Loss.backward() takes too much time

Questions
#1

Hi,

I started using DGL for NLP research. But there was a problem using DGL.

When I train my model with my PC, loss.backward() takes too much time. Same code works well when I use Google Colab. I think GPU/CUDA operation on DGL is not working properly on my PC. Other model without DGLGraph works well on my PC.

My PC setting (not working)

GPU : RTX3090
CUDA version : 11.1
python=3.9
pytorch=1.9.1
dgl=0.7.1

Can I know where the problem occured?

Thanks

#2

Hi,

How did you install the dgl, from source or pip? And how slow is it?

#3

I installed it using pip.
When I use Google Colab, it takes a second to train 1 step but when I use a PC, it takes 30 minutes to train.

#4

It’s weird. Are you using windows or linux on your PC? Does this only happen to backward computation, or also very slow for the forward computation?

#5

I use linux on my PC. And this only happen to backward computation.

#6

Were you able to reproduce this problem on other machines (other than your PC and Colab)? This indeed sounds weird.

#7

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