ptrblck:

I’m not sure, if I understand the question correctly. What would you mean from disk? Do you mean the performance difference between the Kaggle kernels with their (free) GPU runtime vs. a bare metal machine? If so, I cannot comment on the performance of the free Kaggle kernels and am not sure what is being used currently.


In Docker, I’ve found that shared mounts sometimes have slow (particularly write) performance. So if the dataset lives outside Docker, reads might be slow?


Kaggle is using an approach where the users submit the predictions and will get a score based on a secret part of the submission samples.


But participants are provided the input data? We would prefer to avoid this.
I will look up Singularity