TensorflowGPU;只使用GPUMemory,不使用gpu计算能力

2024-04-26 14:16:43 发布

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又是一个Tensorflow GPU问题。我在GPU相关问题上做了很多研究,但是我没有找到一个合适的解决方案。如果我监督了一个,我真的很抱歉!

我已经安装了tensorflow gpu 1.7.0, Cuda V9.0和cuDNN v7.05用于Cuda V9.0。
我使用的是GTX1080 TI和AMD Ryzen 1700 CPU。
当“使用”GPU时,我可以看到已用GPU内存的大量增加(高达10GB)。但我看不到性能的任何提高或GPU使用量的增加(除了内存)

我得到以下输出。看来,GPU是公认的。

  Doom initialized.
2018-04-21 21:54:13.647638: I T:\src\github\tensorflow\tensorflow\core\platform\cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
2018-04-21 21:54:14.329891: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1344] Found device 0 with properties:
name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.683
pciBusID: 0000:24:00.0
totalMemory: 11.00GiB freeMemory: 9.09GiB
2018-04-21 21:54:14.337566: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1423] Adding visible gpu devices: 0
2018-04-21 21:56:24.735851: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:911] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-04-21 21:56:24.743510: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:917]      0
2018-04-21 21:56:24.746905: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:930] 0:   N
2018-04-21 21:56:24.751513: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1041] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 8804 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1080 Ti, pci bus id: 0000:24:00.0, compute capability: 6.1)
WARNING:tensorflow:From C:\Users\Gian-Andrea Heinrich\AppData\Local\conda\conda\envs\tensorflow6GPU\lib\site-packages\tensorflow\contrib\learn\python\learn\datasets\base.py:198: retry (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version.
Instructions for updating:
Use the retry module or similar alternatives.
Starting the training!

如果你能找到解决办法,我将不胜感激。


Tags: 内存coresrcgithubgpudevicetensorflowwith