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Learn LLVM 17 - Second Edition
Learn LLVM 17 - Second Edition

Learn LLVM 17: A beginner's guide to learning LLVM compiler tools and core libraries with C++, Second Edition

By Kai Nacke , Amy Kwan
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Learn LLVM 17 - Second Edition

Installing LLVM

In order to learn how to work with LLVM, it is best to begin by compiling LLVM from source. LLVM is an umbrella project and the GitHub repository contains the source of all projects belonging to LLVM. Each LLVM project is in a top-level directory of the repository. Besides cloning the repository, your system must also have all tools installed that are required by the build system. In this chapter, you will learn about the following topics:

  • Getting the prerequisites ready, which will show you how to set up your build system
  • Cloning the repository and building from source, which will cover how to get the LLVM source code, and how to compile and install the LLVM core libraries and clang with CMake and Ninja
  • Customizing the build process, which will talk about the various possibilities for influencing the build process

Compiling LLVM versus installing binaries

You can install LLVM binaries from various sources. If you are using Linux, then your distribution contains the LLVM libraries. Why bother compiling LLVM yourself?

First, not all install packages contain all the files required for developing with LLVM. Compiling and installing LLVM yourself prevents this problem. Another reason stems from the fact that LLVM is highly customizable. With building LLVM, you learn how you can customize LLVM, and this will enable you to diagnose problems that may arise if you bring your LLVM application to another platform. And last, in the third part of this book, you will extend LLVM itself, and for this, you need the skill of building LLVM yourself.

However, it is perfectly fine to avoid compiling LLVM for the first steps. If you want to go on this route, then you only need to install the prerequisites as described in the next section.

Note

Many Linux distributions split LLVM into several packages. Please make sure that you install the development package. For example, on Ubuntu, you need to install the llvm-dev package. Please also make sure that you install LLVM 17. For other versions, the examples in this book may require changes.

Getting the prerequisites ready

To work with LLVM, your development system should run a common operating system such as Linux, FreeBSD, macOS, or Windows. You can build LLVM and clang in different modes. A build with debug symbols enabled can take up to 30 GB of space. The required disk space depends heavily on the chosen build options. For example, building only the LLVM core libraries in release mode, targeting only one platform, requires about 2 GB of free disk space, which is the bare minimum needed.

To reduce compile times, a fast CPU (such as a quad-core CPU with a 2.5 GHz clock speed) and a fast SSD are also helpful. It is even possible to build LLVM on a small device such as a Raspberry Pi – it only takes a lot of time. The examples within this book were developed on a laptop with an Intel quad-core CPU running at a 2.7 GHz clock speed, with 40 GB RAM and 2.5 TB SSD disk space. This system is well suited for the development task.

Your development system must have some prerequisite software installed. Let’s review the minimal required version of these software packages.

To check out the source from GitHub, you need Git (https://git-scm.com/). There is no requirement for a specific version. The GitHub help pages recommend using at least version 1.17.10. Due to known security issues found in the past, it is recommended to use the latest available version, which is 2.39.1 at the time of writing.

The LLVM project uses CMake (https://cmake.org/) as the build file generator. At least the 3.20.0 version is required. CMake can generate build files for various build systems. In this book, Ninja (https://ninja-build.org/) is used because it is fast and available on all platforms. The latest version, 1.11.1, is recommended.

Obviously, you also need a C/C++ compiler. The LLVM projects are written in modern C++, based on the C++17 standard. A conforming compiler and standard library are required. The following compilers are known to work with LLVM 17:

  • gcc 7.1.0 or later
  • clang 5.0 or later
  • Apple clang 10.0 or later
  • Visual Studio 2019 16.7 or later

Tip

Please be aware that with further development of the LLVM project, the requirements for the compiler are most likely to change. In general, you should use the latest compiler version available for your system.

Python (https://python.org/) is used during the generation of the build files and for running the test suite. It should be at least the 3.8 version.

Although not covered in this book, there can be reasons that you need to use Make instead of Ninja. In this case, you need to use GNU Make (https://www.gnu.org/software/make/) version 3.79 or later. The usage of both build tools is very similar. It is sufficient to replace ninja in each command with make for the scenarios described below.

