476 lines
14 KiB
Markdown
476 lines
14 KiB
Markdown
<!--===- docs/GettingStarted.md
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Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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See https://llvm.org/LICENSE.txt for license information.
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SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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-->
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# Getting Started
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```{contents}
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---
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local:
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---
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```
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## Building flang
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There are two ways to build flang. The first method is to build it at the same
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time that you build all of the projects on which it depends. This is called
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building in tree. The second method is to first do an in tree build to create
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all of the projects on which flang depends. Then, after creating this base
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build, only build the flang code itself. This is called building standalone.
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Building standalone has the advantage of being smaller and faster. Once you
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create the base build and base install areas, you can create multiple
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standalone builds using them.
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Note that instructions for building LLVM can be found at
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https://llvm.org/docs/GettingStarted.html.
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All of the examples below use GCC as the C/C++ compilers and ninja as the build
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tool.
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### Building flang in tree
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Building flang in tree means building flang along with all of the projects on
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which it depends. These projects include mlir, clang, flang, openmp, and
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compiler-rt. Note that compiler-rt is only needed to access libraries that
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support 16 bit floating point numbers. It's not needed to run the automated
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tests. You can use several different C++ compilers for most of the build,
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includig GNU and clang. But building compiler-rt requres using the clang
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compiler built in the initial part of the build.
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Here's a directory structure that works. Create a root directory for the
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cloned and built files. Under that root directory, clone the source code
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into a directory called llvm-project. The build will also
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create subdirectories under the root directory called build (holds most of
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the built files), install (holds the installed files, and compiler-rt (holds
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the result of building compiler-rt).
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Here's a complete set of commands to clone all of the necessary source and do
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the build.
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First, create the root directory and `cd` into it.
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```bash
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mkdir root
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cd root
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```
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Now clone the source:
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```bash
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git clone https://github.com/llvm/llvm-project.git
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```
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Once the clone is complete, execute the following commands:
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```bash
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rm -rf build
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mkdir build
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rm -rf install
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mkdir install
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ROOTDIR=`pwd`
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INSTALLDIR=$ROOTDIR/install
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cd build
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cmake \
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-G Ninja \
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-DCMAKE_BUILD_TYPE=Release \
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-DCMAKE_INSTALL_PREFIX=$INSTALLDIR \
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-DCMAKE_CXX_STANDARD=17 \
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-DCMAKE_EXPORT_COMPILE_COMMANDS=ON \
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-DCMAKE_CXX_LINK_FLAGS="-Wl,-rpath,$LD_LIBRARY_PATH" \
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-DFLANG_ENABLE_WERROR=ON \
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-DLLVM_ENABLE_ASSERTIONS=ON \
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-DLLVM_TARGETS_TO_BUILD=host \
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-DLLVM_LIT_ARGS=-v \
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-DLLVM_ENABLE_PROJECTS="clang;mlir;flang;openmp" \
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-DLLVM_ENABLE_RUNTIMES="compiler-rt" \
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../llvm-project/llvm
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ninja
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```
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On Darwin, to make flang able to link binaries with the default sysroot without
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having to specify additional flags, use the `DEFAULT_SYSROOT` CMake flag, e.g.
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`-DDEFAULT_SYSROOT="$(xcrun --show-sdk-path)"`.
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By default flang tests that do not specify an explicit `--target` flag use
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LLVM's default target triple. For these tests, if there is a need to test on a
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different triple by overriding the default, the following needs to be added to
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the cmake command above:
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`-DLLVM_TARGET_TRIPLE_ENV="<some string>" -DFLANG_TEST_TARGET_TRIPLE="<your triple>"`.
