91b0cad813
The Arm backend will usually return false for isFMAFasterThanFMulAndFAdd, where both the fused VFMA.f32 and a non-fused VMLA.f32 are usually available for scalar code. For MVE we don't have the non-fused version though. It makes more sense for isFMAFasterThanFMulAndFAdd to return true, allowing us to simplify some of the existing ISel patterns. The tests here are that non of the existing tests failed, and so we are still selecting VFMA and VFMS. The one test that changed shows we can now select from fast math flags, as opposed to just relying on the isFMADLegalForFAddFSub option. Differential Revision: https://reviews.llvm.org/D69115 |
||
---|---|---|
clang | ||
clang-tools-extra | ||
compiler-rt | ||
debuginfo-tests | ||
libc | ||
libclc | ||
libcxx | ||
libcxxabi | ||
libunwind | ||
lld | ||
lldb | ||
llgo | ||
llvm | ||
openmp | ||
parallel-libs | ||
polly | ||
pstl | ||
.arcconfig | ||
.clang-format | ||
.clang-tidy | ||
.git-blame-ignore-revs | ||
.gitignore | ||
README.md |
README.md
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.
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The LLVM Getting Started documentation may be out of date.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:
-
Checkout LLVM (including related subprojects 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
-
mkdir build
-
cd build
-
cmake -G <generator> [options] ../llvm
Some 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:
-
-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).
-
Run your build tool of choice!
-
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 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.)
-
-
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.