LLVM also depends on the zlib library (https://www.zlib.net/). You should have at least version 1.2.3.4 installed. As usual, we recommend using the latest version, 1.2.13.

To install the prerequisite software, the easiest way is to use the package manager from your operating system. In the following sections, the commands required to install the software are shown for the most popular operating systems.

Ubuntu

Ubuntu 22.04 uses the apt package manager. Most of the basic utilities are already installed; only the development tools are missing. To install all packages at once, you type the following:

$ sudo apt -y install gcc g++ git cmake ninja-build zlib1g-dev

Fedora and RedHat

The package manager of Fedora 37 and RedHat Enterprise Linux 9 is called dnf. Like Ubuntu, most of the basic utilities are already installed. To install all packages at once, you type the following:

$ sudo dnf –y install gcc gcc-c++ git cmake ninja-build \
  zlib-devel

FreeBSD

On FreeBSD 13 or later, you have to use the pkg package manager. FreeBSD differs from Linux-based systems in that the clang compiler is already installed. To install all other packages at once, you type the following:

$ sudo pkg install –y git cmake ninja zlib-ng

OS X

For development on OS X, it is best to install Xcode from the Apple store. While the Xcode IDE is not used in this book, it comes with the required C/C++ compilers and supporting utilities. For installation of the other tools, the package manager Homebrew (https://brew.sh/) can be used. To install all packages at once, you type the following:

$ brew install git cmake ninja zlib

Windows

Like OS X, Windows does not come with a package manager. For the C/C++ compiler, you need to download Visual Studio Community 2022 (https://visualstudio.microsoft.com/vs/community/), which is free for personal use. Please make sure that you install the workload named Desktop Development with C++. You can use the package manager Scoop (https://scoop.sh/) to install the other packages. After installing Scoop as described on the website, you open x64 Native Tools Command Prompt for VS 2022 from your Windows menu. To install the required packages, you type the following:

$ scoop install git cmake ninja python gzip bzip2 coreutils
$ scoop bucket add extras
$ scoop install zlib

Please watch the output from Scoop closely. For the Python and zlib packages, it advises adding some registry keys. These entries are needed so that other software can find these packages. To add the registry keys, you’d best copy and paste the output from Scoop, which looks like the following:

$ %HOMEPATH%\scoop\apps\python\current\install-pep-514.reg
$ %HOMEPATH%\scoop\apps\zlib\current\register.reg

After each command, a message window from the registry editor will pop up asking whether you really want to import those registry keys. You need to click on Yes to finish the import. Now all prerequisites are installed.

For all examples in this book, you must use the x64 Native Tools Command Prompt for VS 2022. Using this command prompt, the compiler is automatically added to the search path.

Tip

The LLVM code base is very large. To comfortably navigate the source, we recommend using an IDE that allows you to jump to the definition of classes and search through the source. We find Visual Studio Code (https://code.visualstudio.com/download), which is an extensible cross-platform IDE, very comfortable to use. However, this is no requirement for following the examples in this book.

Cloning the repository and building from source

With the build tools ready, you can now check out all LLVM projects from GitHub and build LLVM. This process is essentially the same on all platforms:

  1. Configure Git.
  2. Clone the repository.
  3. Create the build directory.
  4. Generate the build system files.
  5. Finally, build and install LLVM.

Let’s begin with configuring Git.

Configuring Git

The LLVM project uses Git for version control. If you have not used Git before, then you should do some basic configuration of Git first before continuing: to set the username and email address. Both pieces of information are used if you commit changes.

One can check whether they previously had an email and username already configured in Git with the following commands:

$ git config user.email
$ git config user.name

The preceding commands will output the respective email and username that you already have set when using Git. However, in the event that you are setting the username and email for the first time, the following commands can be entered for first-time configuration. In the following commands, you can simply replace Jane with your name and jane@email.org with your email:

$ git config --global user.email "jane@email.org"
$ git config --global user.name "Jane"

These commands change the global Git configuration. Inside a Git repository, you can locally overwrite those values by not specifying the --global option.

