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  • Book Overview & Buying LLVM Cookbook
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LLVM Cookbook

LLVM Cookbook

By : Mayur Pandey, Suyog Sarda
2 (9)
Buy this Book
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LLVM Cookbook

LLVM Cookbook

2 (9)
By: Mayur Pandey, Suyog Sarda
Buy this Book

Overview of this book

The book is for compiler programmers who are familiar with concepts of compilers and want to indulge in understanding, exploring, and using LLVM infrastructure in a meaningful way in their work. This book is also for programmers who are not directly involved in compiler projects but are often involved in development phases where they write thousands of lines of code. With knowledge of how compilers work, they will be able to code in an optimal way and improve performance with clean code.
Table of Contents (11 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Sections
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Conventions
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Reader feedback
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Customer support
Lock Free Chapter
1
1. LLVM Design and Use
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1. LLVM Design and Use
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Introduction
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Understanding modular design
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Cross-compiling Clang/LLVM
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Converting a C source code to LLVM assembly
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Converting IR to LLVM bitcode
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Converting LLVM bitcode to target machine assembly
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Converting LLVM bitcode back to LLVM assembly
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Transforming LLVM IR
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Linking LLVM bitcode
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Executing LLVM bitcode
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Using the C frontend Clang
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Using the GO frontend
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Using DragonEgg
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2. Steps in Writing a Frontend
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2. Steps in Writing a Frontend
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Introduction
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Defining a TOY language
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Implementing a lexer
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Defining Abstract Syntax Tree
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Implementing a parser
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Parsing simple expressions
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Parsing binary expressions
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Invoking a driver for parsing
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Running lexer and parser on our TOY language
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Defining IR code generation methods for each AST class
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Generating IR code for expressions
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Generating IR code for functions
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Adding IR optimization support
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3. Extending the Frontend and Adding JIT Support
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3. Extending the Frontend and Adding JIT Support
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Introduction
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Handling decision making paradigms – if/then/else constructs
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Generating code for loops
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Handling user-defined operators – binary operators
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Handling user-defined operators – unary operators
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Adding JIT support
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4. Preparing Optimizations
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4. Preparing Optimizations
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Introduction
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Various levels of optimization
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Writing your own LLVM pass
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Running your own pass with the opt tool
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Using another pass in a new pass
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Registering a pass with pass manager
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Writing an analysis pass
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Writing an alias analysis pass
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Using other analysis passes
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5. Implementing Optimizations
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5. Implementing Optimizations
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Introduction
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Writing a dead code elimination pass
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Writing an inlining transformation pass
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Writing a pass for memory optimization
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Combining LLVM IR
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Transforming and optimizing loops
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Reassociating expressions
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Vectorizing IR
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Other optimization passes
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6. Target-independent Code Generator
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6. Target-independent Code Generator
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Introduction
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The life of an LLVM IR instruction
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Visualizing LLVM IR CFG using GraphViz
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Describing targets using TableGen
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Defining an instruction set
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Adding a machine code descriptor
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Implementing the MachineInstrBuilder class
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Implementing the MachineBasicBlock class
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Implementing the MachineFunction class
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Writing an instruction selector
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Legalizing SelectionDAG
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Optimizing SelectionDAG
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Selecting instruction from the DAG
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Scheduling instructions in SelectionDAG
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7. Optimizing the Machine Code
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7. Optimizing the Machine Code
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Introduction
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Eliminating common subexpression from machine code
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Analyzing live intervals
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Allocating registers
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Inserting the prologue-epilogue code
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Code emission
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Tail call optimization
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Sibling call optimisation
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8. Writing an LLVM Backend
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8. Writing an LLVM Backend
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Introduction
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Defining registers and registers sets
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Defining the calling convention
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Defining the instruction set
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Implementing frame lowering
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Printing an instruction
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Selecting an instruction
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Adding instruction encoding
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Supporting a subtarget
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Lowering to multiple instructions
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Registering a target
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9. Using LLVM for Various Useful Projects
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9. Using LLVM for Various Useful Projects
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Introduction
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Exception handling in LLVM
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Using sanitizers
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Writing the garbage collector with LLVM
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Converting LLVM IR to JavaScript
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Using the Clang Static Analyzer
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Using bugpoint
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Using LLDB
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Using LLVM utility passes
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Index
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Index

