使用命令nvidia-smi:
➜ ~ nvidia-smi
Tue May 14 09:47:51 2019
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 375.66 Driver Version: 375.66 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce GTX 1080 Off | 0000:02:00.0 Off | N/A |
| 27% 39C P8 10W / 180W | 0MiB / 8113MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 1 GeForce GTX 1080 Off | 0000:03:00.0 Off | N/A |
| 40% 60C P2 41W / 180W | 7789MiB / 8114MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 2 GeForce GTX 1080 Off | 0000:82:00.0 Off | N/A |
| 28% 42C P8 10W / 180W | 0MiB / 8114MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 3 GeForce GTX 1080 Off | 0000:83:00.0 Off | N/A |
| 30% 45C P8 11W / 180W | 0MiB / 8114MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 1 9091 C python 7787MiB |
+-----------------------------------------------------------------------------+
GPU是动态创建的，默认不指定设备时，会占用所有的设备，但是可能需求并没有这么多。通常的做法是指定端口，有两种方式：
1、命令行指定：添加CUDA_VISIBLE_DEVICES=设备号。注意：VISIBLE不要写错了，DEVICES一定记得加S，否则会指定失败。
CUDA_VISABLE_DEVICES=1 python script.py
2、脚本中指定：对于python脚本，可在脚本中指定环境参数：
if GPU_device:
os.environ['CUDA_VISIBLE_DEVICES'] = GPU_device