By default, Git uses the vi editor for commit messages. If you prefer another editor, then you can change the configuration in a similar way. To use the nano editor, you type the following:

$ git config --global core.editor nano

For more information about Git, please see the Git Version Control Cookbook (https://www.packtpub.com/product/git-version-control-cookbook-second-edition/9781789137545).

Now you are ready to clone the LLVM repository from GitHub.

Cloning the repository

The command to clone the repository is essentially the same on all platforms. Only on Windows, it is recommended to turn off the auto-translation of line endings.

On all non-Windows platforms, you type the following command to clone the repository:

$ git clone https://github.com/llvm/llvm-project.git

Only on Windows, add the option to disable auto-translation of line endings. Here, you type the following:

$ git clone --config core.autocrlf=false \
  https://github.com/llvm/llvm-project.git

This Git command clones the latest source code from GitHub into a local directory named llvm-project. Now change the current directory into the new llvm-project directory with the following command:

$ cd llvm-project

Inside the directory are all LLVM projects, each one in its own directory. Most notably, the LLVM core libraries are in the llvm subdirectory. The LLVM project uses branches for subsequent release development (“release/17.x”) and tags (“llvmorg-17.0.1”) to mark a certain release. With the preceding clone command, you get the current development state. This book uses LLVM 17. To check out the first release of LLVM 17 into a branch called llvm-17, you type the following:

$ git checkout -b llvm-17 llvmorg-17.0.1

With the previous steps, you cloned the whole repository and created a branch from a tag. This is the most flexible approach.

Git also allows you to clone only a branch or a tag (including history). With git clone --branch release/17.x https://github.com/llvm/llvm-project, you only clone the release/17.x branch and its history. You then have the latest state of the LLVM 17 release branch, so you only need to create a branch from the release tag like before if you need the exact release version. With the additional –-depth=1 option, which is known as a shallow clone with Git, you prevent the cloning of the history, too. This saves time and space but obviously limits what you can do locally, including checking out a branch based on the release tags.

Creating a build directory

Unlike many other projects, LLVM does not support inline builds and requires a separate build directory. Most easily, this is created inside the llvm-project directory, which is your current directory. Let us name the build directory, build, for simplicity. Here, the commands for Unix and Windows systems differ. On a Unix-like system, you use the following:

$ mkdir build

And on Windows, use the following:

$ md build

Now you are ready to create the build system files with the CMake tool inside this directory.

Generating the build system files

In order to generate build system files to compile LLVM and clang using Ninja, you run the following:

$ cmake -G Ninja -DCMAKE_BUILD_TYPE=Release \
  -DLLVM_ENABLE_PROJECTS=clang -B build -S llvm

The -G option tells CMake for which system to generate build files. Often-used values for that option are as follows:

  • Ninja – for the Ninja build system
  • Unix Makefiles – for GNU Make
  • Visual Studio 17 VS2022 – for Visual Studio and MS Build
  • Xcode – for Xcode projects

With the –B option, you tell CMake the path of the build directory. Similarly, you specify the source directory with the –S option. The generation process can be influenced by setting various variables with the –D option. Usually, they are prefixed with CMAKE_ (if defined by CMake) or LLVM_ (if defined by LLVM).

As mentioned previously, we are also interested in compiling clang alongside LLVM. With the LLVM_ENABLE_PROJECTS=clang variable setting, this allows CMake to generate the build files for clang in addition to LLVM. Furthermore, the CMAKE_BUILD_TYPE=Release variable tells CMake that it should generate build files for a release build.

The default value for the –G option depends on your platform, and the default value for the build type depends on the toolchain. However, you can define your own preference with environment variables. The CMAKE_GENERATOR variable controls the generator, and the CMAKE_BUILD_TYPE variable specifies the build type. If you use bash or a similar shell, then you can set the variables with the following:

$ export CMAKE_GENERATOR=Ninja
$ export CMAKE_BUILD_TYPE=Release

If you are using the Windows command prompt instead, then you set the variables with the following:

$ set CMAKE_GENERATOR=Ninja
$ set CMAKE_BUILD_TYPE=Release

With these settings, the command to create the build system files becomes the following, which is easier to type:

$ cmake -DLLVM_ENABLE_PROJECTS=clang -B build -S llvm

You will find more about CMake variables in the Customizing the build process section.