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To run the flang tests on this build, execute the command in the "build"
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directory:
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```bash
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ninja check-flang
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```
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To create the installed files:
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```bash
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ninja install
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echo "latest" > $INSTALLDIR/bin/versionrc
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```
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To build compiler-rt:
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```bash
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cd $ROOTDIR
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rm -rf compiler-rt
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mkdir compiler-rt
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cd compiler-rt
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CC=$INSTALLDIR/bin/clang \
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CXX=$INSTALLDIR/bin/clang++ \
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cmake \
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-G Ninja \
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../llvm-project/compiler-rt \
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-DCMAKE_BUILD_TYPE=Release \
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-DCMAKE_INSTALL_PREFIX=$INSTALLDIR \
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-DCMAKE_CXX_STANDARD=11 \
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-DCMAKE_C_CFLAGS=-mlong-double-128 \
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-DCMAKE_CXX_CFLAGS=-mlong-double-128 \
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-DCMAKE_EXPORT_COMPILE_COMMANDS=ON \
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-DCOMPILER_RT_BUILD_ORC=OFF \
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-DCOMPILER_RT_BUILD_XRAY=OFF \
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-DCOMPILER_RT_BUILD_MEMPROF=OFF \
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-DCOMPILER_RT_BUILD_LIBFUZZER=OFF \
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-DCOMPILER_RT_BUILD_SANITIZERS=OFF \
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-DLLVM_CONFIG_PATH=$INSTALLDIR/bin/llvm-config
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ninja
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ninja install
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```
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Note that these instructions specify flang as one of the projects to build in
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the in tree build. This is not strictly necessary for subsequent standalone
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builds, but doing so lets you run the flang tests to verify that the source
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code is in good shape.
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### Building flang standalone
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To do the standalone build, start by building flang in tree as described above.
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This build can be used as the base build for several subsequent standalone
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builds. Set the environment variable **ROOT_DIR** to the directory that
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contains the subdirectory `build` that was created previously, for example:
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```bash
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export ROOTDIR=/home/user/root
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```
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Start each standalone build the same way by cloning the source for
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llvm-project:
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```bash
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mkdir standalone
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cd standalone
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git clone https://github.com/llvm/llvm-project.git
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```
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Once the clone is complete, execute the following commands:
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```bash
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cd llvm-project/flang
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rm -rf build
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mkdir build
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cd build
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cmake \
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-G Ninja \
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-DCMAKE_BUILD_TYPE=Release \
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-DCMAKE_CXX_STANDARD=17 \
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-DCMAKE_CXX_LINK_FLAGS="-Wl,-rpath,$LD_LIBRARY_PATH" \
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-DCMAKE_EXPORT_COMPILE_COMMANDS=ON \
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-DFLANG_ENABLE_WERROR=ON \
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-DLLVM_TARGETS_TO_BUILD=host \
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-DLLVM_ENABLE_ASSERTIONS=ON \
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-DLLVM_BUILD_MAIN_SRC_DIR=$ROOTDIR/build/lib/cmake/llvm \
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-DLLVM_EXTERNAL_LIT=$ROOTDIR/build/bin/llvm-lit \
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-DLLVM_LIT_ARGS=-v \
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-DLLVM_DIR=$ROOTDIR/build/lib/cmake/llvm \
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-DCLANG_DIR=$ROOTDIR/build/lib/cmake/clang \
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-DMLIR_DIR=$ROOTDIR/build/lib/cmake/mlir \
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..
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ninja
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```
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To run the flang tests on this build, execute the command in the `flang/build`
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directory:
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```bash
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ninja check-flang
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```
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### Building flang runtime for accelerators
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Flang runtime can be built for accelerators in experimental mode, i.e.
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complete enabling is WIP. CUDA and OpenMP target offload builds
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are currently supported.
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#### Building out-of-tree
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##### CUDA build
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Clang with NVPTX backend and NVCC compilers are supported.
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```bash
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cd llvm-project/flang
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rm -rf build_flang_runtime
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mkdir build_flang_runtime
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cd build_flang_runtime
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cmake \
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-DFLANG_EXPERIMENTAL_CUDA_RUNTIME=ON \
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-DCMAKE_CUDA_ARCHITECTURES=80 \
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-DCMAKE_C_COMPILER=clang \
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-DCMAKE_CXX_COMPILER=clang++ \
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-DCMAKE_CUDA_COMPILER=clang \
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-DCMAKE_CUDA_HOST_COMPILER=clang++ \
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../runtime/
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make -j FortranRuntime
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```
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Note that the used version of `clang` must [support](https://releases.llvm.org/16.0.0/tools/clang/docs/ReleaseNotes.html#cuda-support)
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CUDA toolkit version installed on the build machine. If there are multiple
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CUDA toolkit installations, please use `-DCUDAToolkit_ROOT=/some/path`
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to specify the compatible version.
