@ptrblck Thanks for the reply. I have found the trick. I’m not a professional in CPU field. It seems that something with swap does slow the tensor transfer speed.
Our cloud machine has two NUMA nodes. The docker parameter --cpus=4 doesn’t allocate 4 cpu cores to the job, but load every cores balanced under cpu rate 4/cpu_core_nums. To run the training job correctly, the docker parameter --cpuset-cpus should be used.