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[CUDA] updated CompileCudaWithLLVM.rst

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Differential Revision: https://reviews.llvm.org/D54608

llvm-svn: 347007
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Artem Belevich 2018-11-16 01:02:43 +00:00
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docs/CompileCudaWithLLVM.rst
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@ -22,21 +22,21 @@ Compiling CUDA Code
Prerequisites
-------------
CUDA is supported in llvm 3.9, but it's still in active development, so we
recommend you `compile clang/LLVM from HEAD
<http://llvm.org/docs/GettingStarted.html>`_.
CUDA is supported since llvm 3.9. Current release of clang (7.0.0) supports CUDA
7.0 through 9.2. If you need support for CUDA 10, you will need to use clang
built from r342924 or newer.
Before you build CUDA code, you'll need to have installed the appropriate
driver for your nvidia GPU and the CUDA SDK. See `NVIDIA's CUDA installation
guide <https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html>`_
for details. Note that clang `does not support
<https://llvm.org/bugs/show_bug.cgi?id=26966>`_ the CUDA toolkit as installed
by many Linux package managers; you probably need to install nvidia's package.
Before you build CUDA code, you'll need to have installed the appropriate driver
for your nvidia GPU and the CUDA SDK. See `NVIDIA's CUDA installation guide
<https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html>`_ for
details. Note that clang `does not support
<https://llvm.org/bugs/show_bug.cgi?id=26966>`_ the CUDA toolkit as installed by
many Linux package managers; you probably need to install CUDA in a single
directory from NVIDIA's package.
You will need CUDA 7.0, 7.5, or 8.0 to compile with clang.
CUDA compilation is supported on Linux, on MacOS as of 2016-11-18, and on
Windows as of 2017-01-05.
CUDA compilation is supported on Linux. Compilation on MacOS and Windows may or
may not work and currently have no maintainers. Compilation with CUDA-9.x is
`currently broken on Windows <https://bugs.llvm.org/show_bug.cgi?id=38811>`_.
Invoking clang
--------------
@ -73,7 +73,9 @@ run your program.
Pass e.g. ``-L/usr/local/cuda/lib64`` if compiling in 64-bit mode; otherwise,
pass e.g. ``-L/usr/local/cuda/lib``. (In CUDA, the device code and host code
always have the same pointer widths, so if you're compiling 64-bit code for
the host, you're also compiling 64-bit code for the device.)
the host, you're also compiling 64-bit code for the device.) Note that as of
v10.0 CUDA SDK `no longer supports compilation of 32-bit
applications<https://docs.nvidia.com/cuda/cuda-toolkit-release-notes/index.html#deprecated-features>`_.
* ``<GPU arch>`` -- the `compute capability
<https://developer.nvidia.com/cuda-gpus>`_ of your GPU. For example, if you
@ -89,8 +91,7 @@ run your program.
The `-L` and `-l` flags only need to be passed when linking. When compiling,
you may also need to pass ``--cuda-path=/path/to/cuda`` if you didn't install
the CUDA SDK into ``/usr/local/cuda``, ``/usr/local/cuda-7.0``, or
``/usr/local/cuda-7.5``.
the CUDA SDK into ``/usr/local/cuda`` or ``/usr/local/cuda-X.Y``.
Flags that control numerical code
---------------------------------
@ -548,9 +549,9 @@ The relevant tools are now just vanilla clang/LLVM.
| Jingyue Wu, Artem Belevich, Eli Bendersky, Mark Heffernan, Chris Leary, Jacques Pienaar, Bjarke Roune, Rob Springer, Xuetian Weng, Robert Hundt
| *Proceedings of the 2016 International Symposium on Code Generation and Optimization (CGO 2016)*
|
| `Slides from the CGO talk <http://wujingyue.com/docs/gpucc-talk.pdf>`_
| `Slides from the CGO talk <http://wujingyue.github.io/docs/gpucc-talk.pdf>`_
|
| `Tutorial given at CGO <http://wujingyue.com/docs/gpucc-tutorial.pdf>`_
| `Tutorial given at CGO <http://wujingyue.github.io/docs/gpucc-tutorial.pdf>`_
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