Tools: Monomorphization in Rust — How Generics Become Fast, Concrete Code

What is Monomorphization in Rust? Monomorphization is the process by which Rust converts generic code into a specific type or hard-coded version during compilation. Monomorphization is a key factor in Rust's exceptional performance. With monomorphization, Rust provides zero-cost abstractions, allowing you to write clean, high-level generic code without incurring any runtime performance penalties. The Trade-offs of Monomorphization
Nothing in systems programming comes for free. While monomorphization gives you maximum execution speed, you pay for it in two ways: Binary Bloat
If you use a generic function with 20 different types, the compiler generates 20 copies of that function. If you have complex generic structs (like Option or Result), the compiler will generate a unique layout for every type you wrap in them. This can lead to larger executable file sizes. Slower Compile Times
Generating, analyzing, and optimizing multiple copies of the same function takes CPU cycles. Heavy use of generics is one of the primary reasons large Rust projects can take a long time to compile. Summary
What it is: The compiler copying generic code and replacing T with concrete types (like i32 or String). The Benefit: Zero-cost abstractions. It enables static dispatch, inlining, and extreme runtime performance. The Cost: Increased binary size and slower compile times. The Rust Philosophy: Rust defaults to monomorphization because it prioritizes runtime performance and safety over compile speed and binary size. Templates let you quickly answer FAQs or store snippets for re-use. Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink. Hide child comments as well For further actions, you may consider blocking this person and/or reporting abuse CODE_BLOCK:
fn main() { let integer = Some(5); // Compiles to Option_i32 let float = Some(5.0); // Compiles to Option_f64
} Enter fullscreen mode Exit fullscreen mode CODE_BLOCK:
fn main() { let integer = Some(5); // Compiles to Option_i32 let float = Some(5.0); // Compiles to Option_f64
} CODE_BLOCK:
fn main() { let integer = Some(5); // Compiles to Option_i32 let float = Some(5.0); // Compiles to Option_f64
} COMMAND_BLOCK:
// Cargo.toml: edition = "2021" use std::ops::Add; fn add<T: Add<Output = T> + Copy>(a: T, b: T) -> T { a + b
} fn main() { let x = add(1i32, 2i32); let y = add(1.5f64, 2.5f64); println!("x = {}, y = {}", x, y);
} Enter fullscreen mode Exit fullscreen mode COMMAND_BLOCK:
// Cargo.toml: edition = "2021" use std::ops::Add; fn add<T: Add<Output = T> + Copy>(a: T, b: T) -> T { a + b
} fn main() { let x = add(1i32, 2i32); let y = add(1.5f64, 2.5f64); println!("x = {}, y = {}", x, y);
} COMMAND_BLOCK:
// Cargo.toml: edition = "2021" use std::ops::Add; fn add<T: Add<Output = T> + Copy>(a: T, b: T) -> T { a + b
} fn main() { let x = add(1i32, 2i32); let y = add(1.5f64, 2.5f64); println!("x = {}, y = {}", x, y);
} - Binary Bloat
If you use a generic function with 20 different types, the compiler generates 20 copies of that function. If you have complex generic structs (like Option or Result), the compiler will generate a unique layout for every type you wrap in them. This can lead to larger executable file sizes.
- Slower Compile Times
Generating, analyzing, and optimizing multiple copies of the same function takes CPU cycles. Heavy use of generics is one of the primary reasons large Rust projects can take a long time to compile.