So thats what I did - except for some reason the utilization never goes above 0. I couldn’t really figure that out
import os
os.environ["CUDA_VISIBLE_DEVICES"] = "0,1,2,3,4,5"

[0] Tesla K80        | 49'C,   0 % |  1356 / 11439 MB | ubuntu(650M) ubuntu(701M)
[1] Tesla K80        | 41'C,   0 % |   214 / 11439 MB | ubuntu(210M)
[2] Tesla K80        | 47'C,   0 % |   214 / 11439 MB | ubuntu(210M)
[3] Tesla K80        | 42'C,   0 % |   214 / 11439 MB | ubuntu(210M)
[4] Tesla K80        | 47'C,   0 % |   214 / 11439 MB | ubuntu(210M)
[5] Tesla K80        | 42'C,   0 % |   214 / 11439 MB | ubuntu(210M)
[6] Tesla K80        | 42'C,   0 % |     2 / 11439 MB |
[7] Tesla K80        | 36'C,   0 % |     2 / 11439 MB |

if typ == 'RNN':
    netD = torch.nn.DataParallel(netD, list(range(6)))