diff --git a/install/install_c.md b/install/install_c.md
index 8c165aa..1abd840 100644
--- a/install/install_c.md
+++ b/install/install_c.md
@@ -38,7 +38,7 @@ enable TensorFlow for C:
          OS="linux" # Change to "darwin" for macOS
          TARGET_DIRECTORY="/usr/local"
          curl -L \
-           "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-${OS}-x86_64-1.8.0-rc1.tar.gz" |
+           "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-${OS}-x86_64-1.8.0.tar.gz" |
            sudo tar -C $TARGET_DIRECTORY -xz
 
      The `tar` command extracts the TensorFlow C library into the `lib`
diff --git a/install/install_go.md b/install/install_go.md
index 26cbcc9..52a2a3f 100644
--- a/install/install_go.md
+++ b/install/install_go.md
@@ -38,7 +38,7 @@ steps to install this library and enable TensorFlow for Go:
          TF_TYPE="cpu" # Change to "gpu" for GPU support
          TARGET_DIRECTORY='/usr/local'
          curl -L \
-           "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-$(go env GOOS)-x86_64-1.8.0-rc1.tar.gz" |
+           "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-$(go env GOOS)-x86_64-1.8.0.tar.gz" |
          sudo tar -C $TARGET_DIRECTORY -xz
 
      The `tar` command extracts the TensorFlow C library into the `lib`
diff --git a/install/install_java.md b/install/install_java.md
index 1b0bbdb..700ae01 100644
--- a/install/install_java.md
+++ b/install/install_java.md
@@ -36,7 +36,7 @@ following to the project's `pom.xml` to use the TensorFlow Java APIs:
 <dependency>
   <groupId>org.tensorflow</groupId>
   <artifactId>tensorflow</artifactId>
-  <version>1.8.0-rc1</version>
+  <version>1.8.0</version>
 </dependency>
 ```
 
@@ -65,7 +65,7 @@ As an example, these steps will create a Maven project that uses TensorFlow:
                <dependency>
                  <groupId>org.tensorflow</groupId>
                  <artifactId>tensorflow</artifactId>
-                 <version>1.8.0-rc1</version>
+                 <version>1.8.0</version>
                </dependency>
              </dependencies>
          </project>
@@ -123,12 +123,12 @@ instead:
 <dependency>
   <groupId>org.tensorflow</groupId>
   <artifactId>libtensorflow</artifactId>
-  <version>1.8.0-rc1</version>
+  <version>1.8.0</version>
 </dependency>
 <dependency>
   <groupId>org.tensorflow</groupId>
   <artifactId>libtensorflow_jni_gpu</artifactId>
-  <version>1.8.0-rc1</version>
+  <version>1.8.0</version>
 </dependency>
 ```
 
@@ -147,7 +147,7 @@ refer to the simpler instructions above instead.
 Take the following steps to install TensorFlow for Java on Linux or macOS:
 
   1. Download
-     [libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.8.0-rc1.jar),
+     [libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.8.0.jar),
      which is the TensorFlow Java Archive (JAR).
 
   2. Decide whether you will run TensorFlow for Java on CPU(s) only or with
@@ -166,7 +166,7 @@ Take the following steps to install TensorFlow for Java on Linux or macOS:
          OS=$(uname -s | tr '[:upper:]' '[:lower:]')
          mkdir -p ./jni
          curl -L \
-           "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-${TF_TYPE}-${OS}-x86_64-1.8.0-rc1.tar.gz" |
+           "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-${TF_TYPE}-${OS}-x86_64-1.8.0.tar.gz" |
            tar -xz -C ./jni
 
 ### Install on Windows
@@ -174,10 +174,10 @@ Take the following steps to install TensorFlow for Java on Linux or macOS:
 Take the following steps to install TensorFlow for Java on Windows:
 
   1. Download
-     [libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.8.0-rc1.jar),
+     [libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.8.0.jar),
      which is the TensorFlow Java Archive (JAR).
   2. Download the following Java Native Interface (JNI) file appropriate for
-     [TensorFlow for Java on Windows](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-cpu-windows-x86_64-1.8.0-rc1.zip).
+     [TensorFlow for Java on Windows](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-cpu-windows-x86_64-1.8.0.zip).
   3. Extract this .zip file.
 
