Tensorflow没有分配完整的GPU内存 [英] Tensorflow doesn't allocate full GPU memory
问题描述
Tensorflow默认情况下分配所有GPU内存，但是我的新设置实际上仅为9588 MiB/11264 MiB.我希望能像以前的设置一样在11.000MiB左右.
Tensorflow allocates all of GPU memory per default, but my new settings actually only are 9588 MiB / 11264 MiB. I expected around 11.000MiB like my old settings.
Tensorflow信息在这里:
Tensorflow information is here:
$ from tensorflow.python.client import device_lib
$ print(device_lib.list_local_devices())
[name: "/cpu:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation: 9709578925658430097
, name: "/gpu:0"
device_type: "GPU"
memory_limit: 9273834701
locality {
bus_id: 1
}
incarnation: 16668416364446126258
physical_device_desc: "device: 0, name: GeForce GTX 1080 Ti, pci bus id: 0000:03:00.0"
, name: "/gpu:1"
device_type: "GPU"
memory_limit: 9273834701
locality {
bus_id: 1
}
incarnation: 2094938711079475130
physical_device_desc: "device: 1, name: GeForce GTX 1080 Ti, pci bus id: 0000:04:00.0"
]
nvidia-smi.exe说:
nvidia-smi.exe says:
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 385.41 Driver Version: 385.41 |
|-------------------------------+----------------------+----------------------+
| GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce GTX 108... WDDM | 00000000:03:00.0 Off | N/A |
| 23% 35C P8 13W / 250W | 9284MiB / 11264MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 1 GeForce GTX 108... WDDM | 00000000:04:00.0 Off | N/A |
| 23% 38C P2 55W / 250W | 9146MiB / 11264MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 1280 C+G ...mmersiveControlPanel\SystemSettings.exe N/A |
| 0 1448 C ...ers\Administrator\Anaconda3\pythonw.exe N/A |
| 0 1560 C+G Insufficient Permissions N/A |
| 0 4120 C+G ...6)\Google\Chrome\Application\chrome.exe N/A |
| 0 4580 C+G C:\Windows\explorer.exe N/A |
| 0 5188 C+G ...t_cw5n1h2txyewy\ShellExperienceHost.exe N/A |
| 0 5324 C+G ...dows.Cortana_cw5n1h2txyewy\SearchUI.exe N/A |
| 1 1228 C+G Insufficient Permissions N/A |
| 1 1244 C+G Insufficient Permissions N/A |
| 1 1448 C ...ers\Administrator\Anaconda3\pythonw.exe N/A |
+-----------------------------------------------------------------------------+
我的环境是这样:
操作系统:Windows10 库:python 3.6，keras 2.0.8，tensorflow-gpu 1.3.0，CUDA8.0 CUDNN6.0
OS: Windows10 library: python 3.6, keras 2.0.8, tensorflow-gpu 1.3.0, CUDA8.0 CUDNN6.0
有人知道原因吗?
推荐答案
必须使用TCC驱动程序，以避免Windows保留某些VRAM.您可能正在使用WDDM驱动程序.
It is necessary to use the TCC driver to avoid windows reserving some of the VRAM. You may be using the WDDM driver.
这是TCC上的页面: https://docs.nvidia.com/gameworks/content/developertools/desktop/nsight/tesla_compute_cluster.htm
Here is the page on TCC: https://docs.nvidia.com/gameworks/content/developertools/desktop/nsight/tesla_compute_cluster.htm
Here is a related question: How can I use 100% of VRAM on a secondary GPU from a single process on windows 10?
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