llvm with tablegen backend for capstone disassembler
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Craig Topper 79e798aca3 Recommit "[RISCV] Add a test of vector sadd.overflow to demonstrate intrinsics with multiple scalable vector results."
This recommits 2c51bef76c.

I've fixed the broken check line from when I renamed the test function.

Original commit message:
This builds on D94142 where scalable vectors are allowed in structs.

I did have to fix one scalable vector issue in the vector type
creation for these intrinsics where we used getVectorNumElements
instead of ElementCount.
2021-01-18 11:08:28 -08:00
.github [github] Move repo lockdown config into llvm-project repo 2021-01-11 16:20:08 -08:00
clang [clang] Allow LifetimeExtendedTemporary to have no access specifier 2021-01-18 19:19:57 +01:00
clang-tools-extra [clangd] Derive new signals in CC from ASTSignals. 2021-01-18 17:37:27 +01:00
compiler-rt hwasan: Update register-dump-read.c test to reserve x23 instead of x20. 2021-01-15 16:14:36 -08:00
debuginfo-tests Fix check-gdb-mlir-support build after MLIR API changed to take Context as first argument 2021-01-07 21:30:39 +00:00
flang [flang] Create names to allow access to inaccessible specifics 2021-01-15 16:56:38 -08:00
libc [libc] CopyAlignedBlocks can now specify alignment on top of block size 2021-01-15 15:32:02 +00:00
libclc
libcxx Fix libc++ clang-cl build, swap attribute order 2021-01-15 11:44:13 -08:00
libcxxabi [libc++/abi] Re-remove unnecessary null pointer checks from operator delete 2021-01-08 17:03:50 -05:00
libunwind [VE] Support VE in libunwind 2021-01-17 15:35:02 +09:00
lld [LLD][ELF][AArch64] Set _GLOBAL_OFFSET_TABLE_ at the start of .got 2021-01-18 14:51:14 -03:00
lldb [lldb][docs] Use 'any' as the default role in LLDB's sphinx project 2021-01-18 19:08:19 +01:00
llvm Recommit "[RISCV] Add a test of vector sadd.overflow to demonstrate intrinsics with multiple scalable vector results." 2021-01-18 11:08:28 -08:00
mlir [MLIR] NFC: simplify PresburgerSet::isEqual 2021-01-18 22:47:25 +05:30
openmp Revert "[OpenMP] Added the support for hidden helper task in RTL" 2021-01-18 06:57:52 -05:00
parallel-libs
polly [NFC] Rename ThinLTOPhase to ThinOrFullLTOPhase and move it from PassBuilder.h 2021-01-13 15:55:40 -08:00
pstl [pstl] Replace direct use of assert() with _PSTL_ASSERT 2020-11-02 18:35:54 -05:00
runtimes [MSVC] Don't add -nostdinc++ -isystem to runtimes builds 2021-01-15 13:22:07 -08:00
utils/arcanist
.arcconfig Set the target branch for arc land to main 2020-12-07 21:57:32 +00:00
.arclint
.clang-format
.clang-tidy
.git-blame-ignore-revs
.gitignore Reland [lldb][docs] Use sphinx instead of epydoc to generate LLDB's Python reference 2021-01-17 12:13:01 +01:00
CONTRIBUTING.md
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.