 
@@ -225,7 +225,7 @@ must be part of your `classpath`. For example, you can include the
 downloaded `.jar` in your `classpath` by using the `-cp` compilation flag
 as follows:
 
-<pre><b>javac -cp libtensorflow-1.8.0-rc1.jar HelloTF.java</b></pre>
+<pre><b>javac -cp libtensorflow-1.8.0.jar HelloTF.java</b></pre>
 
 
 ### Running
@@ -239,11 +239,11 @@ two files are available to the JVM:
 For example, the following command line executes the `HelloTF` program on Linux
 and macOS X:
 
-<pre><b>java -cp libtensorflow-1.8.0-rc1.jar:. -Djava.library.path=./jni HelloTF</b></pre>
+<pre><b>java -cp libtensorflow-1.8.0.jar:. -Djava.library.path=./jni HelloTF</b></pre>
 
 And the following command line executes the `HelloTF` program on Windows:
 
-<pre><b>java -cp libtensorflow-1.8.0-rc1.jar;. -Djava.library.path=jni HelloTF</b></pre>
+<pre><b>java -cp libtensorflow-1.8.0.jar;. -Djava.library.path=jni HelloTF</b></pre>
 
 If the program prints <tt>Hello from <i>version</i></tt>, you've successfully
 installed TensorFlow for Java and are ready to use the API.  If the program
diff --git a/install/install_linux.md b/install/install_linux.md
index f19f827..16a232e 100644
--- a/install/install_linux.md
+++ b/install/install_linux.md
@@ -48,7 +48,7 @@ must be installed on your system:
     Toolkit.
   * The libcupti-dev library, which is the NVIDIA CUDA Profile Tools Interface.
     This library provides advanced profiling support. To install this library,
-    issue the following command for CUDA Toolkit >= 8.0:
+    issue the following command for CUDA Toolkit >= 9.0:
 
     <pre>
     $ <b>sudo apt-get install cuda-command-line-tools</b>
@@ -65,16 +65,38 @@ must be installed on your system:
     <pre>
     $ <b>sudo apt-get install libcupti-dev</b>
     </pre>
+
   * **[OPTIONAL]**  For optimized inferencing performance, you can also install
-    NVIDIA TensorRT 3.0. For details, see
-    [NVIDIA's TensorRT documentation](http://docs.nvidia.com/deeplearning/sdk/tensorrt-install-guide/index.html#installing-tar).
-    Only steps 1-4 in the TensorRT Tar File installation instructions are
-    required for compatibility with TensorFlow; the Python package installation
-    in steps 5 and 6 can be omitted. Detailed installation instructions can be found at [package documentataion](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/tensorrt#installing-tensorrt-304)
+    **NVIDIA TensorRT 3.0**. The minimal set of TensorRT runtime components needed
+    for use with the pre-built `tensorflow-gpu` package can be installed as follows:
+
+    <pre>
+    $ <b>wget https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1404/x86_64/nvinfer-runtime-trt-repo-ubuntu1404-3.0.4-ga-cuda9.0_1.0-1_amd64.deb</b>
+    $ <b>sudo dpkg -i nvinfer-runtime-trt-repo-ubuntu1404-3.0.4-ga-cuda9.0_1.0-1_amd64.deb</b>
+    $ <b>sudo apt-get update</b>
+    $ <b>sudo apt-get install -y --allow-downgrades libnvinfer-dev libcudnn7-dev=7.0.5.15-1+cuda9.0 libcudnn7=7.0.5.15-1+cuda9.0</b>
+    </pre>
 
     **IMPORTANT:** For compatibility with the pre-built `tensorflow-gpu`
-    package, please use the Ubuntu **14.04** tar file package of TensorRT
-    even when installing onto an Ubuntu 16.04 system.   
+    package, please use the Ubuntu **14.04** package of TensorRT as shown above,
+    even when installing onto an Ubuntu 16.04 system.<br/>
+    <br/>
+    To build the TensorFlow-TensorRT integration module from source rather than
+    using pre-built binaries, see the [module documentation](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/tensorrt#using-tensorrt-in-tensorflow).
+    For detailed TensorRT installation instructions, see [NVIDIA's TensorRT documentation](http://docs.nvidia.com/deeplearning/sdk/tensorrt-install-guide/index.html).<br/>
+    <br/>
+    To avoid cuDNN version conflicts during later system upgrades, you can hold
+    the cuDNN version at 7.0.5:
+
+    <pre>
+    $ <b> sudo apt-mark hold libcudnn7 libcudnn7-dev</b>
+    </pre>
+
+    To later allow upgrades, you can remove the hold:
+
+    <pre>
+    $ <b> sudo apt-mark unhold libcudnn7 libcudnn7-dev</b>
+    </pre>
 
 If you have an earlier version of the preceding packages, please upgrade to
 the specified versions. If upgrading is not possible, then you may still run
@@ -194,7 +216,7 @@ Take the following steps to install TensorFlow with Virtualenv:
      Virtualenv environment:
 
      <pre>(tensorflow)$ <b>pip3 install --upgrade \
-     https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0rc1-cp34-cp34m-linux_x86_64.whl</b></pre>
+     https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0-cp34-cp34m-linux_x86_64.whl</b></pre>
 
 If you encounter installation problems, see
 [Common Installation Problems](#common_installation_problems).
@@ -299,7 +321,7 @@ take the following steps:
 
      <pre>
      $ <b>sudo pip3 install --upgrade \
-     https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0rc1-cp34-cp34m-linux_x86_64.whl</b>
+     https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0-cp34-cp34m-linux_x86_64.whl</b>
      </pre>
 
