How Do I View GPU Usage on the Notebook?
If you select GPU when creating a notebook instance, perform the following operations to view GPU usage:
- Log in to the ModelArts management console, and choose .
- In the Operation column of the target notebook instance in the notebook list, click Open to go to the Jupyter page.
- On the Files tab page of the Jupyter page, click New and select Terminal. The Terminal page is displayed.
- Run the following command to view GPU usage:
nvidia-smi
- Check which processes in the current notebook instance use GPUs.
python /modelarts/tools/gpu_processes.py
The following figure shows the case that the current process is using GPUs.
The following figure shows the case that the current process is not using GPUs.
Method 2:
Open /resource_info/gpu_usage.json and view the processes that are using GPUs.
If no process is using GPUs, the file may be unavailable or empty.
Others FAQs
- How Do I Use Multiple Ascend Cards for Debugging in a Notebook Instance?
- Why Is the Training Speed Similar When Different Notebook Flavors Are Used?
- How Do I Perform Incremental Training When Using MoXing?
- How Do I View GPU Usage on the Notebook?
- How Can I Obtain GPU Usage Through Code?
- Which Real-Time Performance Indicators of an Ascend Chip Can I View?
- Does the System Automatically Stop or Delete a Notebook Instance If I Do Not Enable Automatic Stop?
- What Are the Relationships Between Files Stored in JupyterLab, Terminal, and OBS?
- How Do I Migrate Data from an Old-Version Notebook Instance to a New-Version One?
- How Do I Use the Datasets Created on ModelArts in a Notebook Instance?
- pip and Common Commands
- What Are Sizes of the /cache Directories for Different Notebook Specifications in DevEnviron?
- How Do I Isolate IAM Users for Using Development Environments?
- What Is the Impact of Resource Overcommitment on Notebook Instances?
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