commit	3f170eb197906c2a793e62b54870296a4f5d722a	[log] [tgz]
author	Michael Kruse <llvm-project@meinersbur.de>	Mon Mar 15 12:13:21 2021 -0500
committer	Michael Kruse <llvm-project@meinersbur.de>	Mon Mar 15 13:05:39 2021 -0500
tree	04e5a4042b035ebba9e1f181efd6dfda20011b6b
parent	ab86edbc88fa41e9cb9c6b43d99b69278c9c5040 [diff]

[Polly][Optimizer] Apply user-directed unrolling.

Make Polly look for unrolling metadata (https://llvm.org/docs/TransformMetadata.html#loop-unrolling) that is usually only interpreted by the LoopUnroll pass and apply it to the SCoP's schedule.

While not that useful by itself (there already is an unroll pass), it introduces mechanism to apply arbitrary loop transformation directives in arbitrary order to the schedule. Transformations are applied until no more directives are found. Since ISL's rescheduling would discard the manual transformations and it is assumed that when the user specifies the sequence of transformations, they do not want any other transformations to apply. Applying user-directed transformations can be controlled using the `-polly-pragma-based-opts` switch and is enabled by default.

This does not influence the SCoP detection heuristic. As a consequence, loop that do not fulfill SCoP requirements or the initial profitability heuristic will be ignored. `-polly-process-unprofitable` can be used to disable the latter.

Other than manually editing the IR, there is currently no way for the user to add loop transformations in an order other than the order in the default pipeline, or transformations other than the one supported by clang's LoopHint. See the `unroll_double.ll` test as example that clang currently is unable to emit. My own extension of `#pragma clang loop` allowing an arbitrary order and additional transformations is available here: https://github.com/meinersbur/llvm-project/tree/pragma-clang-loop. An effort to upstream this functionality as `#pragma clang transform` (because `#pragma clang loop` has an implicit transformation order defined by the loop pipeline) is D69088.

Additional transformations from my downstream pragma-clang-loop branch are tiling, interchange, reversal, unroll-and-jam, thread-parallelization and array packing. Unroll was chosen because it uses already-defined metadata and does not require correctness checks.

Reviewed By: sebastiankreutzer

Differential Revision: https://reviews.llvm.org/D97977

18 files changed

tree: 04e5a4042b035ebba9e1f181efd6dfda20011b6b

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 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:

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
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 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 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.