我买了Alienware Gpu 1070用于深度学习。
但是在某种程度上简单的Tensorflow运行比我在旧的唯一的旧旧戴尔计算机上运行Tensorflow时要慢。
我得到了
I tensorflow/core/common_runtime/gpu/gpu_init.cc:126] DMA: 0
I tensorflow/core/common_runtime/gpu/gpu_init.cc:136] 0: Y
I tensorflow/core/common_runtime/gpu/gpu_device.cc:806] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 1070, pci bus id: 0000:01:00.0)
E tensorflow/stream_executor/cuda/cuda_driver.cc:965] failed to allocate 123.25M (129236992 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
用于简单的Tensorflow运行。
我的nvidia-smi设置如下
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 384.81 Driver Version: 384.81 |
|-------------------------------+----------------------+----------------------+
| 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 1070 Off | 00000000:01:00.0 On | N/A |
| N/A 49C P0 31W / N/A | 7915MiB / 8105MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 1053 G /usr/lib/xorg/Xorg 299MiB |
| 0 1985 G compiz 257MiB |
| 0 26444 G ...-token=35E56369B532703BC65298BE4DF4A2E8 121MiB |
| 0 27364 C /home/jake/tensorflow/bin/python3 6997MiB |
| 0 29540 C /home/jake/tensorflow/bin/python3 235MiB |
+-----------------------------------------------------------------------------+
我无法猜测为什么我的新GPU计算机发出如此多的声音并且比我的旧计算机慢得多。
我是否应该为使用GPU进行深度学习做其他设置？