06789ccb16
These functions all map to the corresponding LLVM intrinsics, but the vector intrinsics weren't being generated. The intrinsic mapping from CLC vector function to vector intrinsic was working correctly, but the mapping from OpenCL builtin to CLC function was suboptimally recursively splitting vectors in halves. For example, with this change, `ceil(float16)` calls `llvm.ceil.v16f32` directly once optimizations are applied. Now also, instead of generating LLVM intrinsics through `__asm` we now call clang elementwise builtins for each CLC builtin. This should be a more standard way of achieving the same result The CLC versions of each of these builtins are also now built and enabled for SPIR-V targets. The LLVM -> SPIR-V translator maps the intrinsics to the appropriate OpExtInst, so there should be no difference in semantics, despite the newly introduced indirection from OpenCL builtin through the CLC builtin to the intrinsic. The AMDGPU targets make use of the same `_CLC_DEFINE_UNARY_BUILTIN` macro to override `sqrt`, so those functions also appear more optimal with this change, calling the vector `llvm.sqrt.vXf32` intrinsics directly.
libclc
libclc is an open source 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 supports PTX, AMDGPU, SPIRV and CLSPV targets, but support for more targets is welcome.
Compiling and installing
(in the following instructions you can use make or ninja)
For an in-tree build, Clang must also be built at the same time:
$ cmake <path-to>/llvm-project/llvm/CMakeLists.txt -DLLVM_ENABLE_PROJECTS="libclc;clang" \
-DCMAKE_BUILD_TYPE=Release -G Ninja
$ ninja
Then install:
$ ninja install
Note you can use the DESTDIR Makefile variable to do staged installs.
$ DESTDIR=/path/for/staged/install ninja install
To build out of tree, or in other words, against an existing LLVM build or install:
$ cmake <path-to>/llvm-project/libclc/CMakeLists.txt -DCMAKE_BUILD_TYPE=Release \
-G Ninja -DLLVM_DIR=$(<path-to>/llvm-config --cmakedir)
$ ninja
Then install as before.
In both cases this will include all supported targets. You can choose which
targets are enabled by passing -DLIBCLC_TARGETS_TO_BUILD to CMake. The default
is all.
In both cases, the LLVM used must include the targets you want libclc support for
(AMDGPU and NVPTX are enabled in LLVM by default). Apart from SPIRV where you do
not need an LLVM target but you do need the
llvm-spirv tool available.
Either build this in-tree, or place it in the directory pointed to by
LLVM_TOOLS_BINARY_DIR.