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Roman Lebedev 6734018041
[Codegen][X86] EltsFromConsecutiveLoads(): if only have AVX1, ensure that the "load" is actually foldable (PR51615)
This fixes another reproducer from https://bugs.llvm.org/show_bug.cgi?id=51615
And again, the fix lies not in the code added in D105390

In this case, we completely don't check that the "broadcast-from-mem" we create
can actually fold the load. In this case, it's operand was not a load at all:
```
Combining: t16: v8i32 = vector_shuffle<0,u,u,u,0,u,u,u> t14, undef:v8i32
Creating new node: t29: i32 = undef
RepeatLoad:
t8: i32 = truncate t7
  t7: i64 = extract_vector_elt t5, Constant:i64<0>
    t5: v2i64,ch = load<(load (s128) from %ir.arg)> t0, t2, undef:i64
      t2: i64,ch = CopyFromReg t0, Register:i64 %0
        t1: i64 = Register %0
      t4: i64 = undef
    t3: i64 = Constant<0>
Combining: t15: v8i32 = undef

```

Reviewed By: RKSimon

Differential Revision: https://reviews.llvm.org/D108821
2021-08-27 20:26:53 +03:00
.github
clang [MCParser][z/OS] Mark test as unsupported for the z/OS Target 2021-08-27 11:45:38 -04:00
clang-tools-extra [clang-tidy] Add bugprone-suspicious-memory-comparison check 2021-08-26 09:23:37 +02:00
compiler-rt [ORC][ORC-RT] Reapply "Introduce ELF/*nix Platform and runtime..." with fixes. 2021-08-27 14:41:58 +10:00
cross-project-tests
flang [flang] Take result length into account in ApplyElementwise folding 2021-08-26 09:46:14 +02:00
libc [libc][Obvious] Add header guards for the generated linux syscall header file. 2021-08-27 16:17:53 +00:00
libclc
libcxx [libcxx] Use GetSystemTimePreciseAsFileTime() if available 2021-08-27 20:11:29 +03:00
libcxxabi
libunwind [libunwind] Don't include cet.h/immintrin.h unconditionally 2021-08-26 11:37:07 +02:00
lld [lld/COFF] Ignore /LTCG, /LTCG:, /LTCGOUT:, /ILK: flags 2021-08-27 09:13:30 -04:00
lldb [trace] [intel pt] Create a "process trace save" command 2021-08-27 09:34:01 -07:00
llvm [Codegen][X86] EltsFromConsecutiveLoads(): if only have AVX1, ensure that the "load" is actually foldable (PR51615) 2021-08-27 20:26:53 +03:00
mlir [mlir][spirv] Initial support for 64 bit index type and builtins 2021-08-27 01:38:53 +03:00
openmp [openmp][amdgpu] Initial gfx10 offloading implementation 2021-08-27 12:34:03 +01:00
parallel-libs
polly polly: remove the old reference to svn in the doc 2021-08-27 10:46:50 +02:00
pstl
runtimes
utils [mlir][linalg] Replace AffineMinSCFCanonicalizationPattern with SCF reimplementation 2021-08-25 08:52:56 +09:00
.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:

  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

    • 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 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.