Compiling and installing LLVM

After the build files are generated, LLVM and clang can be compiled with the following:

$ cmake –-build build

This command runs Ninja under the hood because we told CMake to generate Ninja files in the configuration step. However, if you generate build files for a system such as Visual Studio, which supports multiple build configurations, then you need to specify the configuration to use for the build with the --config option. Depending on the hardware resources, this command runs for between 15 minutes (server with lots of CPU cores, memory, and fast storage) and several hours (dual-core Windows notebook with limited memory).

By default, Ninja utilizes all available CPU cores. This is good for the speed of compilation but may prevent other tasks from running; for example, on a Windows-based notebook, it is almost impossible to surf the internet while Ninja is running. Fortunately, you can limit the resource usage with the j option.

Let’s assume you have four CPU cores available and Ninja should only use two (because you have parallel tasks to run); you then use this command for compilation:

$ cmake --build build –j2

After compilation is finished, a best practice is to run the test suite to check whether everything works as expected:

$ cmake --build build --target check-all

Again, the runtime of this command varies widely with the available hardware resources. The check-all Ninja target runs all test cases. Targets are generated for each directory containing test cases. Using check-llvm instead of check-all runs the LLVM tests but not the clang tests; check-llvm-codegen runs only the tests in the CodeGen directory from LLVM (that is, the llvm/test/CodeGen directory).

You can also do a quick manual check. One of the LLVM applications is llc, the LLVM compiler. If you run it with the -version option, it shows the LLVM version, the host CPU, and all supported architectures:

$ build/bin/llc --version

If you have trouble getting LLVM compiled, then you should consult the Common Problems section of the Getting Started with the LLVM System documentation https://releases.llvm.org/17.0.1/docs/GettingStarted.html#common-problems) for solutions to typical problems.

As the last step, you can install the binaries:

$ cmake --install build

On a Unix-like system, the install directory is /usr/local. On Windows, C:\Program Files\LLVM is used. This can be changed, of course. The next section explains how.

Customizing the build process

The CMake system uses a project description in the CMakeLists.txt file. The top-level file is in the llvm directory, llvm/CMakeLists.txt. Other directories also have CMakeLists.txt files, which are recursively included during the generation process.

Based on the information provided in the project description, CMake checks which compilers are installed, detects libraries and symbols, and creates the build system files, for example, build.ninja or Makefile (depending on the chosen generator). It is also possible to define reusable modules, for example, a function to detect whether LLVM is installed. These scripts are placed in the special cmake directory (llvm/cmake), which is searched automatically during the generation process.

The build process can be customized with the definition of CMake variables. The command-line option –D is used to set a variable to a value. The variables are used in the CMake scripts. Variables defined by CMake itself are almost always prefixed with CMAKE_ and these variables can be used in all projects. Variables defined by LLVM are prefixed with LLVM_ but they can only be used if the project definition includes the use of LLVM.

Variables defined by CMake

Some variables are initialized with the value of environment variables. Most notable are CC and CXX, which define the C and C++ compilers to be used for building. CMake tries to locate a C and a C++ compiler automatically, using the current shell search path. It picks the first compiler found. If you have several compilers installed, for example, gcc and clang or different versions of clang, then this might not be the compiler you want for building LLVM.

Suppose you like to use clang17 as a C compiler and clang++17 as a C++ compiler. Then, you can invoke CMake in a Unix shell in the following way:

$ CC=clang17 CXX=clang++17 cmake –B build –S llvm

This sets the value of the environment variables only for the invocation of cmake. If necessary, you can specify an absolute path for the compiler executables.

