debug on gpu node
Debugging on a Specialized GPU Node with VS Code
In this post, we’ll explore how to connect to a GPU node on a cluster server via SSH in Visual Studio Code (VS Code) and debug a Python file in that environment.
Prerequisites
You should already be able to connect to the login node on VS Code.
Strategy
The strategy involves logging in and applying for a compute-node with a GPU, setting a configuration for that GPU node in your .ssh/config
with a ProxyJump through the login node, and finally logging into the GPU node via remote-SSH in VS Code. You can find more details on this approach on Stack Overflow .
Preliminary Work
Before proceeding, ensure your local public key is added to the SSH on the login node. Direct SSH to the GPU node should work seamlessly without requiring a password.
Local SSH Config File Setup
Here’s what your local .ssh/config
file should look like:
1 | #example |
After setting this up, refresh your VS Code SSH and select ‘computenode’ to open a server session where you can happily debug.
Potential Difficulties
Difficulty 1: Connection Failures
Even though you can connect via command-line SSH to computenode
, connecting through VS Code might fail. This could be due to a version conflict in VS Code or its extensions.
Solution:
Attempt to connect via command line and manually clear the VS Code server on the compute node:
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9ssh computenode
cd .vscode-server/
rm -rf *
ps -ef | grep vscode
kill -9 [process_ids] # Replace [process_ids] with the actual IDs shown
cd ..
rm -rf .vscode-server/
ps -ef | grep vscode
kill -9 [process_ids]After cleaning up, download and try using a different version of VS Code. Make sure to remove the old server files and let VS Code reinstall the server component.
Difficulty 2: Debugging Errors
When you attempt to debug using F5, errors might pop up indicating missing plugins or interpreters, suggesting a version mismatch.
For similar experiences, see this CSDN blog post .
Solution:
If you connect successfully but encounter issues when hitting F5 to debug, it could be another version issue. The solution is similar: switch to another version of VS Code after cleaning up old server files. Also, be mindful of any network or proxy issues that could be interfering.
Other remainders
Viewing Mac Public Key
If you need to verify your public key on a Mac, you can use the following commands:
1 | cd ~/.ssh |
Copy and paste your public key into the server’s .ssh/authorized_keys
file to enable password-less SSH access.
Issues with VPN
Switching VPN connections can lead to connectivity problems in VS Code. To troubleshoot, you may need to:
1 | ps -ef | grep vscode |
After clearing any potentially hanging processes, try reconnecting to the compute node using VS Code. If problems persist, verify your VPN settings and network configuration to ensure they are compatible with your remote access requirements. Adjusting the VPN settings or temporarily disabling the VPN might help identify whether it is the source of the connection issues.
Alternative Approaches: Caution Advised
While exploring remote development setups, I came across an approach that involves modifying JSON configurations (see GitHub issue ). However, I encountered similar problems as discussed in the issue and ultimately found the method unreliable.
Recommendation:
Due to the complexities and unresolved issues noted in the GitHub discussion, I recommend avoiding this JSON configuration approach for setting up remote environments in VS Code. Stick with proven SSH configurations for a more stable setup.
Additional Resources and Troubleshooting
conclusion
Changing the version until everything is feasible….
- Title: debug on gpu node
- Author: wy
- Created at : 2024-07-19 17:07:07
- Updated at : 2024-07-19 18:32:55
- Link: https://yuuee-www.github.io/blog/2024/07/19/debug-on-gpu-node/
- License: This work is licensed under CC BY-NC-SA 4.0.