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int64 versions were switched to volatile pointers in cl1.1 cl1.1 also renamed atom_ functions to atomic_ that use volatile pointers. CTS and applications use volatile pointers. Passes CTS on carrizo no return piglit tests still pass on turks. Reviewed-By: Aaron Watry <awatry@gmail.com> Tested-By: Aaron Watry <awatry@gmail.com> Signed-off-by: Jan Vesely <jan.vesely@rutgers.edu> llvm-svn: 335280 |
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| amdgcn/lib | ||
| amdgcn-amdhsa/lib | ||
| amdgpu/lib | ||
| build | ||
| generic | ||
| ptx/lib | ||
| ptx-nvidiacl/lib | ||
| r600/lib | ||
| test | ||
| utils | ||
| www | ||
| .gitignore | ||
| .travis.yml | ||
| check_external_calls.sh | ||
| compile-test.sh | ||
| configure.py | ||
| CREDITS.TXT | ||
| LICENSE.TXT | ||
| README.TXT | ||
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/