badcd58589
We have a large compile showing occasional non-deterministic behavior that is due to DIArgList not being properly uniqued in some cases. I tracked this down to handleChangedOperands, for which there is a custom implementation for DIArgList, that does not take care of re-uniquing after updating the DIArgList Args, unlike the default version of handleChangedOperands for MDNode. Since the Args in the DIArgList form the key for the store, this seems to be occasionally breaking the lookup in that DenseSet. Specifically, when invoking DIArgList::get() from replaceVariableLocationOp, very occasionally it returns a new DIArgList object, when one already exists having the same exact Args pointers. This in turn causes a subsequent call to Instruction::isIdenticalToWhenDefined on those two otherwise identical DIArgList objects during a later pass to return false, leading to different IR in those rare cases. I modified DIArgList::handleChangedOperands to perform similar re-uniquing as the MDNode version used by other metadata node types. This also necessitated a change to the context destructor, since in some cases we end up with DIArgList as distinct nodes: DIArgList is the only metadata node type to have a custom dropAllReferences, so we need to invoke that version on DIArgList in the DistinctMDNodes store to clean it up properly. Differential Revision: https://reviews.llvm.org/D108968 |
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.github | ||
clang | ||
clang-tools-extra | ||
compiler-rt | ||
cross-project-tests | ||
flang | ||
libc | ||
libclc | ||
libcxx | ||
libcxxabi | ||
libunwind | ||
lld | ||
lldb | ||
llvm | ||
mlir | ||
openmp | ||
parallel-libs | ||
polly | ||
pstl | ||
runtimes | ||
utils | ||
.arcconfig | ||
.arclint | ||
.clang-format | ||
.clang-tidy | ||
.git-blame-ignore-revs | ||
.gitignore | ||
.mailmap | ||
CONTRIBUTING.md | ||
README.md | ||
SECURITY.md |
The LLVM Compiler Infrastructure
This directory and its sub-directories contain source code for LLVM, a toolkit for the construction of highly optimized compilers, optimizers, and run-time environments.
The README briefly describes how to get started with building LLVM. For more information on how to contribute to the LLVM project, please take a look at the Contributing to LLVM guide.
Getting Started with the LLVM System
Taken from https://llvm.org/docs/GettingStarted.html.
Overview
Welcome to the LLVM project!
The LLVM project has multiple components. The core of the project is itself called "LLVM". This contains all of the tools, libraries, and header files needed to process intermediate representations and convert them into object files. Tools include an assembler, disassembler, bitcode analyzer, and bitcode optimizer. It also contains basic regression tests.
C-like languages use the Clang front end. This component compiles C, C++, Objective-C, and Objective-C++ code into LLVM bitcode -- and from there into object files, using LLVM.
Other components include: the libc++ C++ standard library, the LLD linker, and more.
Getting the Source Code and Building LLVM
The LLVM Getting Started documentation may be out of date. The Clang Getting Started page might have more accurate information.
This is an example work-flow and configuration to get and build the LLVM source:
-
Checkout LLVM (including related sub-projects like Clang):
-
git clone https://github.com/llvm/llvm-project.git
-
Or, on windows,
git clone --config core.autocrlf=false https://github.com/llvm/llvm-project.git
-
-
Configure and build LLVM and Clang:
-
cd llvm-project
-
cmake -S llvm -B build -G <generator> [options]
Some common build system generators are:
Ninja
--- for generating Ninja build files. Most llvm developers use Ninja.Unix Makefiles
--- for generating make-compatible parallel makefiles.Visual Studio
--- for generating Visual Studio projects and solutions.Xcode
--- for generating Xcode projects.
Some Common options:
-
-DLLVM_ENABLE_PROJECTS='...'
--- semicolon-separated list of the LLVM sub-projects you'd like to additionally build. Can include any of: clang, clang-tools-extra, libcxx, libcxxabi, libunwind, lldb, compiler-rt, lld, polly, or cross-project-tests.For example, to build LLVM, Clang, libcxx, and libcxxabi, use
-DLLVM_ENABLE_PROJECTS="clang;libcxx;libcxxabi"
. -
-DCMAKE_INSTALL_PREFIX=directory
--- Specify for directory the full path name of where you want the LLVM tools and libraries to be installed (default/usr/local
). -
-DCMAKE_BUILD_TYPE=type
--- Valid options for type are Debug, Release, RelWithDebInfo, and MinSizeRel. Default is Debug. -
-DLLVM_ENABLE_ASSERTIONS=On
--- Compile with assertion checks enabled (default is Yes for Debug builds, No for all other build types).
-
cmake --build build [-- [options] <target>]
or your build system specified above directly.-
The default target (i.e.
ninja
ormake
) will build all of LLVM. -
The
check-all
target (i.e.ninja check-all
) will run the regression tests to ensure everything is in working order. -
CMake will generate targets for each tool and library, and most LLVM sub-projects generate their own
check-<project>
target. -
Running a serial build will be slow. To improve speed, try running a parallel build. That's done by default in Ninja; for
make
, use the option-j NNN
, whereNNN
is the number of parallel jobs, e.g. the number of CPUs you have.
-
-
For more information see CMake
-
Consult the Getting Started with LLVM page for detailed information on configuring and compiling LLVM. You can visit Directory Layout to learn about the layout of the source code tree.