28b1dcb122
Resolve a crash related to split functions
Due to split function optimization, a function can be divided to two
fragments, and both fragments can access same jump table. This
violates
the assumption that a jump table can only have one parent
function,
which causes a crash during instrumentation.
We want to support the case: different functions cannot access same
jump tables, but different fragments of same function can!
As all fragments are from same function, we point JT::Parent to one
specific fragment. Right now it is the first disassembled fragment, but
we can point it to the function's main fragment later.
Functions are disassembled sequentially. Previously, at the end of
processing a function, JT::OffsetEntries is cleared, so other fragment
can no longer reuse JT::OffsetEntries. To extend the support for split
function, we only clear JT::OffsetEntries after all functions are
disassembled.
Let say A.hot and A.cold access JT of three targets {X, Y, Z}, where
X and Y are in A.hot, and Z is in A.cold. Suppose that A.hot is
disassembled first, JT::OffsetEntries = {X',Y',INVALID_OFFSET}. When
A.cold is disassembled, it cannot reuse JT::OffsetEntries above due to
different fragment start. A simple solution:
A.hot = {X',Y',INVALID_OFFSET}
A.cold = {INVALID_OFFSET, INVALID_OFFSET, INVALID_OFFSET}
We update the assertion to allow different fragments of same function
to get the same JumpTable object.
Potential improvements:
A.hot = {X',Y',INVALID_OFFSET}
A.cold = {INVALID_OFFSET, INVALID_OFFSET, Z'}
The main issue is A.hot and A.cold have separate CFGs, thus jump table
targets are still constrained within fragment bounds.
Future improvements:
A.hot = {X, Y, Z}
A.cold = {X, Y, Z}
Reviewed By: Amir
Differential Revision: https://reviews.llvm.org/D127924
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.
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