Matt Arsenault bc20bdb9f9 AMDGPU/GlobalISel: Start rewriting load/store legality rules
The current set is an incomprehensible mess riddled with ordering
hacks for various limitations in the legalizer at the time of writing,
many of which have been fixed. This takes a very small step in
correcting this.

The core first change is to start checking for fully legal cases
first, rather than trying to figure out all of the actions that could
need to be performed. It's recommended to check the legal cases first
for faster legality checks in the common case. This still has a table
listing some common cases, but it needs measuring whether this really
helps or not.

More significantly, stop trying to allow any arbitrary type with a
legal bitwidth as a legal memory type, and start using the bitcast
legalize action for them. Allowing loads of these weird vector types
produced new burdens we don't need for handling all of the
legalization artifacts. Unlike the SelectionDAG handling, this is
still not casting 64 or 16-bit element vectors to 32-bit
vectors. These cases should still be handled by increasing/decreasing
the number of 16-bit elements. This is primarily to fix 8-bit element
vectors.

Another change is to stop trying to handle the load-widening based on
a higher alignment. We should still do this, but the way it was
handled wasn't really correct. We really need to modify the MMO's size
at the same time, and not just increase the result type. The
LegalizerHelper does not do this, and I think this would really
require a separate WidenMemory action (or to add a memory action
payload to the LegalizeMutation). These will now fail to legalize.

The structure of the legalizer rules makes writing concise rules here
difficult. It would be easier if the same function could answer the
query the query, and report the action to perform at the same
time. Instead these two are split into distinct predicate and action
functions. This is mostly tolerable for other cases, but the
load/store rules get pretty complicated so it's difficult to keep two
versions of these functions in sync.
2020-06-06 09:59:46 -04:00
2020-05-29 09:18:37 +02:00
2020-04-28 09:55:48 -07:00
2020-04-11 15:55:07 -07:00

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.

Description
The LLVM Project is a collection of modular and reusable compiler and toolchain technologies.
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