Update README.md

README.md

@@ -2,7 +2,7 @@
 
 Custom builds for TensorFlow with platform optimizations, including SSE, AVX and FMA.
 
-These wheels are built for use on [TinyMind](http://www.tinymind.com), the cloud machine learning platform. If you want to install them on your own Linux box (Ubuntu 16.04 LTS), you can do so with:
+These wheels are built for use on [TinyMind](https://www.tinymind.com), the cloud machine learning platform. If you want to install them on your own Linux box (Ubuntu 16.04 LTS), you can do so with:
 
 ```sh
 # RELEASE is the git tag like tf1.1-cpu. WHEEL is the full wheel name.
@@ -19,9 +19,11 @@ The list of all wheels can be found in the [releases page](https://github.com/mi
 
 ## Versions
 
-The table below lists versions you will most likely use. However, be sure to check out the [releases page](https://github.com/mind/wheels/releases) as we are adding other builds (debug, XLA, etc) to the collection. Need something or a wheel doesn't work for you? File an issue.
+The table below lists versions you will most likely use. However, be sure to check out the [releases page](https://github.com/mind/wheels/releases) as we are adding other builds (debug, XLA, etc) to the collection. Need something or a wheel doesn't work for you? File an issue. 
 
-Please note that your machine needs to have a relatively new Intel CPU (and nvidia GPU if you use the GPU version) to be compatible with the wheels below. TensorFlow versions of 1.2.1 and above use CuDNN 6, whereas 1.1 and 1.2 use CuDNN 5.1.
+Please note that your machine needs to have a relatively new Intel CPU (and nvidia GPU if you use the GPU version) to be compatible with the wheels below. If the hardware is not up-to-date, the wheels will not work.
+
+TensorFlow versions of 1.2.1 and above use CuDNN 6, whereas 1.1 and 1.2 use CuDNN 5.1. Additionally, GPU builds for version 1.3 and above use MPICH (for MPI support). See the section below for more information.
 
 Version | Python | Arch | Link
 --------|--------|------|-----
@@ -49,4 +51,23 @@ Version | Python | Arch | Link
 1.3 | 3.6 | GPU | https://github.com/mind/wheels/releases/download/tf1.3-gpu/tensorflow-1.3.0-cp36-cp36m-linux_x86_64.whl
 1.3.1 | 2.7 | CPU | https://github.com/mind/wheels/releases/download/tf1.3.1-cpu/tensorflow-1.3.1-cp27-cp27mu-linux_x86_64.whl
 1.3.1 | 3.5 | CPU | https://github.com/mind/wheels/releases/download/tf1.3.1-cpu/tensorflow-1.3.1-cp35-cp35m-linux_x86_64.whl
-1.3.1 | 3.6 | CPU | https://github.com/mind/wheels/releases/download/tf1.3.1-cpu/tensorflow-1.3.1-cp36-cp36m-linux_x86_64.whl
+1.3.1 | 3.6 | CPU | https://github.com/mind/wheels/releases/download/tf1.3.1-cpu/tensorflow-1.3.1-cp36-cp36m-linux_x86_64.whl
+
+## Help!
+
+This section contains tips for debugging your setup. Seriously though, try [TinyMind](https://www.tinymind.com) out and you will never need to waste time debugging again. We also have [Docker images](https://hub.docker.com/r/tinymind/tensorflow/) that you can use on your own machines.
+
+### CUDA
+
+Make sure you have CUDA 8 installed. TensorFlow < 1.4 doesn't work with CUDA 9, the current version. Instead of `sudo apt-get install cuda`, do `sudo apt-get install cuda-8-0`.
+
+Missing `libcupti` library? Install it and add it to your `PATH`.
+
+```sh
+sudo apt-get install libcupti-dev
+echo 'export LD_LIBRARY_PATH=/usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH' >> ~/.bashrc
+```
+
+### MPI
+
+Using TensorFlow 1.3+ with GPU and it complains about MPI? Run `sudo apt-get install mpich`.