e28b15b572
(Re-Apply with fixes to clang MicrosoftMangle.cpp) This is a first step towards high level representation for fp8 types that have been built in to hardware with near term roadmaps. Like the BFLOAT16 type, the family of fp8 types are inspired by IEEE-754 binary floating point formats but, due to the size limits, have been tweaked in various ways in order to maximally use the range/precision in various scenarios. The list of variants is small/finite and bounded by real hardware. This patch introduces the E5M2 FP8 format as proposed by Nvidia, ARM, and Intel in the paper: https://arxiv.org/pdf/2209.05433.pdf As the more conformant of the two implemented datatypes, we are plumbing it through LLVM's APFloat type and MLIR's type system first as a template. It will be followed by the range optimized E4M3 FP8 format described in the paper. Since that format deviates further from the IEEE-754 norms, it may require more debate and implementation complexity. Given that we see two parts of the FP8 implementation space represented by these cases, we are recommending naming of: * `F8M<N>` : For FP8 types that can be conceived of as following the same rules as FP16 but with a smaller number of mantissa/exponent bits. Including the number of mantissa bits in the type name is enough to fully specify the type. This naming scheme is used to represent the E5M2 type described in the paper. * `F8M<N>F` : For FP8 types such as E4M3 which only support finite values. The first of these (this patch) seems fairly non-controversial. The second is previewed here to illustrate options for extending to the other known variant (but can be discussed in detail in the patch which implements it). Many conversations about these types focus on the Machine-Learning ecosystem where they are used to represent mixed-datatype computations at a high level. At that level (which is why we also expose them in MLIR), it is important to retain the actual type definition so that when lowering to actual kernels or target specific code, the correct promotions, casts and rescalings can be done as needed. We expect that most LLVM backends will only experience these types as opaque `I8` values that are applicable to some instructions. MLIR does not make it particularly easy to add new floating point types (i.e. the FloatType hierarchy is not open). Given the need to fully model FloatTypes and make them interop with tooling, such types will always be "heavy-weight" and it is not expected that a highly open type system will be particularly helpful. There are also a bounded number of floating point types in use for current and upcoming hardware, and we can just implement them like this (perhaps looking for some cosmetic ways to reduce the number of places that need to change). Creating a more generic mechanism for extending floating point types seems like it wouldn't be worth it and we should just deal with defining them one by one on an as-needed basis when real hardware implements a new scheme. Hopefully, with some additional production use and complete software stacks, hardware makers will converge on a set of such types that is not terribly divergent at the level that the compiler cares about. (I cleaned up some old formatting and sorted some items for this case: If we converge on landing this in some form, I will NFC commit format only changes as a separate commit) Differential Revision: https://reviews.llvm.org/D133823 |
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| .github | ||
| bolt | ||
| clang | ||
| clang-tools-extra | ||
| cmake | ||
| compiler-rt | ||
| cross-project-tests | ||
| flang | ||
| libc | ||
| libclc | ||
| libcxx | ||
| libcxxabi | ||
| libunwind | ||
| lld | ||
| lldb | ||
| llvm | ||
| llvm-libgcc | ||
| mlir | ||
| openmp | ||
| polly | ||
| pstl | ||
| runtimes | ||
| third-party | ||
| utils | ||
| .arcconfig | ||
| .arclint | ||
| .clang-format | ||
| .clang-tidy | ||
| .git-blame-ignore-revs | ||
| .gitignore | ||
| .mailmap | ||
| CONTRIBUTING.md | ||
| LICENSE.TXT | ||
| README.md | ||
| SECURITY.md | ||
README.md
The LLVM Compiler Infrastructure
This directory and its sub-directories contain the 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 here.
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 frontend. 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:
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Checkout LLVM (including related sub-projects like Clang):
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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
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Configure and build LLVM and Clang:
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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:
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-DLLVM_ENABLE_PROJECTS='...'and-DLLVM_ENABLE_RUNTIMES='...'--- semicolon-separated list of the LLVM sub-projects and runtimes you'd like to additionally build.LLVM_ENABLE_PROJECTScan include any of: clang, clang-tools-extra, cross-project-tests, flang, libc, libclc, lld, lldb, mlir, openmp, polly, or pstl.LLVM_ENABLE_RUNTIMEScan include any of libcxx, libcxxabi, libunwind, compiler-rt, libc or openmp. Some runtime projects can be specified either inLLVM_ENABLE_PROJECTSor inLLVM_ENABLE_RUNTIMES.For example, to build LLVM, Clang, libcxx, and libcxxabi, use
-DLLVM_ENABLE_PROJECTS="clang" -DLLVM_ENABLE_RUNTIMES="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). Be careful if you install runtime libraries: if your system uses those provided by LLVM (like libc++ or libc++abi), you must not overwrite your system's copy of those libraries, since that could render your system unusable. In general, using something like/usris not advised, but/usr/localis fine. -
-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).
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cmake --build build [-- [options] <target>]or your build system specified above directly.-
The default target (i.e.
ninjaormake) will build all of LLVM. -
The
check-alltarget (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, whereNNNis the number of parallel jobs to run. In most cases, you get the best performance if you specify the number of CPU threads you have. On some Unix systems, you can specify this with-j$(nproc).
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For more information see CMake.
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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.
Getting in touch
Join LLVM Discourse forums, discord chat or #llvm IRC channel on OFTC.
The LLVM project has adopted a code of conduct for participants to all modes of communication within the project.