multi-gpu training triggers CUDA out of memory error
Hi -
I am running into issues when going from single to multi-gpu training.  Specifically, if I switch the line
pl.Trainer(gpus=1, precision=16, distributed_backend='ddp')
to
pl.Trainer(gpus=4, precision=16, distributed_backend='ddp')
I get the dreaded CUDA out of memory error.  Is there any reason why the parallelism causes the GPU to receive more data?