Google Git
Sign in
llvm / llvm-project / 8cd782487fe68082e57d24a576b77f529d77f96c
commit8cd782487fe68082e57d24a576b77f529d77f96c[log] [tgz]
authorRoman Lebedev <lebedev.ri@gmail.com>Tue Nov 30 10:36:20 2021 +0300
committerRoman Lebedev <lebedev.ri@gmail.com>Tue Nov 30 10:47:56 2021 +0300
tree0fc1edf73a3e25f685e256dfbdf64371100a9060
parent89453ed6f2059b5cec576fc41914def713fe38f7 [diff]
[X86][LoopVectorize] "Fix" `X86TTIImpl::getAddressComputationCost()`

We ask `TTI.getAddressComputationCost()` about the cost of computing vector address,
and then multiply it by the vector width. This doesn't make any sense,
it implies that we'd do a vector GEP and then scalarize the vector of pointers,
but there is no such thing in the vectorized IR, we perform scalar GEP's.

This is *especially* bad on X86, and was effectively prohibiting any scalarized
vectorization of gathers/scatters, because `X86TTIImpl::getAddressComputationCost()`
says that cost of vector address computation is `10` as compared to `1` for scalar.

The computed costs are similar to the ones with D111222+D111220,
but we end up without masked memory intrinsics that we'd then have to
expand later on, without much luck. (D111363)

Differential Revision: https://reviews.llvm.org/D111460
17 files changed
tree: 0fc1edf73a3e25f685e256dfbdf64371100a9060
  1. .github/
  2. clang/
  3. clang-tools-extra/
  4. cmake/
  5. compiler-rt/
  6. cross-project-tests/
  7. flang/
  8. libc/
  9. libclc/
  10. libcxx/
  11. libcxxabi/
  12. libunwind/
  13. lld/
  14. lldb/
  15. llvm/
  16. mlir/
  17. openmp/
  18. polly/
  19. pstl/
  20. runtimes/
  21. utils/
  22. .arcconfig
  23. .arclint
  24. .clang-format
  25. .clang-tidy
  26. .git-blame-ignore-revs
  27. .gitignore
  28. .mailmap
  29. CONTRIBUTING.md
  30. README.md
  31. SECURITY.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 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, compiler-rt,cross-project-tests, flang, libc, libclc, libcxx, libcxxabi, libunwind, lld, lldb, mlir, openmp, polly, or pstl.

        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.