CC is the default value of the CMAKE_C_COMPILER CMake variable, and CXX is the default value of the CMAKE_CXX_COMPILER CMake variable. Instead of using the environment variables, you can set the CMake variables directly. This is equivalent to the preceding call:

$ cmake –DCMAKE_C_COMPILER=clang17 \
  -DCMAKE_CXX_COMPILER=clang++17 –B build –S llvm

Other useful variables defined by CMake are as follows:

Variable name

Purpose

CMAKE_INSTALL_PREFIX

This is a path prefix that is prepended to every path during installation. The default is /usr/local on Unix and C:\Program Files\<Project> on Windows. To install LLVM in the /opt/llvm directory, you specify -DCMAKE_INSTALL_PREFIX=/opt/llvm. The binaries are copied to /opt/llvm/bin, library files to /opt/llvm/lib, and so on.

CMAKE_BUILD_TYPE

Different types of build require different settings. For example, a debug build needs to specify options to generate debug symbols and usually link against debug versions of system libraries. In contrast, a release build uses optimization flags and links against production versions of libraries. This variable is only used for build systems that can only handle one build type, for example, Ninja or Make. For IDE build systems, all variants are generated and you have to use the mechanism of the IDE to switch between build types. Possible values are as follows:

DEBUG: build with debug symbols

RELEASE: build with optimization for speed

RELWITHDEBINFO: release build with debug symbols

MINSIZEREL: build with optimization for size

The default build type is taken from the CMAKE_BUILD_TYPE environment variable. If this variable is not set, then the default depends on the used toolchain and is often empty. In order to generate build files for a release build, you specify -DCMAKE_BUILD_TYPE=RELEASE.

CMAKE_C_FLAGS

CMAKE_CXX_FLAGS

These are extra flags used when compiling C and C++ source files. The initial values are taken from the CFLAGS and CXXFLAGS environment variables, which can be used as an alternative.

CMAKE_MODULE_PATH

This specifies additional directories that are searched for CMake modules. The specified directories are searched before the default ones. The value is a semicolon-separated list of directories.

PYTHON_EXECUTABLE

If the Python interpreter is not found or if the wrong one is picked in case you have installed multiple versions, you can set this variable to the path of the Python binary. This variable only has an effect if the Python module of CMake is included (which is the case for LLVM).

Table 1.1 - Additional useful variables provided by CMake

CMake provides built-in help for variables. The --help-variable var option prints help for the var variable. For instance, you can type the following to get help for CMAKE_BUILD_TYPE:

$ cmake --help-variable CMAKE_BUILD_TYPE

You can also list all variables with the following command:

$ cmake --help-variable-list

This list is very long. You may want to pipe the output to more or a similar program.

Using LLVM-defined build configuration variables

The build configuration variables defined by LLVM work in the same way as those defined by CMake except that there is no built-in help. The most useful variables are found in the following tables, where they are divided into variables that are useful for first-time users installing LLVM, and also variables for more advanced LLVM users.

Variables useful for first-time users installing LLVM

Variable name

Purpose

LLVM_TARGETS_TO_BUILD

LLVM supports code generation for different CPU architectures. By default, all these targets are built. Use this variable to specify the list of targets to build, separated by semicolons. The current targets are AArch64, AMDGPU, ARM, AVR, BPF, Hexagon, Lanai, LoongArch, Mips, MSP430, NVPTX, PowerPC, RISCV, Sparc, SystemZ, VE, WebAssembly, X86, and XCore. all can be used as shorthand for all targets. The names are case-sensitive. To only enable the PowerPC and the System Z target, you specify -DLLVM_TARGETS_TO_BUILD="PowerPC;SystemZ".

LLVM_EXPERIMENTAL_TARGETS_TO_BUILD

In addition to the official targets, the LLVM source tree also contains experimental targets. These targets are under development and often do not yet support the full functionality of a backend. The current list of experimental targets is ARC, CSKY, DirectX, M68k, SPIRV, and Xtensa. To build the M68k target, you specify -D LLVM_EXPERIMENTAL_TARGETS_TO_BUILD=M68k.

