Book Image

LLVM Essentials

By : Mayur Pandey, Suyog Sarda, David Farago
Book Image

LLVM Essentials

By: Mayur Pandey, Suyog Sarda, David Farago

Overview of this book

LLVM is currently the point of interest for many firms, and has a very active open source community. It provides us with a compiler infrastructure that can be used to write a compiler for a language. It provides us with a set of reusable libraries that can be used to optimize code, and a target-independent code generator to generate code for different backends. It also provides us with a lot of other utility tools that can be easily integrated into compiler projects. This book details how you can use the LLVM compiler infrastructure libraries effectively, and will enable you to design your own custom compiler with LLVM in a snap. We start with the basics, where you’ll get to know all about LLVM. We then cover how you can use LLVM library calls to emit intermediate representation (IR) of simple and complex high-level language paradigms. Moving on, we show you how to implement optimizations at different levels, write an optimization pass, generate code that is independent of a target, and then map the code generated to a backend. The book also walks you through CLANG, IR to IR transformations, advanced IR block transformations, and target machines. By the end of this book, you’ll be able to easily utilize the LLVM libraries in your own projects.
Table of Contents (14 chapters)
LLVM Essentials
About the Authors
About the Reviewer

Chapter 5. Advanced IR Block Transformations

In the previous chapter, we have gone through some of the optimizations, which were mainly at instruction level. In this chapter, we will look at optimizations on block level where we will be optimizing a block of code to a simpler form, which makes the code more effective. We will start by looking at how loops are represented in LLVM, use the concept of dominance and CFG to optimize loops. We will use Loop Simplification (LoopSimplify)and Loop Invariant Code Motion optimizations for loop processing. We will then see how a scalar value changes during program execution and how the result of this Scalar Evolution Optimization can be used in other optimizations. Then we will look into how LLVM represents its in build functions called as LLVM intrinsics. Finally, we will look into how LLVM deals with concepts of parallelism by understanding its approach towards vectorization.

In this chapter, we will look into the following topics:

  • Loop processing...