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David Blaikie 5c2451785d DebugInfo: Use debug_line.dwo for debug_macro.dwo
This is an alternative proposal to D81476 (and D82084) - the details were sufficiently confusing to me it seemed easier to write some code and see how it looks.

Reviewers: SouraVX

Differential Revision: https://reviews.llvm.org/D84278
2020-07-22 14:06:33 -07:00
clang For PR46800, implement the GCC __builtin_complex builtin. 2020-07-22 13:43:10 -07:00
clang-tools-extra Revert "Enable -Wsuggest-override in the LLVM build" and the follow-ups. 2020-07-22 20:23:58 +02:00
compiler-rt asan_device_setup's wrapper scripts not handling args with spaces correctly 2020-07-22 12:55:28 -07:00
debuginfo-tests Harmonize Python shebang 2020-07-16 21:53:45 +02:00
flang [flang] Fix an assert when RESHAPE() is called on empty strings 2020-07-22 12:21:58 -07:00
libc Add implementations for fmin, fminf, and fminl. Testing infrastructure update is splitted to https://reviews.llvm.org/D83931. 2020-07-21 17:24:15 -04:00
libclc [CMake] Bump CMake minimum version to 3.13.4 2020-07-22 14:25:07 -04:00
libcxx [libc++] Make sure we only consider _GNUC_VER_NEW when the compiler is GCC 2020-07-22 16:08:19 -04:00
libcxxabi [libc++] Add static_assert to make sure rate limiter doesn't use locks 2020-07-22 14:49:50 -04:00
libunwind [CMake] Bump CMake minimum version to 3.13.4 2020-07-22 14:25:07 -04:00
lld [CMake] Bump CMake minimum version to 3.13.4 2020-07-22 14:25:07 -04:00
lldb [lldb] Eliminate unneeded value parameters in Utility (NFC) 2020-07-22 13:56:23 -07:00
llvm DebugInfo: Use debug_line.dwo for debug_macro.dwo 2020-07-22 14:06:33 -07:00
mlir [mlir][linalg] Add vectorization transform for CopyOp 2020-07-22 12:40:42 -07:00
openmp [CMake] Bump CMake minimum version to 3.13.4 2020-07-22 14:25:07 -04:00
parallel-libs [CMake] Bump CMake minimum version to 3.13.4 2020-07-22 14:25:07 -04:00
polly [Polly] Run polly-update-format. NFC. 2020-07-22 15:46:30 -05:00
pstl [CMake] Bump CMake minimum version to 3.13.4 2020-07-22 14:25:07 -04:00
utils/arcanist Use in-tree clang-format-diff.py as Arcanist linter 2020-04-06 12:02:20 -04:00
.arcconfig [arcconfig] Default base to previous revision 2020-02-24 16:20:25 -08:00
.arclint Fix .arclint on Windows 2020-04-28 09:55:48 -07:00
.clang-format
.clang-tidy - Update .clang-tidy to ignore parameters of main like functions for naming violations in clang and llvm directory 2020-01-31 16:49:45 +00:00
.git-blame-ignore-revs Add some libc++ revisions to .git-blame-ignore-revs 2020-03-17 17:30:20 -04:00
.gitignore [clangd] Store index in '.cache/clangd/index' instead of '.clangd/index' 2020-07-07 14:53:45 +02:00
CONTRIBUTING.md
README.md Revert 'This is a test commit - ded57e1a06 2020-06-18 01:03:42 +05:30

README.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 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 work-flow and configuration to get and build the LLVM source:

  1. 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

  2. Configure and build LLVM and Clang:

    • cd llvm-project

    • mkdir build

    • cd build

    • cmake -G <generator> [options] ../llvm

      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 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 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 . [-- [options] <target>] or your build system specified above directly.

      • The default target (i.e. ninja or make) 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, where NNN 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.