advent-of-code VS aoc2021

I just did simple BFS on the lava cubes for part 1. For part 2, I just did a BFS on the bounding cube. Total runtime - 500 micro seconds for both parts on my 8 years old laptop: https://github.com/SvetlinZarev/advent-of-code/blob/main/2022/aoc-day-18/src/lib.rs

My solution is pretty simple - top down DP. On each step we can do only one of two things: * open a valve and stay in current position * do not open a vale, but move to a different positions

🦀🦀🦀 RUST 🦀🦀🦀

You can see it in action here: https://github.com/SvetlinZarev/advent-of-code/blob/main/2022/aoc-day-04/src/lib.rs

Rust

Here are the results of my benchmarks, which you can also run

You can calculate the distances between the points found by each scanner. If two scanners report points with the same distance between them, then most probably they are adjacent. Runs in 4ms on my machine: https://github.com/SvetlinZarev/advent-of-code/tree/main/2021/aoc-day-19

You can copy the release profile from here https://github.com/SvetlinZarev/advent-of-code/blob/main/2021/aoc-day-25/Cargo.toml#L8 and copy that directory to enable compilation for the machine's cpu https://github.com/SvetlinZarev/advent-of-code/tree/main/2021/aoc-day-25/.cargo

I want to share my repo for whoever is interested. It contains Rust solutions for:

Mine (rust)runs for 50ms for both parts. I've used just a regular bruteforce approach, so nothing fancy. There are several things I did that reduced the execution time:

I've done every year in Haskell (2015 2016 2017 2018 2019 2020 2021), and so have several other people such as /u/glguy. I don't see if /u/mstksg has anything published for 2015 but they've done 2016 2017 2018 2019 2020 2021 along with some pretty good writeups, I recommend checking those out.

I ran my own benchmarks for a whole ton of code at https://github.com/ephemient/aoc2021 on both Linux x64 and macos x64, and ended up disabling Kotlin/Native because it was varying between 10x and 100x slower than Kotlin/JVM, eventually timing out on CI. The generated code may be reasonable thanks to LLVM, but the runtime certainly is not.

Took a while for me to get around to completing this in Kotlin, Python, and Rust as well, since I was working on optimizing other solutions, but I finally made it.

So I switched tacks and implemented this in Kotlin, where mutation is easier. First version was brute-force with duplicate state avoidance (checked before the state explosion at every input), which worked quickly enough for part 1, but ran into OOMs for part 2. Once I replaced the HashSet with a custom LruSet (and later a simpler CacheSet which simply overwrites on hash collisions) it ran part 2 in a few minutes. I then ported this into Haskell.

Haskell 1171/339

Kotlin, Python, and Rust solutions are the same solution but much uglier.

I'm doing the same cached recursion in Kotlin, Python, and Rust.

Haskell 621/603

Haskell 258/240

Haskell Kotlin 622/1185