Optimizing Rust Compilation: Techniques and Tips | RustMeUp.com

Optimizing Rust Compilation: Techniques and Tips

In the ever-evolving world of programming, Rust leads the pack with its emphasis on system-level performance, reliability, and security. While efficient coding in Rust is a crucial aspect, one often overlooked element is optimizing your Rust compilation. This guide will delve into the various techniques, tips, and tricks to enhance the efficiency of your Rust projects, and allow you to extract maximum performance from your codebase during compilation stages.

What is Rust Compilation?

Before delving into optimization techniques, it is essential to understand what Rust compilation is. The Rust compiler, rustc, takes your source code written in Rust language and turns it into an executable binary file that a computer can understand and execute.

Rust has a reputation for having slower compile times compared to other languages like C or C++. However, with meticulous adherence to some specific practices and careful tuning, you can drastically improve the compile-time and optimization level of your Rust programs.

Why Rust Compilation Optimization is Essential?

There are a few reasons why you might want to optimize your Rust compile times:

  1. It can drastically reduce your code's overall development time, as you spend less time waiting for your programs to compile.
  2. If you are working on a large scale Rust project or in a professional setup with multiple developers involved, improvements in compile times can lead to significant increases in productivity.
  3. Quicker compile times can facilitate more iterations and faster debugging, enhancing the overall development cycle.

With those reasons in mind, it's time to look at some techniques and tips that can significantly optimize your Rust compilation.

1. Incremental Compilation

Introduced in Rust 1.24, incremental compilation is a feature designed to improve compiler performance. When you make minor changes to your code, the compiler doesn't need to recompile everything from scratch—it only compiles the portion of the code that was modified, saving a lot of time. Note that it's not perfect and sometimes produces slower code, especially for larger projects. But it's enabled by default and generally beneficial.

2. Use the ThinLTO

Link Time Optimization (LTO) refers to program optimizations by a compiler that occur during linking. ThinLTO is an approach to LTO that scales better for large codebases. It uses less memory and performs faster than full LTO but generally achieves similar performance in the generated code. You can enable ThinLTO in your Cargo.toml file like so:

lto = "thin"

3. Codegen Units

Codegen Units parallelize (and thus speed up) code generation. They control how many threads are used when optimizing and translating code to machine code. By default, Rust sets this to 16 for debug mode and 1 for release mode. However, you can play around with this number to see if it improves your compilation time. Be aware that using more codegen units can lead to slower produced code.

4. Profile Guided Optimization (PGO)

PGO allows the compiler to better optimize code by collecting data from profile runs about which parts of your program are most commonly executed. This is accomplished by running the program with a specific workload and then collecting statistics about its behaviour. While it does take more time initially, the optimized code can sometimes perform significantly better.

Here's how you can enable PGO:

codegen-units = 1
lto = true
overflow-checks = false
panic = 'abort'
rpath = false
debug = false
opt-level = 3
debug-assertions = false
profiler = true

Run your program with a representative workload. This generates a .profdata file. Now recompile your program with the following environment variable set:

RUSTFLAGS=-Cprofile-use=path/to/your.profdata cargo build --release

5. Exploring Tools For Compilation

Certain tools help monitor and control your compilation processes:

  • cargo-bloat: Can tell you where the most costly parts of your binary are.
  • cargo-llvm-lines: Measures how many LLVM lines of code are generated for Rust source lines.
  • sccache: Just like ccache, but for Rust. It caches your libraries, which can tremendously speed up the compilation process.


Overall, improving your Rust compilation times isn't just a single step but a combination of meticulously applied practices and careful tuning. It does require a detailed understanding of the compiler and the language, but it can significantly speed up your development process and make Rust programming smoother and more enjoyable.

Frequently Asked Questions

Q1: Why is Rust compilation slow?

The Rust compiler does a lot of work to assure memory safety without garbage collection, zero-cost abstractions, and other such features. The trade-off is that this makes Rust compilation slower than some other languages.

Q2: Does optimizing Rust compilation affect the performance of code?

Mostly, optimization aims to improve compile times without negatively affecting the speed of the resulting binary. However, in some cases (like using more codegen units), speedup in compile time might slightly affect the speed of the produced binary.

Q3: How can I enable incremental compilation in Rust?

Incremental compilation is enabled by default since Rust version 1.24. If not, you can enable it by adding incremental = true to your profile in Cargo.toml.

Q4: Is Rust a compiled language or an interpreted language?

Rust is a statically typed, compiled language. It means the Rust programs must be converted into machine code before they can be run on a computer.

Q5: What is ThinLTO in Rust compilation?

ThinLTO is a way to perform Link Time Optimization (LTO) that uses less memory and performs faster than full LTO. It's generally beneficial for larger codebases.

Q6: How to measure Rust compilation time?

You can use the time command in Unix systems before your normal cargo build or cargo run commands. For example, time cargo build.

Q7: Can I use PGO for all Rust programs?

Profile Guided Optimization is beneficial for programs where runtime performance matters a lot. However, PGO can lead to larger binaries and longer compile times, so it should be used judiciously.