LLVM_ENABLE_PROJECTS

This is a list of the projects you want to build, separated by semicolons. The source for the projects must be on the same level as the llvm directory (side-by-side layout). The current list is bolt, clang, clang-tools-extra, compiler-rt, cross-project-tests, libc, libclc, lld, lldb, mlir, openmp, polly, and pstl. all can be used as shorthand for all projects in this list. Additionally, you can specify the flang project here. Due to some special build requirements, it is not yet part of the all list.

To build clang and bolt together with LLVM, you specify -DLLVM_ENABLE_PROJECT="clang;bolt".

Table 1.2 - Useful variables for first-time LLVM users

Variables for advanced users of LLVM

LLVM_ENABLE_ASSERTIONS

If set to ON, then assertion checks are enabled. These checks help to find errors and are very useful during development. The default value is ON for a DEBUG build and otherwise OFF. To turn assertion checks on (e.g. for a RELEASE build), you specify –DLLVM_ENABLE_ASSERTIONS=ON.

LLVM_ENABLE_EXPENSIVE_CHECKS

This enables some expensive checks that can really slow down compilation speed or consume large amounts of memory. The default value is OFF. To turn these checks on, you specify -DLLVM_ENABLE_EXPENSIVE_CHECKS=ON.

LLVM_APPEND_VC_REV

LLVM tools such as llc display the LLVM version they are based on besides other information if the –version command-line option is given. This version information is based on the LLVM_REVISION C macro. By default, not only the LLVM version but also the current Git hash is part of the version information. This is handy in case you are following the development of the master branch because it makes clear on which Git commit the tool is based. If not needed, then this can be turned off with –DLLVM_APPEND_VC_REV=OFF.

LLVM_ENABLE_THREADS

LLVM automatically includes thread support if a threading library is detected (usually the pthreads library). Further, LLVM assumes in this case that the compiler supports TLS (thread-local storage). If you don’t want thread support or your compiler does not support TLS, then you can turn it off with -DLLVM_ENABLE_THREADS=OFF.

LLVM_ENABLE_EH

The LLVM projects do not use C++ exception handling and therefore turn exception support off by default. This setting can be incompatible with other libraries your project is linking with. If needed, you can enable exception support by specifying –DLLVM_ENABLE_EH=ON.

LLVM_ENABLE_RTTI

LLVM uses a lightweight, self-build system for runtime type information. The generation of C++ RTTI is turned off by default. Like the exception handling support, this may be incompatible with other libraries. To turn generation of C++ RTTI on, you specify –DLLVM_ENABLE_RTTI=ON.

LLVM_ENABLE_WARNINGS

Compiling LLVM should generate no warning messages if possible. The option to print warning messages is therefore turned on by default. To turn it off, you specify –DLLVM_ENABLE_WARNINGS=OFF.

LLVM_ENABLE_PEDANTIC

The LLVM source should be C/C++ language standard-conforming; hence, pedantic checking of the source is enabled by default. If possible, compiler-specific extensions are also disabled. To reverse this setting, you specify –DLLVM_ENABLE_PEDANTIC=OFF.

LLVM_ENABLE_WERROR

If set to ON, then all warnings are treated as errors – the compilation aborts as soon as warnings are found. It helps to find all remaining warnings in the source. By default, it is turned off. To turn it on, you specify –DLLVM_ENABLE_WERROR=ON.

LLVM_OPTIMIZED_TABLEGEN

Usually, the tablegen tool is built with the same options as all other parts of LLVM. At the same time, tablegen is used to generate large parts of the code generator. As a result, tablegen is much slower in a debug build, increasing the compile time noticeably. If this option is set to ON, then tablegen is compiled with optimization turned on even for a debug build, possibly reducing compile time. The default is OFF. To turn it on, you specify –DLLVM_OPTIMIZED_TABLEGEN=ON.

LLVM_USE_SPLIT_DWARF

If the build compiler is gcc or clang, then turning on this option will instruct the compiler to generate the DWARF debug information in a separate file. The reduced size of the object files reduces the link time of debug builds significantly. The default is OFF. To turn it on, you specify -LLVM_USE_SPLIT_DWARF=ON.

Table 1.3 - Useful variables for advanced LLVM users

Note

LLVM defines many more CMake variables. You can find the complete list in the LLVM documentation about CMake https://releases.llvm.org/17.0.1/docs/CMake.html#llvm-specific-variables. The preceding list contains only the ones you are most likely to need.

