CUDA_DISABLE_CONTROL=true` is set, the workload runs inside Docker-in-Docker, the application calls the GPU driver directly (bypassing `libvgpu.so`), or `nvidia-container-runtime` is not the default runtime on the node. See [Troubleshooting](./troubleshooting) for resolution steps.
The four most common causes: `CUDA_DISABLE_CONTROL=true` is set, the workload runs inside Docker-in-Docker, the application calls the GPU driver directly (bypassing `libvgpu.so`), or `nvidia-container-runtime` is not the default runtime on the node. See [Troubleshooting](../troubleshooting/troubleshooting.md) for resolution steps.

## Does HAMi replace kube-scheduler or run alongside it?

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