Hello. I am currently using the 2 GPU machines in the lab.
The first one, it has 2 Titan V.
Second, the other has 4 Titan V.
When I train the same dataset but 2 times bigger batch size but 2 titan V result is better.
The network is Mobilenet V3 based network.
I have read some articles, and they said that Sync batch normalization could be helpful.
I use the Apex version of Sync batch normalization.
Preformatted textmodel = apex.parallel.convert_syncbn_model(model)
However, still, 2 GPUs have a better result.
So I am looking for another article. They said in some cases, the DDP is required if I use a lot of GPU.
Does anyone have the same experience when you use multi GPU training?
The second thought is the multi-scale training, I read other published paper with code. They use multi-scale training with multiple GPUs. Does this effects the segmentation result?
Thank you.