- HOW TO INSTALL CUDA 9.0 ON UBUNTU 16.04 HOW TO
- HOW TO INSTALL CUDA 9.0 ON UBUNTU 16.04 INSTALL
- HOW TO INSTALL CUDA 9.0 ON UBUNTU 16.04 DRIVERS
- HOW TO INSTALL CUDA 9.0 ON UBUNTU 16.04 UPDATE
- HOW TO INSTALL CUDA 9.0 ON UBUNTU 16.04 UPGRADE
HOW TO INSTALL CUDA 9.0 ON UBUNTU 16.04 INSTALL
This tutorial was tested on a fresh install of Ubuntu 16.04 with a GeForce GTX 780, GTX 970m & Quadro K2000M. There you have it, you should now have TensorFlow installed on your computer.
HOW TO INSTALL CUDA 9.0 ON UBUNTU 16.04 HOW TO
TensorFlow also has instructions on how to do a basic test and a list of common installation problems.
Also make sure your Terminal is not in the ‘tensorflow’ directory. $ sudo pip install /tmp/tensorflow_pkg/tensorflowĬlose all your terminals and open a new terminal to test. # with no spaces after tensorflow hit tab before hitting enter to fill in blanksįor Python 2 (remove sudo if using a virtualenv) $ sudo pip3 install /tmp/tensorflow_pkg/tensorflow To Install Using Python 3 (remove sudo if using a virtualenv) This will build the pip package required for installing TensorFlow in your /tmp/ folder $ bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg If you want to build TensorFlow with GPU support enter: $ bazel build -config=opt -config=cuda //tensorflow/tools/pip_package:build_pip_packageįor CPU only enter: $ bazel build -config=opt //tensorflow/tools/pip_package:build_pip_package Warning Resource Intensive I recommend having at least 8GB of computer memory. If all was done correctly you should see: INFO: All external dependencies fetched successfully. You can find the compute capability of your device at:
(has anyone tested this? ping me if so!)ĭo you wish to build TensorFlow with CUDA support? $ Y Unless you have a Radeon graphic card you can say no to OpenCL support. Default is :įor Python 2 use default or If you wish to build for Python 3 enter: $ /usr/local/lib/python3.5/dist-packages Please input the desired Python library path to use. :įor Python 2 use default or If you wish to build for Python 3 enter: $ /usr/bin/python3.5 Use defaults by pressing enter for all except: $ cd ~/tensorflowĬonfigure TensorFlow Installation $ cd ~/tensorflow
Unless you want absolute bleeding edge I highly recommend checking-out to the latest branch rather than master.
HOW TO INSTALL CUDA 9.0 ON UBUNTU 16.04 UPGRADE
$ sudo apt-get upgrade bazel Clone Tensorflow $ cd ~ Instructions also on Bazel website $ echo "deb stable jdk1.8" | sudo tee /etc/apt//bazel.list bashrc file: $ source ~/.bashrc Install Bazel Once you save and close the text file you can return to your original terminal and type this command to reload your. This will open your bash file in a text editor which you will scroll to the bottom and add these lines: export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64" $ sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn* $ sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64 $ sudo cp cuda/include/cudnn.h /usr/local/cuda/include To install CudNN download cudNN v6.0 for Cuda 8.0 from Nvidia website and extract into /usr/local/cuda via: $ tar -xzvf cudnn-8.0-linux-圆4-v6.0.tgz This will install cuda into: /usr/local/cuda MAKE SURE YOU SAY NO TO INSTALLING NVIDIA DRIVERS! Also make sure you select yes to creating a symbolic link to your cuda directory. To install the Nvidia Toolkit download base installation.
If you experience any troubles booting linux or logging in: try disabling fast & safe boot in your bios and modifying your grub boot options to enable nomodeset.
HOW TO INSTALL CUDA 9.0 ON UBUNTU 16.04 DRIVERS
Once installed using additional drivers restart your computer. $ sudo add-apt-repository ppa:graphics-drivers/ppa
HOW TO INSTALL CUDA 9.0 ON UBUNTU 16.04 UPDATE
You must also have the 367 (or later) NVidia drivers installed, this can easily be done from Ubuntu’s built in additional drivers after you update your driver packages. Paste each line one at a time (without the $) using Shift + Ctrl + V $ sudo apt-get install openjdk-8-jdk git python-dev python3-dev python-numpy python3-numpy python-six python3-six build-essential python-pip python3-pip python-virtualenv swig python-wheel python3-wheel libcurl3-dev libcupti-dev Update & Install Nvidia Drivers Open a terminal by pressing Ctrl + Alt + T Getting started I am going to assume you know some of the basics of using a terminal in Linux. In order to use TensorFlow with GPU support you must have a Nvidia graphic card with a minimum compute capability of 3.0. If you prefer to build from sources using Ubuntu 14.04 please see my other tutorial. I much prefer to install Tensorflow using Anaconda Python and you can find a tutorial for that here. In this tutorial I will be going through the process of building the latest TensorFlow from sources for Ubuntu 16.04. I have decided to move my blog to my github page, this post will no longer be updated here.
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