# AoC 2023 Day 6: Racinator

## Source: Day 6: Wait For It

Full solution for today (spoilers!)

## Part 1

Simulate charging up race boats with the behavior that waiting X seconds to start means you move at X units per second. Given time allowed and a target distance, determine how many (integer) numbers of seconds will beat the target distance.

### Types and Parsing

Okay, there’s minimal input, so this should be quick. The main gotcha is that you get all of the times before all of the distances and then have to zip them.

#[derive(Debug)]
pub struct Race {
pub time: u64,
pub record: u64,
}

pub fn races(s: &str) -> IResult<&str, Vec<Race>> {
let (s, times) = delimited(
tuple((tag("Time:"), space1)),
separated_list1(space1, complete::u64),
newline,
)(s)?;
let (s, records) = preceded(
tuple((tag("Distance:"), space1)),
separated_list1(space1, complete::u64),
)(s)?;

Ok((
s,
times
.into_iter()
.zip(records)
.map(|(time, record)| Race { time, record })
.collect::<Vec<_>>(),
))
}

### Initial Brute Force Solution

So the obvious answer here would be to just directly try all possible values for X seconds from 0 up to time:

impl Race {
pub fn record_breakers_bf(&self) -> u64 {
(0..=self.time)
.filter(|x| x * (self.time - x) > self.record)
.count() as u64
}
}

fn main() -> Result<()> {
let stdin = io::stdin();
let (s, races) = parse::races(&input).unwrap();
assert_eq!(s.trim(), "");

let result = races
.iter()
.map(|r| r.record_breakers_bf())
.product::<u64>();

println!("{result}");
Ok(())
}

I like how compact that code is.

Running it:

$hyperfine 'just run 6 1-brute' Benchmark 1: just run 6 1-brute Time (mean ± σ): 152.3 ms ± 74.5 ms [User: 35.5 ms, System: 16.8 ms] Range (min … max): 82.6 ms … 277.9 ms 11 runs That’s fine for now. ## Part 2 Instead of treating the input as individual values, concatenate each line of input into a single (much larger) value. So instead of times of 7 15 30, you have one of 71530. Well, here’s where we might need to do a bit of optimization. Let’s find out! fn main() -> Result<()> { let stdin = io::stdin(); let input = io::read_to_string(stdin.lock())?; let (s, races) = parse::races(&input).unwrap(); assert_eq!(s.trim(), ""); let race = Race { time: races .iter() .map(|r| r.time.to_string()) .collect::<String>() .parse::<u64>()?, record: races .iter() .map(|r| r.record.to_string()) .collect::<String>() .parse::<u64>()?, }; let result = race.record_breakers_bf(); println!("{result}"); Ok(()) } .collect::<String> is neat. 😄 How does it run?$ just time 6 2-brute

hyperfine 'just run 6 2-brute'
Benchmark 1: just run 6 2-brute
Time (mean ± σ):     148.4 ms ±  50.6 ms    [User: 51.4 ms, System: 14.2 ms]
Range (min … max):    99.1 ms … 267.3 ms    11 runs

Actually… it’s completely fine. I didn’t expect that, but I suppose it’s still only ~50 million values.

## (Premature) Optimization

Okay, time to be honest. I didn’t actually write the brute force solution first. I didn’t expect it to work nearly as well as it did. Instead, I went all quadratic equation on things!

• The race is D units long
• Each option is hold the button for x seconds, maximum of T
• Distance traveled is x for T-x seconds
• We need to travel at least D
x(T-x) > D \\ xT - x^2 > D \\ x^2 - xT + D < 0 \\ x \between \frac{T \pm \sqrt{T^2 - 4D}}{2} \\

In code:

impl Race {
pub fn record_breakers(&self) -> u64 {
// Race is D units long
// Each option is hold the button for x seconds, maximum of T
// Distance traveled is x for T-x seconds
// We need to travel at least D
// x(T-x) > D
// xT - x^2 > D
// x^2 - xT + D < 0
// x in (T +/- sqrt(T^2 - 4D)) / 2

let t = self.time as f64;
let d = self.record as f64;

let x1 = (t - (t * t - 4.0 * d).sqrt()) / 2.0;
let x2 = (t + (t * t - 4.0 * d).sqrt()) / 2.0;

let lo = x1.min(x2).ceil() as u64;
let hi = x1.max(x2).floor() as u64;

// If lo is an integer, we don't want it (< vs <=)
// But it's a float, so check by epsilon difference
// This isn't perfect, but it works
let diff = ((lo as f64) - x1.min(x2)).abs();

if diff < 1e-6 {
hi - lo - 1
} else {
hi - lo + 1
}
}
}

Then for each solution we can just use record_breakers instead of record_breakers_bf. But… does it actually help? (There’s not really much room for optimization).

$hyperfine --warmup 3 'just run 6 1' 'just run 6 1-brute' Benchmark 1: just run 6 1 Time (mean ± σ): 102.9 ms ± 32.6 ms [User: 31.4 ms, System: 13.4 ms] Range (min … max): 77.1 ms … 196.9 ms 31 runs Benchmark 2: just run 6 1-brute Time (mean ± σ): 115.8 ms ± 32.0 ms [User: 32.6 ms, System: 13.8 ms] Range (min … max): 83.2 ms … 200.9 ms 31 runs Summary just run 6 1 ran 1.13 ± 0.47 times faster than just run 6 1-brute$ hyperfine --warmup 3 'just run 6 2' 'just run 6 2-brute'

Benchmark 1: just run 6 2
Time (mean ± σ):     103.3 ms ±  29.4 ms    [User: 31.8 ms, System: 12.5 ms]
Range (min … max):    81.4 ms … 167.5 ms    33 runs

Benchmark 2: just run 6 2-brute
Time (mean ± σ):     120.7 ms ±  27.1 ms    [User: 47.8 ms, System: 12.4 ms]
Range (min … max):    99.3 ms … 188.4 ms    25 runs

Summary
just run 6 2 ran
1.17 ± 0.42 times faster than just run 6 2-brute

10% faster (for the mathy version). That’s not nothing… but it’s pretty close at this scale. I expect a lot of speedup in the direct version is lost by doing sqrt and division.

If we scaled way up, perhaps this would matter? It would have to be pretty big though!

Anyways, it was an interesting. Onward!