Tensorflow not using GPU

Question

I'm trying to run the example seq2seq by Tensorflow, but it won't use the GPU. Here are the step I took to install Tensorflow on a Linux system with Tesla K20x

git clone --recurse-submodules https://github.com/tensorflow/tensorflow
./configure # Yes GPU
bazel build -c opt --config=cuda //tensorflow/cc:tutorials_example_trainer
bazel-bin/tensorflow/cc/tutorials_example_trainer --use_gpu # The GPU is being used)
bazel build -c opt --config=cuda //tensorflow/tools/pip_package:build_pip_package
bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg
pip install /tmp/tensorflow_pkg/tensorflow-0.5.0-cp27-none-linux_x86_64.whl

After all of this step, I have tensorflow installed. I then try to run the seq2seq example, by

bazel run -c opt //tutorials/models/rnn/translate:translate

but it will not use the GPU. I then try the example

bazel-bin/tensorflow/cc/tutorials_example_trainer --use_gpu

and it gives an error

bazel-bin/tensorflow/cc/tutorials_example_trainer: error while loading shared libraries: /path/to/home/.cache/bazel/_bazel_hduong/9e8a6e75473e7bf5c9d1c8a084e2a0e9/tensorflow/bazel-out/local_linux-opt/bin/tensorflow/cc/../../_solib_local/_U_S_Sthird_Uparty_Sgpus_Scuda_Ccudart___Uthird_Uparty_Sgpus_Scuda_Slib64/libcudart.so.7.0: file too short

Was wondering if anyone know what might cause the program to not use the GPU? Any help is appreciated.

Thank you.

you would need to run ./configure inside tensorflow folder. Then you can mention your cuda driver's path and don't forget to mention the cuda compatibility version. — PixelPioneer
– PixelPioneer, Commented Aug 18, 2016 at 20:20

mrry · Accepted Answer · 2015-12-17 18:23:11Z

5

The issue looks to be that when you bazel run the translation example, it rebuilds without GPU support. Try adding --config=cuda to the bazel run command, as follows:

$ bazel run -c opt --config=cuda //tensorflow/models/rnn/translate:translate

Without this option, Bazel will recompile the entire TensorFlow runtime without GPU support, and use this version when it runs the example application.

answered Dec 17, 2015 at 18:23

mrry

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ram · Accepted Answer · 2016-07-31 14:17:12Z

1

it occurs since the cuda is not properly linked. Enter the following command in the terminal

sudo ldconfig /usr/local/cuda/lib64

answered Jul 31, 2016 at 14:17

ram

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BenjiBB · Accepted Answer · 2017-10-28 12:55:46Z

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I’m guessing you should install it with a GPU version

pip install tensorflow-gpu

answered Oct 28, 2017 at 12:55

BenjiBB

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