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9228f9718c
We already know where the CUDA SDK is, so there is no point in letting Clang search for it again and possibly finding no or a different installation. --cuda-path is supported since the beginning of CUDA support in Clang, so making this required doesn't impose additional restrictions. Differential Revision: https://reviews.llvm.org/D46930 llvm-svn: 332495 |
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| CMakeLists.txt | ||
| README.txt | ||
README for the LLVM* OpenMP* Offloading Runtime Library (libomptarget)
======================================================================
How to Build the LLVM* OpenMP* Offloading Runtime Library (libomptarget)
========================================================================
In-tree build:
$ cd where-you-want-to-live
Check out openmp (libomptarget lives under ./libomptarget) into llvm/projects
$ cd where-you-want-to-build
$ mkdir build && cd build
$ cmake path/to/llvm -DCMAKE_C_COMPILER=<C compiler> -DCMAKE_CXX_COMPILER=<C++ compiler>
$ make omptarget
Out-of-tree build:
$ cd where-you-want-to-live
Check out openmp (libomptarget lives under ./libomptarget)
$ cd where-you-want-to-live/openmp/libomptarget
$ mkdir build && cd build
$ cmake path/to/openmp -DCMAKE_C_COMPILER=<C compiler> -DCMAKE_CXX_COMPILER=<C++ compiler>
$ make
For details about building, please look at README.rst in the parent directory.
Architectures Supported
=======================
The current library has been only tested in Linux operating system and the
following host architectures:
* Intel(R) 64 architecture
* IBM(R) Power architecture (big endian)
* IBM(R) Power architecture (little endian)
* ARM(R) AArch64 architecture (little endian)
The currently supported offloading device architectures are:
* Intel(R) 64 architecture (generic 64-bit plugin - mostly for testing purposes)
* IBM(R) Power architecture (big endian) (generic 64-bit plugin - mostly for testing purposes)
* IBM(R) Power architecture (little endian) (generic 64-bit plugin - mostly for testing purposes)
* ARM(R) AArch64 architecture (little endian) (generic 64-bit plugin - mostly for testing purposes)
* CUDA(R) enabled 64-bit NVIDIA(R) GPU architectures
Supported RTL Build Configurations
==================================
Supported Architectures: Intel(R) 64, IBM(R) Power 7 and Power 8
---------------------------
| gcc | clang |
--------------|------------|------------|
| Linux* OS | Yes(1) | Yes(2) |
-----------------------------------------
(1) gcc version 4.8.2 or later is supported.
(2) clang version 3.7 or later is supported.
Front-end Compilers that work with this RTL
===========================================
The following compilers are known to do compatible code generation for
this RTL:
- clang (from https://github.com/clang-ykt )
- clang (development branch at http://clang.llvm.org - several features still
under development)
-----------------------------------------------------------------------
Notices
=======
This library and related compiler support is still under development, so the
employed interface is likely to change in the future.
*Other names and brands may be claimed as the property of others.