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ReStructuredText
175 lines
6.9 KiB
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=============================
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Advanced Build Configurations
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=============================
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.. contents::
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:local:
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Introduction
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============
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`CMake <http://www.cmake.org/>`_ is a cross-platform build-generator tool. CMake
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does not build the project, it generates the files needed by your build tool
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(GNU make, Visual Studio, etc.) for building LLVM.
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If **you are a new contributor**, please start with the :doc:`GettingStarted` or
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:doc:`CMake` pages. This page is intended for users doing more complex builds.
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Many of the examples below are written assuming specific CMake Generators.
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Unless otherwise explicitly called out these commands should work with any CMake
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generator.
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Bootstrap Builds
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================
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The Clang CMake build system supports bootstrap (aka multi-stage) builds. At a
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high level a multi-stage build is a chain of builds that pass data from one
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stage into the next. The most common and simple version of this is a traditional
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bootstrap build.
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In a simple two-stage bootstrap build, we build clang using the system compiler,
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then use that just-built clang to build clang again. In CMake this simplest form
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of a bootstrap build can be configured with a single option,
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CLANG_ENABLE_BOOTSTRAP.
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.. code-block:: console
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$ cmake -G Ninja -DCLANG_ENABLE_BOOTSTRAP=On <path to source>
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$ ninja stage2
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This command itself isn't terribly useful because it assumes default
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configurations for each stage. The next series of examples utilize CMake cache
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scripts to provide more complex options.
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The clang build system refers to builds as stages. A stage1 build is a standard
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build using the compiler installed on the host, and a stage2 build is built
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using the stage1 compiler. This nomenclature holds up to more stages too. In
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general a stage*n* build is built using the output from stage*n-1*.
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Apple Clang Builds (A More Complex Bootstrap)
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=============================================
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Apple's Clang builds are a slightly more complicated example of the simple
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bootstrapping scenario. Apple Clang is built using a 2-stage build.
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The stage1 compiler is a host-only compiler with some options set. The stage1
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compiler is a balance of optimization vs build time because it is a throwaway.
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The stage2 compiler is the fully optimized compiler intended to ship to users.
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Setting up these compilers requires a lot of options. To simplify the
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configuration the Apple Clang build settings are contained in CMake Cache files.
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You can build an Apple Clang compiler using the following commands:
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.. code-block:: console
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$ cmake -G Ninja -C <path to clang>/cmake/caches/Apple-stage1.cmake <path to source>
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$ ninja stage2-distribution
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This CMake invocation configures the stage1 host compiler, and sets
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CLANG_BOOTSTRAP_CMAKE_ARGS to pass the Apple-stage2.cmake cache script to the
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stage2 configuration step.
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When you build the stage2-distribution target it builds the minimal stage1
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compiler and required tools, then configures and builds the stage2 compiler
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based on the settings in Apple-stage2.cmake.
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This pattern of using cache scripts to set complex settings, and specifically to
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make later stage builds include cache scripts is common in our more advanced
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build configurations.
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Multi-stage PGO
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===============
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Profile-Guided Optimizations (PGO) is a really great way to optimize the code
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clang generates. Our multi-stage PGO builds are a workflow for generating PGO
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profiles that can be used to optimize clang.
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At a high level, the way PGO works is that you build an instrumented compiler,
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then you run the instrumented compiler against sample source files. While the
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instrumented compiler runs it will output a bunch of files containing
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performance counters (.profraw files). After generating all the profraw files
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you use llvm-profdata to merge the files into a single profdata file that you
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can feed into the LLVM_PROFDATA_FILE option.
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Our PGO.cmake cache script automates that whole process. You can use it by
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running:
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.. code-block:: console
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$ cmake -G Ninja -C <path_to_clang>/cmake/caches/PGO.cmake <source dir>
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$ ninja stage2-instrumented-generate-profdata
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If you let that run for a few hours or so, it will place a profdata file in your
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build directory. This takes a really long time because it builds clang twice,
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and you *must* have compiler-rt in your build tree.
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This process uses any source files under the perf-training directory as training
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data as long as the source files are marked up with LIT-style RUN lines.
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After it finishes you can use “find . -name clang.profdata” to find it, but it
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should be at a path something like:
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.. code-block:: console
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<build dir>/tools/clang/stage2-instrumented-bins/utils/perf-training/clang.profdata
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You can feed that file into the LLVM_PROFDATA_FILE option when you build your
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optimized compiler.
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The PGO came cache has a slightly different stage naming scheme than other
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multi-stage builds. It generates three stages; stage1, stage2-instrumented, and
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stage2. Both of the stage2 builds are built using the stage1 compiler.
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The PGO came cache generates the following additional targets:
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**stage2-instrumented**
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Builds a stage1 x86 compiler, runtime, and required tools (llvm-config,
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llvm-profdata) then uses that compiler to build an instrumented stage2 compiler.
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**stage2-instrumented-generate-profdata**
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Depends on "stage2-instrumented" and will use the instrumented compiler to
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generate profdata based on the training files in <clang>/utils/perf-training
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**stage2**
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Depends of "stage2-instrumented-generate-profdata" and will use the stage1
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compiler with the stage2 profdata to build a PGO-optimized compiler.
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**stage2-check-llvm**
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Depends on stage2 and runs check-llvm using the stage2 compiler.
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**stage2-check-clang**
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Depends on stage2 and runs check-clang using the stage2 compiler.
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**stage2-check-all**
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Depends on stage2 and runs check-all using the stage2 compiler.
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**stage2-test-suite**
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Depends on stage2 and runs the test-suite using the stage3 compiler (requires
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in-tree test-suite).
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3-Stage Non-Determinism
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=======================
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In the ancient lore of compilers non-determinism is like the multi-headed hydra.
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Whenever its head pops up, terror and chaos ensue.
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Historically one of the tests to verify that a compiler was deterministic would
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be a three stage build. The idea of a three stage build is you take your sources
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and build a compiler (stage1), then use that compiler to rebuild the sources
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(stage2), then you use that compiler to rebuild the sources a third time
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(stage3) with an identical configuration to the stage2 build. At the end of
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this, you have a stage2 and stage3 compiler that should be bit-for-bit
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identical.
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You can perform one of these 3-stage builds with LLVM & clang using the
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following commands:
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.. code-block:: console
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$ cmake -G Ninja -C <path_to_clang>/cmake/caches/3-stage.cmake <source dir>
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$ ninja stage3
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After the build you can compare the stage2 & stage3 compilers. We have a bot
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setup `here <http://lab.llvm.org:8011/builders/clang-3stage-ubuntu>`_ that runs
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this build and compare configuration.
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