在virtualenv中的GPU群集上运行Tensorflow

我按照以下说明.问题是，启动会话时出现分段错误.也就是说，这段代码:

I installed the GPU version of tensorflow in a virtualenv following these instructions. The problem is, I am getting a segmentation fault upon starting a session. That is, this code:

import tensorflow as tf
sess = tf.InteractiveSession()

退出并出现以下错误:

(tesnsorflowenv)user@machine$ python testtensorflow.py 
I tensorflow/stream_executor/dso_loader.cc:101] successfully opened CUDA library libcublas.so.7.0 locally
I tensorflow/stream_executor/dso_loader.cc:93] Couldn't open CUDA library libcudnn.so.6.5. LD_LIBRARY_PATH: :/vol/cuda/7.0.28/lib64
I tensorflow/stream_executor/cuda/cuda_dnn.cc:1382] Unable to load cuDNN DSO
I tensorflow/stream_executor/dso_loader.cc:101] successfully opened CUDA library libcufft.so.7.0 locally
I tensorflow/stream_executor/dso_loader.cc:101] successfully opened CUDA library libcuda.so locally
I tensorflow/stream_executor/dso_loader.cc:101] successfully opened CUDA library libcurand.so.7.0 locally
I tensorflow/core/common_runtime/local_device.cc:40] Local device intra op parallelism threads: 40
Segmentation fault

我尝试使用gdb进行更深入的研究，但仅获得以下附加输出:

I tried to dig deeper using gdb but only got the following additional outputs:

[New Thread 0x7fffdf880700 (LWP 32641)]
[New Thread 0x7fffdf07f700 (LWP 32642)]
... lines omitted 
[New Thread 0x7fffadffb700 (LWP 32681)]
[Thread 0x7fffadffb700 (LWP 32681) exited]
Program received signal SIGSEGV, Segmentation fault.
0x0000000000000000 in ?? ()

任何想法在这里发生了什么以及如何解决?

Any ideas what is happening here and how to fix it?

这是nvidia-smi的输出:

Here is the output of nvidia-smi:

+------------------------------------------------------+                       
| NVIDIA-SMI 352.63     Driver Version: 352.63         |                       
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  Tesla K80           On   | 0000:06:00.0     Off |                    0 |
| N/A   65C    P0   142W / 149W |    235MiB / 11519MiB |     81%   E. Process |
+-------------------------------+----------------------+----------------------+
|   1  Tesla K80           On   | 0000:07:00.0     Off |                    0 |
| N/A   25C    P8    30W / 149W |     55MiB / 11519MiB |      0%   E. Process |
+-------------------------------+----------------------+----------------------+
|   2  Tesla K80           On   | 0000:0D:00.0     Off |                    0 |
| N/A   27C    P8    26W / 149W |     55MiB / 11519MiB |      0%   Prohibited |
+-------------------------------+----------------------+----------------------+
|   3  Tesla K80           On   | 0000:0E:00.0     Off |                    0 |
| N/A   25C    P8    28W / 149W |     55MiB / 11519MiB |      0%   E. Process |
+-------------------------------+----------------------+----------------------+
|   4  Tesla K80           On   | 0000:86:00.0     Off |                    0 |
| N/A   46C    P0    85W / 149W |    206MiB / 11519MiB |     97%   E. Process |
+-------------------------------+----------------------+----------------------+
|   5  Tesla K80           On   | 0000:87:00.0     Off |                    0 |
| N/A   27C    P8    29W / 149W |     55MiB / 11519MiB |      0%   E. Process |
+-------------------------------+----------------------+----------------------+
|   6  Tesla K80           On   | 0000:8D:00.0     Off |                    0 |
| N/A   28C    P8    26W / 149W |     55MiB / 11519MiB |      0%   Prohibited |
+-------------------------------+----------------------+----------------------+
|   7  Tesla K80           On   | 0000:8E:00.0     Off |                    0 |
| N/A   23C    P8    30W / 149W |     55MiB / 11519MiB |      0%   E. Process |
+-------------------------------+----------------------+----------------------+

感谢您在此问题上的任何帮助！

Thanks for any help on this issue!