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LLVM Techniques, Tips, and Best Practices Clang and Middle-End Libraries

LLVM Techniques, Tips, and Best Practices Clang and Middle-End Libraries

By : Min-Yih Hsu
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LLVM Techniques, Tips, and Best Practices Clang and Middle-End Libraries

LLVM Techniques, Tips, and Best Practices Clang and Middle-End Libraries

5 (7)
By: Min-Yih Hsu

Overview of this book

Every programmer or engineer, at some point in their career, works with compilers to optimize their applications. Compilers convert a high-level programming language into low-level machine-executable code. LLVM provides the infrastructure, reusable libraries, and tools needed for developers to build their own compilers. With LLVM’s extensive set of tooling, you can effectively generate code for different backends as well as optimize them. In this book, you’ll explore the LLVM compiler infrastructure and understand how to use it to solve different problems. You’ll start by looking at the structure and design philosophy of important components of LLVM and gradually move on to using Clang libraries to build tools that help you analyze high-level source code. As you advance, the book will show you how to process LLVM IR – a powerful way to transform and optimize the source program for various purposes. Equipped with this knowledge, you’ll be able to leverage LLVM and Clang to create a wide range of useful programming language tools, including compilers, interpreters, IDEs, and source code analyzers. By the end of this LLVM book, you’ll have developed the skills to create powerful tools using the LLVM framework to overcome different real-world challenges.
Table of Contents (18 chapters)
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1
Section 1: Build System and LLVM-Specific Tooling
6
Section 2: Frontend Development
11
Section 3: "Middle-End" Development

Working with PGO

In the previous section, we learned how a sanitizer assists developers in performing sanity checks with higher precision using data that is only available at runtime. We also learned how to create a custom sanitizer. In this section, we will follow up on the idea of leveraging runtime data. We are going to learn an alternative use for such information – using it for compiler optimization.

PGO is a technique that uses statistics that have been collected during runtime to enable more aggressive compiler optimizations. The profile in its name refers to the runtime data that's been collected. To give you an idea of how such data enhances an optimization, let's assume we have the following C code:

void foo(int N) {
  if (N > 100)
    bar();
  else
    zoo();
}

In this code, we have three functions: foo, bar, and zoo. The first function conditionally calls the latter two.

When we...

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