Running tensorflow on GPU cluster in virtualenv

Question

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()

exits with the following error:

(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

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 ?? ()

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

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 |
+-------------------------------+----------------------+----------------------+

Thanks for any help on this issue!

Answer 1

It's not finding CuDNN -

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

You need to have it installed. Please see the TensorFlow CUDA installation instructions

Answer 2

After untar the cudnn

[root@localhost cudnn]# cd include/
[root@localhost include]# mv cudnn.h /usr/local/cuda/include/
[root@localhost include]# cd ../lib64/
[root@localhost lib64]# mv * /usr/local/cuda/lib

And it is ok

[root@localhost ~]# python
Python 2.7.5 (default, Sep 15 2016, 22:37:39) 
[GCC 4.8.5 20150623 (Red Hat 4.8.5-4)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as f
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcublas.so.8.0 locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcudnn.so.5 locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcufft.so.8.0 locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcuda.so.1 locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcurand.so.8.0 locally
>>>