gap between single 2080ti GPU and double 2080ti GPU

[JackyZDHu]

Hi！thx to your work！My question is that when I train the spcl with default config from two 2080ti gpus to single 2080ti gpu，the result drops about 6% in mAP. So I want to know the reason about it, thank u !

[yxgeee]

The number of GPUs is sensitive in re-ID experiments, and I guess the main reason is the batch_size for BN layers. I conducted all the UDA re-ID experiments on 4 GPUs with a batch_size of 64, which means a mini-batch of 16 images are fed into BN. I did not try to train with 2 GPUs or 1 GPU. If you want to achieve better performance on one GPU, I think you need to tune the batch_size, the iters, and the learning rate.
For example, we use the following setup on 4 GPUs,

batch size: 64
iters: 400
learning rate: 0.00035

When adapting to one GPU, it's better to use

batch size: 64/4
iters: 400*4
learning rate: 0.00035/4

[JackyZDHu]

Thx to your reply! Cuz as usual ,single GPU always get better result than multi gpus due to BN ,so I was confused about my result. I'll try your suggestion to train again, Thank U very much!

[yxgeee]

Yes. On fully-supervised re-ID experiments, single GPU seems better. However, on unsupervised re-ID tasks, I found that 4 GPUs with a batch_size of 64 generally perform better.