Summary

In this chapter, you prepared your development machine to compile LLVM. You cloned the GitHub repository and compiled your own version of LLVM and clang. The build process can be customized with CMake variables. You learned about useful variables and how to change them. Equipped with this knowledge, you can tweak LLVM to your needs.

In the next section, we will be taking a closer look at the structure of a compiler. We will be exploring the different components found inside the compiler, as well as different types of analyses that occur in it – specifically, the lexical, syntactical, and semantic analyses. Finally, we will also briefly touch on interfacing with an LLVM backend for code generation.

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Key benefits

  • Get to grips with using LLVM libraries step by step
  • Understand the high-level design of LLVM compilers and apply these principles to your own compiler
  • Add a new backend to target an unsupported CPU architecture
  • Purchase of the print or Kindle book includes a free PDF eBook

Description

LLVM was built to bridge the gap between the theoretical knowledge found in compiler textbooks and the practical demands of compiler development. With a modular codebase and advanced tools, LLVM empowers developers to build compilers with ease. This book serves as a practical introduction to LLVM, guiding you progressively through complex scenarios and ensuring that you navigate the challenges of building and working with compilers like a pro. The book starts by showing you how to configure, build, and install LLVM libraries, tools, and external projects. You’ll then be introduced to LLVM's design, unraveling its applications in each compiler stage: frontend, optimizer, and backend. Using a real programming language subset, you'll build a frontend, generate LLVM IR, optimize it through the pipeline, and generate machine code. Advanced chapters extend your expertise, covering topics such as extending LLVM with a new pass, using LLVM tools for debugging, and enhancing the quality of your code. You'll also focus on just-in-time compilation issues and the current state of JIT-compilation support with LLVM. Finally, you’ll develop a new backend for LLVM, gaining insights into target description and how instruction selection works. By the end of this book, you'll have hands-on experience with the LLVM compiler development framework through real-world examples and source code snippets.

What you will learn

Configure, compile, and install the LLVM framework Understand how the LLVM source is organized Discover what you need to do to use LLVM in your own projects Explore how a compiler is structured, and implement a tiny compiler Generate LLVM IR for common source language constructs Set up an optimization pipeline and tailor it for your own needs Extend LLVM with transformation passes and clang tooling Add new machine instructions and a complete backend

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Table of Contents

20 Chapters
Preface Chevron down icon Chevron up icon
1. Part 1: The Basics of Compiler Construction with LLVM Chevron down icon Chevron up icon
2. Chapter 1: Installing LLVM Chevron down icon Chevron up icon
3. Chapter 2: The Structure of a Compiler Chevron down icon Chevron up icon
4. Part 2: From Source to Machine Code Generation Chevron down icon Chevron up icon
5. Chapter 3: Turning the Source File into an Abstract Syntax Tree Chevron down icon Chevron up icon
6. Chapter 4: Basics of IR Code Generation Chevron down icon Chevron up icon
7. Chapter 5: IR Generation for High-Level Language Constructs Chevron down icon Chevron up icon
8. Chapter 6: Advanced IR Generation Chevron down icon Chevron up icon
9. Chapter 7: Optimizing IR Chevron down icon Chevron up icon
10. Part 3: Taking LLVM to the Next Level Chevron down icon Chevron up icon
11. Chapter 8: The TableGen Language Chevron down icon Chevron up icon
12. Chapter 9: JIT Compilation Chevron down icon Chevron up icon
13. Chapter 10: Debugging Using LLVM Tools Chevron down icon Chevron up icon
14. Part 4: Roll Your Own Backend Chevron down icon Chevron up icon
15. Chapter 11: The Target Description Chevron down icon Chevron up icon
16. Chapter 12: Instruction Selection Chevron down icon Chevron up icon
17. Chapter 13: Beyond Instruction Selection Chevron down icon Chevron up icon
18. Index Chevron down icon Chevron up icon
19. Other Books You May Enjoy Chevron down icon Chevron up icon

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