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avarmapml 6d4f7801b1 [MLIR] Support for ReturnOps in memref map layout normalization
-- This commit handles the returnOp in memref map layout normalization.
-- An initial filter is applied on FuncOps which helps us know which functions can be
   a suitable candidate for memref normalization which doesn't lead to invalid IR.
-- Handles memref map normalization for external function assuming the external function
   is normalizable.

Differential Revision: https://reviews.llvm.org/D85226
2020-08-13 19:10:47 +05:30
clang [SyntaxTree] Clean #includes in TreeTestBase.h 2020-08-13 13:30:57 +00:00
clang-tools-extra [clangd] Express dumpAST in tests as a customAction() 2020-08-13 14:27:32 +02:00
compiler-rt [compiler-rt][asan][test] Skipt sanitizer_common tests on Sparc 2020-08-13 10:20:52 +02:00
debuginfo-tests Harmonize Python shebang 2020-07-16 21:53:45 +02:00
flang [flang] Compilation fix. 2020-08-13 03:05:05 -05:00
libc [libc][obvious] Remove the unused file utils/CPP/StringRef.h. 2020-08-12 12:19:11 -07:00
libclc [CMake] Bump CMake minimum version to 3.13.4 2020-07-22 14:25:07 -04:00
libcxx [libc++][test] Fix -Wstring-concatenation warnings 2020-08-13 08:51:15 -04:00
libcxxabi [libc++abi] Make sure we use a 32 bit guard on 32 bit Aarch64 2020-08-04 15:12:03 -04:00
libunwind [libunwind] Fix incorrect check for out-of-boundedness 2020-08-11 15:37:57 -04:00
lld [lld-macho] Fix invalid-stub test on Windows, take 2 2020-08-12 22:21:57 -07:00
lldb [lldb][NFC] Use llvm::is_contained instead of std::find in a few places 2020-08-13 14:11:28 +02:00
llvm [gn build] Port d17437d2bd 2020-08-13 13:35:44 +00:00
mlir [MLIR] Support for ReturnOps in memref map layout normalization 2020-08-13 19:10:47 +05:30
openmp [OpenMP] Fix ref count dec for implicit map of partial data 2020-08-06 11:39:29 -04:00
parallel-libs Reapply "Try enabling -Wsuggest-override again, using add_compile_options instead of add_compile_definitions for disabling it in unittests/ directories." 2020-07-22 17:50:19 -07:00
polly [Polly] Reuse LLVM's build rules for gtest/gmock 2020-08-09 12:53:31 +02:00
pstl [libc++][pstl] Remove c++98 from UNSUPPORTED annotations 2020-07-29 14:17:32 -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 PR46997: don't run clang-format on clang's testcases. 2020-08-04 17:53:25 -07:00
.clang-format
.clang-tidy
.git-blame-ignore-revs NFC: Add whitespace changing revisions to .git-blame-ignore-revs 2020-07-28 13:10:05 -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

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.