スパゲッティソートで配列を並び替える
スパゲッティソートを使用する
スパゲッティソート (spaghetti sort) は、各正の数を未調理スパゲッティ棒の長さに見立てたアナログ寄りのソートである。棒を束ねて机へ立てると「いちばん長い棒が突き出る」物理現象を使い、長いものから順に取り出す。
- 棒の用意: 入力の各値に比例した長さのスパゲッティを 1 本ずつ切る(前処理は
O(n))。 - 整列(アナログ): 束を机へ垂直に立て、下端をそろえる。この揃えは手・棒・机が並列に働くとみなし、モデル上は定数時間とする。
- 最長の取り出し: 突き出た最長の棒を 1 本取り、降順の結果列へ追加する。残りがなくなるまで繰り返す(取り出しは
n回)。 - 昇順への変換: 取り出し順は降順なので、必要なら反転して昇順にする。
procedure spaghetti_sort(A)
sticks = copy of A
descending = empty list
while sticks is not empty
maxIdx = index of maximum in sticks
append sticks[maxIdx] to descending
remove sticks[maxIdx]
reverse descending into A
アナログモデルでは揃えが O(1)、用意と取り出しが合わせて O(n) とされる。一方、通常の逐次デジタル実装では最長探索が毎回線形なので全体は O(n²) になる。補助配列に棒をコピーするため空間は O(n) である。同長の棒をどちらから取るかで相対順が変わりうるため、一般に不安定である。
物理的な長さ比較の比喩としては分かりやすいが、切断精度や本数の上限があり、実務のデジタル整列には向かない。デジタルでは 選択ソート と同じく最大(または最小)を繰り返し選ぶ手続きに落ちる。
類似アルゴリズムとの相違点
選択ソートは未整列範囲から最小(または最大)を選んで確定位置と交換する。デジタル化したスパゲッティソートも最長の繰り返し選択に帰着するが、もともとの語りは物理的な長さ揃えを定数時間とみなす点で異なる。
ビーズソートやスリープソートも物理量(玉の段・待ち時間)に値を写す比喩だが、スパゲッティソートは棒の突出長そのものを順序の鍵にする。
パンケーキソートも最大を探して端へ運ぶが、使える操作が接頭辞の反転に限られる制約付き問題である。
計算時間量および空間計算量を計測する
デジタル実装は最長探索の繰り返しのため、平均・最悪とも O(n²) 相当の計測になる。
| Size | Average time | Maximum time | Average memory | Maximum memory |
|---|---|---|---|---|
| 256 | 0.000018 | 0.000081 | 4 | 4 |
| 512 | 0.000058 | 0.000175 | 8 | 8 |
| 1024 | 0.000207 | 0.000315 | 16 | 16 |
| 2048 | 0.000786 | 0.001482 | 32 | 32 |
| 4096 | 0.002978 | 0.006398 | 64 | 64 |
| 8192 | 0.011604 | 0.021015 | 128 | 128 |
| 16384 | 0.045712 | 0.104715 | 256 | 256 |
| 32768 | 0.233990 | 0.471986 | 512 | 512 |
計測に使用したコードを表示する
set -euo pipefail
WORKDIR="$(mktemp -d)"
trap 'rm -rf "$WORKDIR"' EXIT
cat > "$WORKDIR/Dockerfile" <<'EOF'
FROM rust:1.95.0
WORKDIR /app
RUN mkdir -p src
RUN cat > Cargo.toml <<'CARGO'
[package]
name = "rust-benchmark"
version = "0.1.0"
edition = "2021"
[profile.release]
lto = true
codegen-units = 1
panic = "abort"
CARGO
RUN cat > src/main.rs <<'RUST'
use std::{
alloc::{GlobalAlloc, Layout, System},
env,
process::Command,
sync::atomic::{AtomicUsize, Ordering as AtomicOrdering},
time::{Duration, Instant},
};
/// Counts live heap bytes and the high-water mark so auxiliary sort buffers
/// (swap Vecs, etc.) are measured as explicit heap growth during the sort.
