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Update references to minimum CUDA and cuDNN version (#20718)

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Summary:
I didn't update the Windows references because I wasn't sure if they apply to CUDA 9. peterjc123 what should the Windows section say?
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20718

Differential Revision: D15459276

Pulled By: colesbury

fbshipit-source-id: 917e22f8ac75378d88c962c226b5a42b6799c79a
This commit is contained in:
Sam Gross
2019-05-22 14:51:31 -07:00
committed by Facebook Github Bot
parent 05543153dd
commit 6ec3c12255
1 changed files with 3 additions and 9 deletions
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12
README.md
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@ -156,8 +156,8 @@ You will get a high-quality BLAS library (MKL) and you get controlled dependency
Once you have [Anaconda](https://www.anaconda.com/distribution/#download-section) installed, here are the instructions.
If you want to compile with CUDA support, install
- [NVIDIA CUDA](https://developer.nvidia.com/cuda-downloads) 7.5 or above
- [NVIDIA cuDNN](https://developer.nvidia.com/cudnn) v6.x or above
- [NVIDIA CUDA](https://developer.nvidia.com/cuda-downloads) 9 or above
- [NVIDIA cuDNN](https://developer.nvidia.com/cudnn) v7 or above
If you want to disable CUDA support, export environment variable `NO_CUDA=1`.
Other potentially useful environment variables may be found in `setup.py`.
@ -175,7 +175,7 @@ conda install numpy ninja pyyaml mkl mkl-include setuptools cmake cffi typing
On Linux
```bash
# Add LAPACK support for the GPU if needed
conda install -c pytorch magma-cuda90 # or [magma-cuda80 | magma-cuda92 | magma-cuda100 ] depending on your cuda version
conda install -c pytorch magma-cuda90 # or [magma-cuda92 | magma-cuda100 ] depending on your cuda version
```
#### Get the PyTorch Source
@ -209,9 +209,6 @@ If the version of Visual Studio 2017 is higher than 15.4.5, installing of "VC++
<br/> There is no guarantee of the correct building with VC++ 2017 toolsets, others than version 15.4 v14.11.
<br/> "VC++ 2017 version 15.4 v14.11 toolset" might be installed onto already installed Visual Studio 2017 by running its installation once again and checking the corresponding checkbox under "Individual components"/"Compilers, build tools, and runtimes".
For building against CUDA 8.0 Visual Studio 2015 Update 3 (version 14.0), and the [patch](https://download.microsoft.com/download/8/1/d/81dbe6bb-ed92-411a-bef5-3a75ff972c6a/vc14-kb4020481.exe) are needed to be installed too.
The details of the patch can be found [here](https://support.microsoft.com/en-gb/help/4020481/fix-link-exe-crashes-with-a-fatal-lnk1000-error-when-you-use-wholearch).
NVTX is a part of CUDA distributive, where it is called "Nsight Compute". For installing it onto already installed CUDA run CUDA installation once again and check the corresponding checkbox.
Be sure that CUDA with Nsight Compute is installed after Visual Studio 2017.
@ -221,9 +218,6 @@ REM [Optional] The following two lines are needed for Python 2.7, but the suppor
set MSSdk=1
set FORCE_PY27_BUILD=1
REM [Optional] As for CUDA 8, VS2015 Update 3 is required; use the following line.
set "CUDAHOSTCXX=%VS140COMNTOOLS%..\..\VC\bin\amd64\cl.exe"
set CMAKE_GENERATOR=Visual Studio 15 2017 Win64
set DISTUTILS_USE_SDK=1