CUDA: Difference between revisions

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For tensorflow and pytorch, you may need to add <code>LD_LIBRARY_PATH=/usr/local/cuda/lib64</code> to your environment variables.<br>
For tensorflow and pytorch, you may need to add <code>LD_LIBRARY_PATH=/usr/local/cuda/lib64</code> to your environment variables.<br>
You can also do this in PyCharm.<br>
You can also do this in PyCharm.<br>
[[File:Pycharm LD LIBRARY PATH config.png| 200x200px]]
[[File:Pycharm LD LIBRARY PATH console config.png| 200x200px]]


==References==
==References==
* [https://devblogs.nvidia.com/even-easier-introduction-cuda/ An Even Easier Introduction To Cuda]
* [https://devblogs.nvidia.com/even-easier-introduction-cuda/ An Even Easier Introduction To Cuda]

Revision as of 18:55, 16 October 2019

Installation

Linux

Reference
For Ubuntu, install the latest nvidia drivers from the repo and install Cuda Toolkit separately without the drivers.
You may also want to install cuDnn
For tensorflow and pytorch, you may need to add LD_LIBRARY_PATH=/usr/local/cuda/lib64 to your environment variables.
You can also do this in PyCharm.

References