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llvm-capstone/libclc
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Jan Vesely 1c81f4b0e3 Implement cl_khr_int64_base_atomics builtins 
Signed-off-by: Jan Vesely <jan.vesely@rutgers.edu>
Reviewed-by: Aaron Watry <awatry@gmail.com>
Tested-by: Aaron Watry <awatry@gmail.com>
llvm-svn: 313810
2017-09-20 20:42:14 +00:00
..
amdgcn/lib amdgcn,waitcnt: Add datalayout info 2017-09-04 15:52:07 +00:00
amdgcn-amdhsa/lib amdgcn-amdhsa: Add get_num_groups implementation 2016-09-16 22:43:31 +00:00
amdgpu/lib Implement vload_half{,n} and vload(half) 2017-09-08 23:59:00 +00:00
build configure.py: Make python3 friendly 2017-08-02 15:00:59 +00:00
generic Implement cl_khr_int64_base_atomics builtins 2017-09-20 20:42:14 +00:00
ptx/lib
ptx-nvidiacl/lib AMDGPU: Implement get_global_offset builtin 2016-07-22 17:24:24 +00:00
r600/lib r600: Cleanup barrier implementation. 2017-09-04 15:52:05 +00:00
test
utils Move BufferPtr into the block where it it being used 2017-02-12 21:33:49 +00:00
www Update page to list supported targets 2016-02-13 01:02:06 +00:00
.gitignore .gitignore: Ignore amdgcn-mesa object directory 2017-02-24 20:32:18 +00:00
.travis.yml Add travis CI configuration file 2017-09-20 17:28:58 +00:00
compile-test.sh
configure.py configure.py: Simplify compatibility sources 2017-09-08 23:58:53 +00:00
CREDITS.TXT
LICENSE.TXT Update copyright year to 2016. 2016-03-30 22:39:03 +00:00
README.TXT

README.TXT

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libclc
------

libclc is an open source, BSD licensed implementation of the library
requirements of the OpenCL C programming language, as specified by the
OpenCL 1.1 Specification. The following sections of the specification
impose library requirements:

  * 6.1: Supported Data Types
  * 6.2.3: Explicit Conversions
  * 6.2.4.2: Reinterpreting Types Using as_type() and as_typen()
  * 6.9: Preprocessor Directives and Macros
  * 6.11: Built-in Functions
  * 9.3: Double Precision Floating-Point
  * 9.4: 64-bit Atomics
  * 9.5: Writing to 3D image memory objects
  * 9.6: Half Precision Floating-Point

libclc is intended to be used with the Clang compiler's OpenCL frontend.

libclc is designed to be portable and extensible. To this end, it provides
generic implementations of most library requirements, allowing the target
to override the generic implementation at the granularity of individual
functions.

libclc currently only supports the PTX target, but support for more
targets is welcome.

Compiling and installing with Make
----------------------------------

$ ./configure.py --with-llvm-config=/path/to/llvm-config && make
$ make install

Note you can use the DESTDIR Makefile variable to do staged installs.

$ make install DESTDIR=/path/for/staged/install

Compiling and installing with Ninja
-----------------------------------

$ ./configure.py -g ninja --with-llvm-config=/path/to/llvm-config && ninja
$ ninja install

Note you can use the DESTDIR environment variable to do staged installs.

$ DESTDIR=/path/for/staged/install ninja install

Website
-------

http://www.pcc.me.uk/~peter/libclc/