forked from OSchip/llvm-project
24fad7278a
This is required for using the Ninja backend on Windows, as it passes commands directly to CreateProcess, and does not allow the shell to interpret them: https://ninja-build.org/manual.html#ref_rule_command Using the Visual Studio backend is not possible as attempting to create a static library target comprised entirely of novel languages not known to the Visual Studio backend built in to CMake's C++ source will generate nothing at all. reviewer: jvesely Differential Revision: https://reviews.llvm.org/D77165 |
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| .. | ||
| amdgcn/lib | ||
| amdgcn-amdhsa/lib | ||
| amdgpu/lib | ||
| cmake | ||
| generic | ||
| ptx/lib | ||
| ptx-nvidiacl/lib | ||
| r600/lib | ||
| test | ||
| utils | ||
| www | ||
| .gitignore | ||
| CMakeLists.txt | ||
| CREDITS.TXT | ||
| LICENSE.TXT | ||
| README.TXT | ||
| amdgcn-mesa3d | ||
| check_external_calls.sh | ||
| compile-test.sh | ||
| libclc.pc.in | ||
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/