我使用特斯拉k80 GPU为TensorFlow运行了卷积神经网络的示例代码。
$ python cifar10_multi_gpu_train.py --batch_size 64 --num_gpus 2
Then I've checked a memory usage of GPU's. The result is below.
$ nvidia-smi
Mon Oct 31 16:34:15 2016
+------------------------------------------------------+
| NVIDIA-SMI 352.93 Driver Version: 352.93 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 Quadro K420 Off | 0000:01:00.0 On | N/A |
| 25% 45C P0 N/A / N/A | 264MiB / 1023MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 1 Tesla K80 Off | 0000:04:00.0 Off | 0 |
| N/A 41C P0 66W / 149W | 11022MiB / 11519MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 2 Tesla K80 Off | 0000:05:00.0 Off | 0 |
| N/A 37C P0 67W / 149W | 130MiB / 11519MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 8757 C python 8MiB |
| 0 13398 G /usr/bin/Xorg 92MiB |
| 0 14355 G /usr/bin/gnome-shell 146MiB |
| 1 8757 C python 10956MiB |
| 2 8757 C python 64MiB |
+-----------------------------------------------------------------------------+
“GPU 1”的内存使用量为11Gb,约为12Gb的95%。但“GPU 2”的内存使用量仅为64Mb。 你能告诉我如何在Tesla K80和TensorFlow上同时使用GPU的内存吗?