fe593fe15f
Fixes issue encountered in D56362, where I tried to use a SmallSetVector<Instruction*, 128> with an excessively large number of inline elements. This triggers an "Must allocate more buckets than are inline" assertion inside allocateBuckets() under certain usage patterns. The issue is as follows: The grow() method is used either to grow the map, or to rehash it and remove tombstones. The latter is done if the fraction of empty (non-used, non-tombstone) elements is below 1/8. In this case grow() is invoked with the current number of buckets. This is currently incorrectly handled for dense maps using the small rep. The current implementation will switch them over to the large rep, which violates the invariant that the large rep is only used if there are more than InlineBuckets buckets. This patch fixes the issue by staying in the small rep and only moving the buckets. An alternative, if we do want to switch to the large rep in this case, would be to relax the assertion in allocateBuckets(). Differential Revision: https://reviews.llvm.org/D56455
The LLVM Compiler Infrastructure
This directory and its subdirectories contain source code for LLVM, a toolkit for the construction of highly optimized compilers, optimizers, and runtime 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 converts it 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The LLVM Getting Started documentation may be out of date.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 workflow and configuration to get and build the LLVM source:
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Checkout LLVM (including related subprojects like Clang):
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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
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Configure and build LLVM and Clang:
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cd llvm-project -
mkdir build -
cd build -
cmake -G <generator> [options] ../llvmSome common 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:
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-DLLVM_ENABLE_PROJECTS='...'--- semicolon-separated list of the LLVM subprojects you'd like to additionally build. Can include any of: clang, clang-tools-extra, libcxx, libcxxabi, libunwind, lldb, compiler-rt, lld, polly, or debuginfo-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 pathname 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).
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Run your build tool of choice!
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The default target (i.e.
ninjaormake) will build all of LLVM. -
The
check-alltarget (i.e.ninja check-all) will run the regression tests to ensure everything is in working order. -
CMake will generate build 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, usemake -j NNN(NNN is the number of parallel jobs, use e.g. number of CPUs you have.)
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For more information see CMake
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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.