华为云UCS-创建GPU应用:验证GPU虚拟化隔离能力

时间：2024-12-19 08:52:02

华为云UCS GPU调度

验证GPU虚拟化隔离能力

工作负载创建成功后，您可以尝试验证GPU虚拟化的隔离能力。

登录容器查看容器被分配显存总量

kubectl exec -it gpu-app -- nvidia-smi

预期输出：

Wed Apr 12 07:54:59 2023
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 470.141.03   Driver Version: 470.141.03   CUDA Version: 11.4     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  Tesla V100-SXM2...  Off  | 00000000:21:01.0 Off |                    0 |
| N/A   27C    P0    37W / 300W |   4792MiB /  5000MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
+-----------------------------------------------------------------------------+

预期输出表明，该容器被分配显存总量为5000 MiB，实际使用了4792MiB。

查看所在节点的GPU显存隔离情况（在节点上执行）。

export PATH=$PATH:/usr/local/nvidia/bin;nvidia-smi

预期输出：

Wed Apr 12 09:31:10 2023
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 470.141.03   Driver Version: 470.141.03   CUDA Version: 11.4     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  Tesla V100-SXM2...  Off  | 00000000:21:01.0 Off |                    0 |
| N/A   27C    P0    37W / 300W |   4837MiB / 16160MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A    760445      C   python                           4835MiB |
+-----------------------------------------------------------------------------+

预期输出表明，GPU节点上的显存总量为16160 MiB，其中示例Pod使用了4837MiB。

上一篇：华为云UCS-创建GPU应用:约束与限制

下一篇：华为云UCS-创建GPU应用:约束与限制