Comments (4)
Would it be faster if using 2 GPUs? Or does increasing batch size solve this issue? I am trying to figure out whether the problem is because of using more than 2 GPUs, or simply because the batch size you set is not large enough.
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Sorry for the late replay.
The max-tokens and max-sentences were set to 32/24 and 39000/26000, respectively for the transformer/conv_lstm recipes. So it is not the problem. However, increasing the "update_freq" to 5 mades things a little better.
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.51.05 Driver Version: 450.51.05 CUDA Version: 11.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Tesla V100-SXM2... On | 00000000:85:00.0 Off | 0 |
| N/A 51C P0 263W / 300W | 13936MiB / 16160MiB | 97% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 Tesla V100-SXM2... On | 00000000:86:00.0 Off | 0 |
| N/A 54C P0 267W / 300W | 13842MiB / 16160MiB | 84% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 2 Tesla V100-SXM2... On | 00000000:89:00.0 Off | 0 |
| N/A 59C P0 277W / 300W | 13868MiB / 16160MiB | 81% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 3 Tesla V100-SXM2... On | 00000000:8A:00.0 Off | 0 |
| N/A 53C P0 274W / 300W | 8734MiB / 16160MiB | 88% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
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Hmm, it seems that the bottle-neck is from when collecting gradients/stats across multiple GPUs in backprop. I don't have enough computing resources to try 4 GPUs, but I heard from someone else who tried 4 GTX 2080 GPUs in a SunGirdEngine environment that they didn't encounter such issue. So I am sorry I am unable to help out on this. But If a larger update_freq could help, maybe you can reduce the batch size accordingly so that the effective batch size for each update remain the same as when update_freq=1?
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Thanks for the reminder. I will reduce the batch size.
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