I’m focusing at the moment on a single GPU setup.
Running with batch size of 128:

/workspace/examples/imagenet# python main_fake.py -a resnet50 / --workers 10 --batch-size 128 --fp16

I get (after warmup):

Epoch: [2][170/782]     Time 0.235 (0.251)      Data 0.000 (0.015)      Loss 4.6797 (4.6478)    Prec@1 0.781 (0.978)    Prec@5 3.906 (4.889)
Epoch: [2][180/782]     Time 0.235 (0.250)      Data 0.000 (0.014)      Loss 4.6562 (4.6473)    Prec@1 1.562 (0.997)    Prec@5 4.688 (4.886)
Epoch: [2][190/782]     Time 0.235 (0.250)      Data 0.000 (0.013)      Loss 4.6992 (4.6475)    Prec@1 0.000 (1.006)    Prec@5 3.125 (4.884)
Epoch: [2][200/782]     Time 0.241 (0.249)      Data 0.000 (0.013)      Loss 4.6328 (4.6482)    Prec@1 0.781 (0.999)    Prec@5 7.812 (4.862)
Epoch: [2][210/782]     Time 0.241 (0.248)      Data 0.000 (0.012)      Loss 4.6250 (4.6478)    Prec@1 0.781 (0.989)    Prec@5 6.250 (4.858)
Epoch: [2][220/782]     Time 0.241 (0.248)      Data 0.000 (0.012)      Loss 4.6328 (4.6475)    Prec@1 3.125 (0.983)    Prec@5 7.031 (4.854)
Epoch: [2][230/782]     Time 0.241 (0.247)      Data 0.000 (0.011)      Loss 4.6797 (4.6472)    Prec@1 0.781 (0.991)    Prec@5 3.906 (4.880)
Epoch: [2][240/782]     Time 0.240 (0.247)      Data 0.000 (0.011)      Loss 4.6367 (4.6475)    Prec@1 0.781 (0.985)    Prec@5 7.031 (4.843)
Epoch: [2][250/782]     Time 0.235 (0.247)      Data 0.000 (0.010)      Loss 4.6562 (4.6473)    Prec@1 2.344 (0.990)    Prec@5 6.250 (4.846)
Epoch: [2][260/782]     Time 0.235 (0.246)      Data 0.000 (0.010)      Loss 4.6953 (4.6474)    Prec@1 1.562 (0.997)    Prec@5 2.344 (4.852)

so ~0.240 vs ~0.180 ??
btw, I can’t run the example with batch size 256. I get cuda error: out of memory (that’s even if I restart the container)
Any idea what’s wrong ?