struct TrackingAllocator;
static LIVE_BYTES: AtomicUsize = AtomicUsize::new(0);
static PEAK_BYTES: AtomicUsize = AtomicUsize::new(0);
fn record_alloc(size: usize) {
let live = LIVE_BYTES.fetch_add(size, AtomicOrdering::Relaxed) + size;
PEAK_BYTES.fetch_max(live, AtomicOrdering::Relaxed);
}
unsafe impl GlobalAlloc for TrackingAllocator {
unsafe fn alloc(&self, layout: Layout) -> *mut u8 {
let ptr = System.alloc(layout);
if !ptr.is_null() {
record_alloc(layout.size());
}
ptr
}
unsafe fn dealloc(&self, ptr: *mut u8, layout: Layout) {
LIVE_BYTES.fetch_sub(layout.size(), AtomicOrdering::Relaxed);
System.dealloc(ptr, layout);
}
unsafe fn alloc_zeroed(&self, layout: Layout) -> *mut u8 {
let ptr = System.alloc_zeroed(layout);
if !ptr.is_null() {
record_alloc(layout.size());
}
ptr
}
unsafe fn realloc(&self, ptr: *mut u8, layout: Layout, new_size: usize) -> *mut u8 {
let new_ptr = System.realloc(ptr, layout, new_size);
if !new_ptr.is_null() {
LIVE_BYTES.fetch_sub(layout.size(), AtomicOrdering::Relaxed);
record_alloc(new_size);
}
new_ptr
}
}
#[global_allocator]
static GLOBAL: TrackingAllocator = TrackingAllocator;
const MIN_POWER: u32 = 8;
const MAX_POWER: u32 = 15;
const RUNS: usize = 8192;
fn spaghetti_sort(a: &mut [usize]) {
let n = a.len();
if n < 2 {
return;
}
// Physical model: remove the longest remaining stick repeatedly (descending),
// then reverse for ascending order. Digital simulation uses O(n) scratch space.
let mut sticks: Vec<usize> = a.to_vec();
let mut descending: Vec<usize> = Vec::with_capacity(n);
while !sticks.is_empty() {
let mut max_idx = 0;
for i in 1..sticks.len() {
if sticks[i] > sticks[max_idx] {
max_idx = i;
}
}
descending.push(sticks.swap_remove(max_idx));
}
descending.reverse();
a.copy_from_slice(&descending);
}
fn benchmark_sort(array: &mut [usize]) {
spaghetti_sort(array);
}
fn is_non_decreasing(a: &[usize]) -> bool {
a.windows(2).all(|w| w[0] <= w[1])
}
fn same_multiset(a: &[usize], b: &[usize]) -> bool {
if a.len() != b.len() {
return false;
}
let mut left = a.to_vec();
let mut right = b.to_vec();
left.sort_unstable();
right.sort_unstable();
left == right
}
fn check_correctness_case(label: &str, mut input: Vec<usize>) {
let original = input.clone();
benchmark_sort(&mut input);
if !is_non_decreasing(&input) {
panic!("correctness case {}: output is not sorted", label);
}
if !same_multiset(&input, &original) {
panic!("correctness case {}: elements were lost or added", label);
}
}
fn few_unique_values(size: usize, unique: usize, seed: u64) -> Vec<usize> {
let mut state = seed;
(0..size)
.map(|_| {
state ^= state << 13;
state ^= state >> 7;
state ^= state << 17;
(state as usize % unique) + 1
})
.collect()
}
fn run_correctness_checks() {
check_correctness_case("empty", vec![]);
check_correctness_case("single", vec![42]);
check_correctness_case("duplicates", vec![3, 1, 3, 2, 1, 2]);
check_correctness_case("sorted", vec![1, 2, 3, 4, 5]);
check_correctness_case("reverse", vec![5, 4, 3, 2, 1]);
check_correctness_case("all_equal", vec![7, 7, 7, 7]);
check_correctness_case("skewed_range", vec![1_000_000, 2, 1_000_001, 1, 999_999]);
// Static-buffer Grail skips the in-buffer build when key collection is sparse
// (ideal_buffer = false). Exercising that path catches regressions in buffer gating.
check_correctness_case(
"few_keys_len16",
vec![2, 2, 2, 2, 2, 2, 2, 2, 4, 3, 1, 2, 3, 4, 1, 4],
);
// Seed 0 is a fixed point of the xorshift below, so it would degenerate into
// yet another all-equal case instead of a 4-value mix. Start at 1.
for seed in 1..=32 {
check_correctness_case(
&format!("few_keys_len32_seed_{seed}"),
few_unique_values(32, 4, seed),
);
}
// Small-input cutoffs (insertion sort below 32 elements, etc.) hide duplicate-key
// bugs in the recursive path, so repeat the duplicate cases at the smallest
// benchmark size, which every algorithm must handle within reasonable time.
check_correctness_case("all_equal_len256", vec![7; 256]);
for seed in 1..=4 {
check_correctness_case(
&format!("few_keys_len256_seed_{seed}"),
few_unique_values(256, 4, seed),
);
}
// Blit's equal-key second sweep used to copy the whole range into a fixed
// 512-element swap; lengths above that must still sort without panicking.
