forked from docs/doc-exports
Reviewed-by: Hasko, Vladimir <vladimir.hasko@t-systems.com> Co-authored-by: Lai, Weijian <laiweijian4@huawei.com> Co-committed-by: Lai, Weijian <laiweijian4@huawei.com>
1.7 KiB
1.7 KiB
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 Tesla V100 GPUs, the GPU compute power is -gencode arch=compute_70,code=[sm_70,compute_70]. Set the compilation parameters in setup.py accordingly.
Parent topic: Code Execution