      If this step fails, see
@@ -485,7 +507,7 @@ Take the following steps to install TensorFlow in an Anaconda environment:
 
      <pre>
      (tensorflow)$ <b>pip install --ignore-installed --upgrade \
-     https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0rc1-cp34-cp34m-linux_x86_64.whl</b></pre>
+     https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0-cp34-cp34m-linux_x86_64.whl</b></pre>
 
 <a name="ValidateYourInstallation"></a>
 ## Validate your installation
@@ -659,14 +681,14 @@ This section documents the relevant values for Linux installations.
 CPU only:
 
 <pre>
-https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0rc1-cp27-none-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0-cp27-none-linux_x86_64.whl
 </pre>
 
 
 GPU support:
 
 <pre>
-https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.8.0rc1-cp27-none-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.8.0-cp27-none-linux_x86_64.whl
 </pre>
 
 Note that GPU support requires the NVIDIA hardware and software described in
@@ -678,14 +700,14 @@ Note that GPU support requires the NVIDIA hardware and software described in
 CPU only:
 
 <pre>
-https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0rc1-cp34-cp34m-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0-cp34-cp34m-linux_x86_64.whl
 </pre>
 
 
 GPU support:
 
 <pre>
-https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.8.0rc1-cp34-cp34m-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.8.0-cp34-cp34m-linux_x86_64.whl
 </pre>
 
 Note that GPU support requires the NVIDIA hardware and software described in
@@ -697,14 +719,14 @@ Note that GPU support requires the NVIDIA hardware and software described in
 CPU only:
 
 <pre>
-https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0rc1-cp35-cp35m-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0-cp35-cp35m-linux_x86_64.whl
 </pre>
 
 
 GPU support:
 
 <pre>
-https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.8.0rc1-cp35-cp35m-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.8.0-cp35-cp35m-linux_x86_64.whl
 </pre>
 
 
@@ -716,14 +738,14 @@ Note that GPU support requires the NVIDIA hardware and software described in
 CPU only:
 
 <pre>
-https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0rc1-cp36-cp36m-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0-cp36-cp36m-linux_x86_64.whl
 </pre>
 
 
 GPU support:
 
 <pre>
-https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.8.0rc1-cp36-cp36m-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.8.0-cp36-cp36m-linux_x86_64.whl
 </pre>
 
 
diff --git a/install/install_mac.md b/install/install_mac.md
index ff6c2f5..c79075b 100644
--- a/install/install_mac.md
+++ b/install/install_mac.md
@@ -119,7 +119,7 @@ Take the following steps to install TensorFlow with Virtualenv:
      TensorFlow in the active Virtualenv is as follows:
 
      <pre> $ <b>pip3 install --upgrade \
-     https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.8.0rc1-py3-none-any.whl</b></pre>
+     https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.8.0-py3-none-any.whl</b></pre>
 
 If you encounter installation problems, see
 [Common Installation Problems](#common-installation-problems).
@@ -242,7 +242,7 @@ take the following steps:
      issue the following command:
 
      <pre> $ <b>sudo pip3 install --upgrade \
-     https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.8.0rc1-py3-none-any.whl</b> </pre>
+     https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.8.0-py3-none-any.whl</b> </pre>
 
      If the preceding command fails, see
      [installation problems](#common-installation-problems).
@@ -350,7 +350,7 @@ Take the following steps to install TensorFlow in an Anaconda environment:
      TensorFlow for Python 2.7:
 
      <pre> (<i>targetDirectory</i>)$ <b>pip install --ignore-installed --upgrade \
-     https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.8.0rc1-py2-none-any.whl</b></pre>
+     https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.8.0-py2-none-any.whl</b></pre>
 
 
 <a name="ValidateYourInstallation"></a>
@@ -524,7 +524,7 @@ The value you specify depends on your Python version.
 
 
 <pre>
-https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.8.0rc1-py2-none-any.whl
+https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.8.0-py2-none-any.whl
 </pre>
 
 
@@ -532,5 +532,5 @@ https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.8.0rc1-py2-none-a
 
 
 <pre>
-https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.8.0rc1-py3-none-any.whl
+https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.8.0-py3-none-any.whl
 </pre>
diff --git a/install/install_sources.md b/install/install_sources.md
index d48a6ee..3d93736 100644
--- a/install/install_sources.md
+++ b/install/install_sources.md
@@ -350,10 +350,10 @@ Invoke `pip install` to install that pip package.
 The filename of the `.whl` file depends on your platform.
 For example, the following command will install the pip package
 
-for TensorFlow 1.8.0rc1 on Linux:
+for TensorFlow 1.8.0 on Linux:
 
 <pre>
-$ <b>sudo pip install /tmp/tensorflow_pkg/tensorflow-1.8.0rc1-py2-none-any.whl</b>
+$ <b>sudo pip install /tmp/tensorflow_pkg/tensorflow-1.8.0-py2-none-any.whl</b>
 </pre>
 
 ## Validate your installation