I have the same problem. When I load the same transformer model (Roberta-Large)  on Titan X and V100 I get vastly different results:

Gradient Checkpointing True, fp16 off, TitanX:   8034G
Gradient Checkpointing True, fp16 off, V100:    10861G
Gradient Checkpointing True, fp16 on, V100:    10613G

I tried with same cuda/cudnn on both machines (Tried Cuda 10.1/10.2, and cudnn 7605/7603). I also tried both pytorch 1.6 and 1.3. It seems there are some Volta specific kernels that consume more memory on V100?  Does anyone know how to reduce the GPU memory consumption on the Volta cards? I don’t mind sacrificing some speed in my use case.