Expand description
Fast Floating-Point Math
fast_fp
provides a set of primitive types that support fast-math compiler
optimizations for many operations. These optimizations allow the compiler to
potentially generate faster code by relaxing some of the requirements of IEEE
754 floating-point arithmetic.
Examples
use fast_fp::{FF32, ff32};
// Construct instances of the fast type from std's type using the convenience
// wrapper `ff32` (or `ff64`)
let four = ff32(4.0);
// or using the `From`/`Into` trait
let five: FF32 = 5.0.into();
assert_eq!(four + five, ff32(9.0));
// Most ops are also implemented to work with std's floats too (including PartialEq).
// This makes working with literals easier.
assert_eq!(five + 6.0, 11.0);
assert_eq!(five * 2.0, 10.0);
// Functions can be made generic to accept std or fast types using `num-traits`
use num_traits::real::Real;
fn square<T: Real>(num: T) -> T {
num * num
}
assert_eq!(square(3.0_f32), 9.0);
assert_eq!(square(five), 25.0);
// If the nalgebra feature (with version suffix) is enabled, interop with
// nalgebra is supported
use nalgebra_v029 as na;
assert_eq!(na::Matrix3::repeat(four).sum(), 36.0);
Caveats
Precision
The fast-math optimizations may result in different outputs than operations
on the standard float primitives like f32
, particularly where fine-grained
precision is important. Fast-math may allow reordering operations in such a
way that some precision is lost in the overall computation. Note that there are
also cases where fast-math optimizations can improve precision, such as
contracting separate multiplication and addition into a fused multiply-add
operation.
Performance
Use of this crate’s primitives may not be faster than the standard primitives in all cases. That may be because the generated code is slower in practice, or because of certain measures taken by this crate to prevent Undefined Behavior (in particular for comparison heavy code). Users should carefully measure and benchmark their code to understand whether they actually benefit from use of these types.
Finite Math
Many operations have the finite-math-only
optimization flag enabled. With
this flag, the user must ensure that operations on the fast types do not
involve infinite or NaN values. If the arguments to an operation are, or the
results of an operation would be, +inf
, -inf
, or NaN
, then the
operation’s result value is unspecified. This crate goes to lengths to ensure
that such an operation is not UB in the strict sense, but the output is free to
be any representable value of the output type, and may not be a fixed value at
all.
Building
fast_fp
enables fast-math optimizations by calling C code which was compiled
with these optimizations enabled; additionally, some LLVM IR is used to prevent
triggering UB that is otherwise possible with these optimizations. As a
consequence, building this crate requires clang
to be installed and
requires the final binary to be linked using cross-language LTO to achieve the
performance benefits.
This LTO requires a version of clang compatible with the LLVM version used by rustc. To find the necessary LLVM version, check rustc’s version info in verbose mode:
$ rustc -vV
rustc 1.56.0 (09c42c458 2021-10-18)
binary: rustc
commit-hash: 09c42c45858d5f3aedfa670698275303a3d19afa
commit-date: 2021-10-18
host: x86_64-unknown-linux-gnu
release: 1.56.0
LLVM version: 13.0.0 # <--- see the version here
Then build and link using a clang
and lld
with the corresponding version:
$ CC="clang-13" \
RUSTFLAGS="-Clinker-plugin-lto -Clinker=clang-13 -Clink-arg=-fuse-ld=lld-13" \
cargo build
For simplicity, these arguments can be stored in a cargo config file
[env]
CC = "clang-13"
[build]
rustflags = ["-Clinker-plugin-lto", "-Clinker=clang-13", "-Clink-arg=-fuse-ld=lld-13"]
Although rustc does not always use an official LLVM release version, it’s typically close enough to be interoperable with the official clang and LLVM releases of the same version number.
Structs
A wrapper over f32
which enables some fast-math optimizations.
A wrapper over f64
which enables some fast-math optimizations.