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```bash
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cd llvm-project/flang
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rm -rf build_flang_runtime
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mkdir build_flang_runtime
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cd build_flang_runtime
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cmake \
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-DFLANG_EXPERIMENTAL_CUDA_RUNTIME=ON \
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-DCMAKE_CUDA_ARCHITECTURES=80 \
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-DCMAKE_C_COMPILER=clang \
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-DCMAKE_CXX_COMPILER=clang++ \
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-DCMAKE_CUDA_COMPILER=nvcc \
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-DCMAKE_CUDA_HOST_COMPILER=clang++ \
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../runtime/
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make -j FortranRuntime
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```
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Note that `nvcc` might limit support to certain
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[versions](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#host-compiler-support-policy) of `CMAKE_CUDA_HOST_COMPILER`,
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so please use compatible versions.
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The result of the build is a "fat" library with the host and device
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code. Note that the packaging of the libraries is different
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between [Clang](https://clang.llvm.org/docs/OffloadingDesign.html#linking-target-device-code) and NVCC, so the library must be linked using
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compatible compiler drivers.
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#### Building in-tree
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One may build Flang runtime library along with building Flang itself
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by providing these additional CMake variables on top of the Flang in-tree
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build config:
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For example:
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```bash
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-DFLANG_EXPERIMENTAL_CUDA_RUNTIME=ON \
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-DCMAKE_CUDA_ARCHITECTURES=80 \
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-DCMAKE_C_COMPILER=clang \
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-DCMAKE_CXX_COMPILER=clang++ \
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-DCMAKE_CUDA_COMPILER=clang \
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-DCMAKE_CUDA_HOST_COMPILER=clang++ \
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```
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Or:
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```bash
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-DFLANG_EXPERIMENTAL_CUDA_RUNTIME=ON \
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-DCMAKE_CUDA_ARCHITECTURES=80 \
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-DCMAKE_C_COMPILER=gcc \
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-DCMAKE_CXX_COMPILER=g++ \
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-DCMAKE_CUDA_COMPILER=nvcc \
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-DCMAKE_CUDA_HOST_COMPILER=g++ \
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```
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Normal `make -j check-flang` will work with such CMake configuration.
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##### OpenMP target offload build
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Only Clang compiler is currently supported.
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```bash
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cd llvm-project/flang
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rm -rf build_flang_runtime
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mkdir build_flang_runtime
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cd build_flang_runtime
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cmake \
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-DFLANG_EXPERIMENTAL_OMP_OFFLOAD_BUILD="host_device" \
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-DCMAKE_C_COMPILER=clang \
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-DCMAKE_CXX_COMPILER=clang++ \
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-DFLANG_OMP_DEVICE_ARCHITECTURES="all" \
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../runtime/
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make -j FortranRuntime
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```
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The result of the build is a "device-only" library, i.e. the host
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part of the library is just a container for the device code.
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The resulting library may be linked to user programs using
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Clang-like device linking pipeline.
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The same set of CMake variables works for Flang in-tree build.
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## Supported C++ compilers
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Flang is written in C++17.
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The code has been compiled and tested with GCC versions from 7.2.0 to 9.3.0.
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The code has been compiled and tested with clang version 7.0, 8.0, 9.0 and 10.0
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using either GNU's libstdc++ or LLVM's libc++.
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The code has been compiled on AArch64, x86_64 and ppc64le servers with CentOS7,
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Ubuntu18.04, Rhel, MacOs, Mojave, XCode and Apple Clang version 10.0.1.
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Note that flang is not supported on 32 bit CPUs.
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### Building flang with GCC
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By default,
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cmake will search for g++ on your PATH.
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The g++ version must be one of the supported versions
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in order to build flang.
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Or, cmake will use the variable CXX to find the C++ compiler. CXX should include
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the full path to the compiler or a name that will be found on your PATH, e.g.
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g++-8.3, assuming g++-8.3 is on your PATH.
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```bash
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export CXX=g++-8.3
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```
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or
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```bash
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CXX=/opt/gcc-8.3/bin/g++-8.3 cmake ...
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```
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### Building flang with clang
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To build flang with clang,
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cmake needs to know how to find clang++
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and the GCC library and tools that were used to build clang++.
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CXX should include the full path to clang++
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or clang++ should be found on your PATH.
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```bash
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export CXX=clang++
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```
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### Installation Directory
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To specify a custom install location,
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add
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`-DCMAKE_INSTALL_PREFIX=<INSTALL_PREFIX>`
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to the cmake command
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where `<INSTALL_PREFIX>`
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is the path where flang should be installed.
