What Do I Do If cudaCheckError Occurs During Training?
Symptom
The following error occurs when the training code is executed in a notebook:
cudaCheckError() failed : no kernel image is available for execution on the device
Possible Cause
Parameters arch and code in setup.py have not been set to match the GPU compute power.
Solution
For GP Vnt1 GPUs, the GPU computing power is -gencode arch=compute_70,code=[sm_70,compute_70]. Set the compilation parameters in setup.py accordingly.
Code Execution FAQs
- What Do I Do If a Notebook Instance Won't Run My Code?
- Why Does the Instance Break Down When dead kernel Is Displayed During Training Code Running?
- What Do I Do If cudaCheckError Occurs During Training?
- What Should I Do If DevEnviron Prompts Insufficient Space?
- Why Does the Notebook Instance Break Down When opencv.imshow Is Used?
- Why Cannot the Path of a Text File Generated in Windows OS Be Found In a Notebook Instance?
- What Do I Do If Files Fail to Be Saved in JupyterLab?
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