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Updating the cuda compute info and avx info for Windows. #17450

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Mar 6, 2018
Merged

Updating the cuda compute info and avx info for Windows. #17450

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3 changes: 2 additions & 1 deletion tensorflow/docs_src/install/install_linux.md
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Expand Up @@ -41,7 +41,8 @@ must be installed on your system:
[NVIDIA's documentation](https://developer.nvidia.com/cudnn).
Ensure that you create the `CUDA_HOME` environment variable as
described in the NVIDIA documentation.
* GPU card with CUDA Compute Capability 3.0 or higher. See
* GPU card with CUDA Compute Capability 3.0 or higher for building
from source and 3.5 or higher for our binaries. See
[NVIDIA documentation](https://developer.nvidia.com/cuda-gpus) for
a list of supported GPU cards.
* The libcupti-dev library, which is the NVIDIA CUDA Profile Tools Interface.
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5 changes: 3 additions & 2 deletions tensorflow/docs_src/install/install_windows.md
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Expand Up @@ -17,7 +17,7 @@ You must choose one of the following types of TensorFlow to install:
NVIDIA® GPU, you must install this version. Note that this version of
TensorFlow is typically much easier to install (typically,
in 5 or 10 minutes), so even if you have an NVIDIA GPU, we recommend
installing this version first.
installing this version first. Prebuilt binaries will use AVX instructions.
* **TensorFlow with GPU support**. TensorFlow programs typically run
significantly faster on a GPU than on a CPU. Therefore, if your
system has a NVIDIA® GPU meeting the prerequisites shown below
Expand All @@ -41,7 +41,8 @@ installed on your system:
Note that cuDNN is typically installed in a different location from the
other CUDA DLLs. Ensure that you add the directory where you installed
the cuDNN DLL to your `%PATH%` environment variable.
* GPU card with CUDA Compute Capability 3.0 or higher. See
* GPU card with CUDA Compute Capability 3.0 or higher for building
from source and 3.5 or higher for our binaries. See
[NVIDIA documentation](https://developer.nvidia.com/cuda-gpus) for a
list of supported GPU cards.

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