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### Build Types
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To create a debug build,
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add
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`-DCMAKE_BUILD_TYPE=Debug`
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to the cmake command.
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Debug builds execute slowly.
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To create a release build,
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add
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`-DCMAKE_BUILD_TYPE=Release`
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to the cmake command.
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Release builds execute quickly.
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## How to Run Tests
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Flang supports 2 different categories of tests
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1. Regression tests (https://www.llvm.org/docs/TestingGuide.html#regression-tests)
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2. Unit tests (https://www.llvm.org/docs/TestingGuide.html#unit-tests)
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### For standalone builds
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To run all tests:
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```bash
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cd ~/flang/build
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cmake -DLLVM_DIR=$LLVM -DMLIR_DIR=$MLIR ~/flang/src
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ninja check-all
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```
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To run individual regression tests llvm-lit needs to know the lit
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configuration for flang. The parameters in charge of this are:
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flang_site_config and flang_config. And they can be set as shown below:
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```bash
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<path-to-llvm-lit>/llvm-lit \
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--param flang_site_config=<path-to-flang-build>/test-lit/lit.site.cfg.py \
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--param flang_config=<path-to-flang-build>/test-lit/lit.cfg.py \
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<path-to-fortran-test>
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```
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Unit tests:
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If flang was built with `-DFLANG_INCLUDE_TESTS=ON` (`ON` by default), it is possible to generate unittests.
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Note: Unit-tests will be skipped for LLVM install for an standalone build as it does not include googletest related headers and libraries.
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There are various ways to run unit-tests.
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```
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1. ninja check-flang-unit
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2. ninja check-all or ninja check-flang
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3. <path-to-llvm-lit>/llvm-lit \
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test/Unit
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4. Invoking tests from <standalone flang build>/unittests/<respective unit test folder>
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```
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### For in tree builds
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If flang was built with `-DFLANG_INCLUDE_TESTS=ON` (`ON` by default), it is possible to
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generate unittests.
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To run all of the flang unit tests use the `check-flang-unit` target:
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```bash
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ninja check-flang-unit
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```
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To run all of the flang regression tests use the `check-flang` target:
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```bash
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ninja check-flang
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```
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## How to Generate Documentation
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### Generate FIR Documentation
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If flang was built with `-DLINK_WITH_FIR=ON` (`ON` by default), it is possible to
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generate FIR language documentation by running `ninja flang-doc`. This will
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create `<build-dir>/tools/flang/docs/Dialect/FIRLangRef.md` in flang build directory.
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### Generate Doxygen-based Documentation
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To generate doxygen-style documentation from source code
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- Pass `-DLLVM_ENABLE_DOXYGEN=ON -DFLANG_INCLUDE_DOCS=ON` to the cmake command.
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```bash
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cd ~/llvm-project/build
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cmake -G Ninja -DLLVM_ENABLE_PROJECTS="clang;flang" -DCMAKE_BUILD_TYPE=Release -DLLVM_ENABLE_DOXYGEN=ON -DFLANG_INCLUDE_DOCS=ON ../llvm
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ninja doxygen-flang
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```
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It will generate html in
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```bash
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<build-dir>/tools/flang/docs/doxygen/html # for flang docs
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```
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### Generate Sphinx-based Documentation
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[Flang documentation](https://flang.llvm.org/docs/) should preferably be written in `markdown(.md)` syntax (they can be in `reStructuredText(.rst)` format as well but markdown is recommended in first place), it
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is mostly meant to be processed by the Sphinx documentation generation
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system to create HTML pages which would be hosted on the webpage of flang and
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updated periodically.
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If you would like to generate and view the HTML locally:
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- Install [Sphinx](http://sphinx-doc.org/), and the required extensions
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using `pip install --user -r ~/llvm-projects/docs/requirements.txt`
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- Pass `-DLLVM_ENABLE_SPHINX=ON -DSPHINX_WARNINGS_AS_ERRORS=OFF` to the cmake command.
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```bash
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cd ~/llvm-project/build
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cmake -G Ninja -DLLVM_ENABLE_PROJECTS="clang;flang" -DCMAKE_BUILD_TYPE=Release -DLLVM_ENABLE_SPHINX=ON -DSPHINX_WARNINGS_AS_ERRORS=OFF ../llvm
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ninja docs-flang-html
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```
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It will generate html in
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```bash
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$BROWSER <build-dir>/tools/flang/docs/html/
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```
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