Crate microbench

A micro-benchmarking library.

microbench uses linear regression to estimate the execution time of code segments. For example, the following table might represent data collected by microbench about a code segment.

Iterations	Time (ns)
1	19
2	25
3	37
4	47
5	56

microbench of course takes many more than 5 samples and the number of iterations grows geometrically rather than linearly, but the concept remains the same. After collecting data like this, microbench uses ordinary least squares (OLS) linear regression to estimate the actual execution time of the code segment. Using OLS with the above data would yield an estimated execution time of 9.6 nanoseconds with a goodness of fit (R²) of 0.992.

Example

use std::time::{Duration};
use microbench::{self, Options};

fn fibonacci_iterative(n: u64) -> u64 {
    let (mut x, mut y, mut z) = (0, 1, 1);
    for _ in 0..n { x = y; y = z; z = x + y; }
    x
}

fn fibonacci_recursive(n: u64) -> u64 {
    if n < 2 {
        n
    } else {
        fibonacci_recursive(n - 2) + fibonacci_recursive(n - 1)
    }
}

let options = Options::default().maximum(Duration::new(1, 0));
microbench::bench(&options, "iterative_16", || fibonacci_iterative(16));
microbench::bench(&options, "recursive_16", || fibonacci_recursive(16));

Example output:

iterative_16 ... bench:                  273.757 ns/iter (0.999 R²)
recursive_16 ... bench:                9_218.530 ns/iter (0.999 R²)

Structs

Analysis	An analysis of a set of timing data.
GeometricSequence	Generates unique values from a geometric sequence.
Measurement	A measurement of the execution time of a function.
Options	Benchmarking options.
Stopwatch	A high-precision stopwatch.

Functions

analyze	Analyzes the supplied timing data and returns the resulting analysis.
bench	Benchmarks the supplied function and prints the results.
measure	Measures the execution time of the supplied function and returns the resulting timing data.
retain	A function that prevents the optimizer from eliminating the supplied value.