Cross-compiling Clang/LLVM

By cross-compiling we mean building a binary on one platform (for example, x86) that will be run on another platform (for example, ARM). The machine on which we build the binary is called the host, and the machine on which the generated binary will run is called the target. The compiler that builds code for the same platform on which it is running (the host and target platforms are the same) is called a native assembler, whereas the compiler that builds code for a target platform different from the host platform is called a cross-compiler.

In this recipe, cross-compilation of LLVM for a platform different than the host platform will be shown, so that you can use the built binaries for the required target platform. Here, cross-compiling will be shown using an example where cross-compilation from host platform x86_64 for target platform ARM will be done. The binaries thus generated can be used on a platform with ARM architecture.

Getting ready

The following packages need to be installed on your system (host platform):

  • cmake
  • ninja-build (from backports in Ubuntu)
  • gcc-4.x-arm-linux-gnueabihf
  • gcc-4.x-multilib-arm-linux-gnueabihf
  • binutils-arm-linux-gnueabihf
  • libgcc1-armhf-cross
  • libsfgcc1-armhf-cross
  • libstdc++6-armhf-cross
  • libstdc++6-4.x-dev-armhf-cross
  • install llvm on your host platform

How to do it...

To compile for the ARM target from the host architecture, that is X86_64 here, you need to perform the following steps:

  1. Add the following cmake flags to the normal cmake build for LLVM:
    -DCMAKE_CROSSCOMPILING=True
-DCMAKE_INSTALL_PREFIX= path-where-you-want-the-toolchain(optional)
-DLLVM_TABLEGEN=<path-to-host-installed-llvm-toolchain-bin>/llvm-tblgen
-DCLANG_TABLEGEN=< path-to-host-installed-llvm-toolchain-bin >/clang-tblgen
-DLLVM_DEFAULT_TARGET_TRIPLE=arm-linux-gnueabihf
-DLLVM_TARGET_ARCH=ARM
-DLLVM_TARGETS_TO_BUILD=ARM
-DCMAKE_CXX_FLAGS='-target armv7a-linux-gnueabihf -mcpu=cortex-a9 -I/usr/arm-linux-gnueabihf/include/c++/4.x.x/arm-linux-gnueabihf/ -I/usr/arm-linux-gnueabihf/include/ -mfloat-abi=hard -ccc-gcc-name arm-linux-gnueabihf-gcc'
  2. If using your platform compiler, run:
    $ cmake -G Ninja <llvm-source-dir> <options above>

    If using Clang as the cross-compiler, run:

    $ CC='clang' CXX='clang++' cmake -G Ninja <source-dir> <options above>

    If you have clang/Clang++ on the path, it should work fine.

  3. To build LLVM, simply type:
    $ ninja
  4. After the LLVM/Clang has built successfully, install it with the following command:
    $ ninja install

This will create a sysroot on the install-dir location if you have specified the DCMAKE_INSTALL_PREFIX options

How it works...

The cmake package builds the toolchain for the required platform by making the use of option flags passed to cmake, and the tblgen tools are used to translate the target description files into C++ code. Thus, by using it, the information about targets is obtained, for example—what instructions are available on the target, the number of registers, and so on.

Note

If Clang is used as the cross-compiler, there is a problem in the LLVM ARM backend that produces absolute relocations on position-independent code (PIC), so as a workaround, disable PIC at the moment.

The ARM libraries will not be available on the host system. So, either download a copy of them or build them on your system.

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