check_correctness_case("all_equal_len600", vec![7; 600]);
for seed in 1..=4 {
check_correctness_case(
&format!("few_keys_len2048_seed_{seed}"),
few_unique_values(2048, 4, seed),
);
}
}
fn shuffled(size: usize, seed: u64) -> Vec<usize> {
let mut v: Vec<usize> = (1..=size).collect();
let mut state = seed;
for i in (1..size).rev() {
state ^= state << 13;
state ^= state >> 7;
state ^= state << 17;
let j = (state as usize) % (i + 1);
v.swap(i, j);
}
v
}
fn micros(d: Duration) -> u128 {
d.as_micros()
}
fn input_array(size: usize, seed: u64) -> Vec<usize> {
shuffled(size, seed)
}
/// Peak heap growth during `benchmark_sort`, in bytes (explicit buffers such as swap).
/// Kept in bytes so the parent can average before rounding; converting to KiB here
/// would truncate sub-KiB buffers to 0 in every run and hide them from the average.
fn run_once(size: usize, seed: usize) -> (u128, usize) {
let mut array = input_array(size, seed as u64);
let base_bytes = LIVE_BYTES.load(AtomicOrdering::Relaxed);
PEAK_BYTES.store(base_bytes, AtomicOrdering::Relaxed);
let start = Instant::now();
benchmark_sort(&mut array);
let elapsed = start.elapsed();
let peak_bytes = PEAK_BYTES.load(AtomicOrdering::Relaxed);
let aux_bytes = peak_bytes.saturating_sub(base_bytes);
let expected: Vec<usize> = (1..=size).collect();
if array != expected {
panic!(
"sort failed with seed {} for size {}",
seed,
size
);
}
(micros(elapsed), aux_bytes)
}
fn run_child(args: &[String]) {
let size = args[2].parse::<usize>().expect("invalid size");
let seed = args[3].parse::<usize>().expect("invalid seed");
let (elapsed_us, mem) = run_once(size, seed);
println!("{} {}", elapsed_us, mem);
}
fn main() {
let args: Vec<String> = env::args().collect();
if args.get(1).is_some_and(|arg| arg == "--run-once") {
run_child(&args);
return;
}
run_correctness_checks();
println!(
"| {:>10} | {:>15} | {:>15} | {:>15} | {:>15} |",
"Size",
"Average time",
"Maximum time",
"Average memory",
"Maximum memory"
);
println!(
"|{:-<11}:|{:-<16}:|{:-<16}:|{:-<16}:|{:-<16}:|",
"",
"",
"",
"",
""
);
for power in MIN_POWER..=MAX_POWER {
let size = 1usize << power;
let mut total_time: u128 = 0;
let mut max_time: u128 = 0;
let mut total_mem: usize = 0;
let mut max_mem: usize = 0;
for seed in 1..=RUNS {
let output = Command::new(env::current_exe().expect("failed to find current executable"))
.arg("--run-once")
.arg(size.to_string())
.arg(seed.to_string())
.output()
.expect("failed to run benchmark child process");
if !output.status.success() {
panic!(
"benchmark child process failed: {}",
String::from_utf8_lossy(&output.stderr)
);
}
let stdout = String::from_utf8(output.stdout)
.expect("child process returned non-UTF-8 output");
let mut fields = stdout.split_whitespace();
let elapsed_us = fields
.next()
.expect("missing elapsed time")
.parse::<u128>()
.expect("invalid elapsed time");
let aux_mem = fields
.next()
.expect("missing memory usage")
.parse::<usize>()
.expect("invalid memory usage");
total_time += elapsed_us;
if elapsed_us > max_time {
max_time = elapsed_us;
}
total_mem += aux_mem;
if aux_mem > max_mem {
max_mem = aux_mem;
}
}
let avg_time = total_time / RUNS as u128;
// Memory is summed in bytes and converted to KiB once, after averaging.
let avg_mem_kb = total_mem / RUNS / 1024;
let max_mem_kb = max_mem / 1024;
println!(
"| {:>10} | {:>15} | {:>15} | {:>15} | {:>15} |",
size,
format!("{}.{:06}", avg_time / 1_000_000, avg_time % 1_000_000),
format!("{}.{:06}", max_time / 1_000_000, max_time % 1_000_000),
avg_mem_kb,
max_mem_kb
);
}
}
RUST
RUN cargo build --release
CMD ["./target/release/rust-benchmark"]
EOF
docker build -t rust-benchmark "$WORKDIR"
docker run --rm --init rust-benchmark