三点中央値型クイックソートで配列を並び替える
三点中央値型クイックソートを使用する
三点中央値型クイックソート (quick sort with median-of-three pivot) は、部分配列の左端・中央・右端の 3 要素から中央値となるものをピボットに選び、分割の偏りを抑える。
ロムート分割型クイックソートが右端固定だと昇順・降順に近い入力で最悪計算量 \(O(n^2)\) になりやすいのに対し、三点中央値は整列済みやほぼ整列済みでも端の極端な値を避けやすい。分割そのものはロムート方式を使い、違いは「どの位置をピボットにするか」にある。
ランダムピボット型クイックソートが乱択で期待値を上げるのに対し、こちらは決定的な 3 点比較で同じ目的に近づける。
- 三点中央値: 部分配列
lo … hiのA[lo]・A[mid]・A[hi](\(mid = lo + \lfloor (hi - lo) / 2 \rfloor\))を比べ、値の中央値にあたる添字を選ぶ。 - ロムート分割: 選んだ要素を右端へ移し、片方向走査で「未満」と「以上」に分ける。返り値
pがピボットの最終位置になる。 - 再帰:
lo … p - 1とp + 1 … hiに同じ処理を繰り返す。十分短い区間は挿入ソートで仕上げる。
procedure median_of_three_quick_sort(A, lo, hi)
if lo >= hi then
return
if hi - lo < INSERTION_THRESHOLD then
insertion_sort(A, lo, hi)
return
m = median_of_three_index(A, lo, hi)
swap(A[m], A[hi])
p = lomuto_partition(A, lo, hi)
median_of_three_quick_sort(A, lo, p - 1)
median_of_three_quick_sort(A, p + 1, hi)
procedure median_of_three_index(A, lo, hi)
mid = lo + floor((hi - lo) / 2)
// A[lo], A[mid], A[hi] のうち値の中央値の添字を返す
...
procedure lomuto_partition(A, lo, hi)
pivot = A[hi]
i = lo
for j from lo to hi - 1
if A[j] < pivot then
swap(A[i], A[j])
i = i + 1
swap(A[i], A[hi])
return i
整列済み配列では中央が中央値になりやすく、右端固定より分割がバランスしやすい。それでも巧妙に構成した入力では最悪計算量は \(O(n^2)\) のままである。不安定である。
平均計算量は \(O(n \log n)\)、追加空間は再帰スタックの \(O(\log n)\) 程度を見込む。
類似アルゴリズムとの相違点
ロムート分割型クイックソートは分割手順が同じだが、ピボットを右端固定にする。本アルゴリズムはその右端へ移す前に三点中央値を選ぶ点が違う。
ランダムピボット型クイックソートは一様乱択で期待計算量を上げる。三点中央値は乱数を使わず、左端・中央・右端の比較だけで偏りを抑える。
ホーア分割型クイックソートは両端ポインタの分割で、返り値の意味と再帰区間の切り方が異なる。三点中央値はホーア分割とも組み合わせられるが、ここではロムート分割との組み合わせを示す。
三分割クイックソートは等値帯をその場で確定する。デュアルピボットクイックソートはピボットを 2 つ使い 3 区間に分ける。いずれもピボット選びの三点中央値とは直交する改良である。
時間計算量および空間計算量を計測する
| Size | Average time (s) | Maximum time (s) | Average memory (KiB) | Maximum memory (KiB) |
|---|---|---|---|---|
| 256 | 0.000008 | 0.000067 | 0 | 0 |
| 512 | 0.000019 | 0.000232 | 0 | 0 |
| 1024 | 0.000040 | 0.000176 | 0 | 0 |
| 2048 | 0.000090 | 0.000275 | 0 | 0 |
| 4096 | 0.000195 | 0.000316 | 0 | 0 |
| 8192 | 0.000442 | 0.000799 | 0 | 0 |
| 16384 | 0.000832 | 0.002541 | 0 | 0 |
| 32768 | 0.001608 | 0.002523 | 0 | 0 |
| 65536 | 0.003648 | 0.005984 | 0 | 0 |
| 131072 | 0.007168 | 0.043297 | 0 | 0 |
| 262144 | 0.014754 | 0.024926 | 0 | 0 |
計測に使用したコードを表示する
#!/usr/bin/env swift
import Foundation
// This standalone Swift driver creates the same temporary Docker build
// context as the former shell wrapper. The benchmark program itself remains
// embedded below so readers can copy one complete, reproducible file.
struct BenchmarkError: Error, CustomStringConvertible {
let message: String
var description: String { message }
init(_ message: String) {
self.message = message
}
}
func runCommand(_ executable: String, _ arguments: [String]) throws {
let process = Process()
process.executableURL = URL(fileURLWithPath: "/usr/bin/env")
process.arguments = [executable] + arguments
process.standardInput = FileHandle.standardInput
process.standardOutput = FileHandle.standardOutput
process.standardError = FileHandle.standardError
do {
try process.run()
} catch {
throw BenchmarkError("Could not start \(executable): \(error)")
}
process.waitUntilExit()
guard process.terminationStatus == 0 else {
throw BenchmarkError(
"Command failed (\(process.terminationStatus)): " +
"\(executable) \(arguments.joined(separator: " "))"
)
}
}
do {
// The UUID avoids collisions when two benchmark copies are run at once.
let workdir = FileManager.default.temporaryDirectory
.appendingPathComponent("swift-sort-benchmark-\(UUID().uuidString)")
try FileManager.default.createDirectory(at: workdir, withIntermediateDirectories: true)
defer { try? FileManager.default.removeItem(at: workdir) }
// A raw Swift string is used so the nested main.swift keeps its own
// interpolation expressions such as \(seed) until Docker compiles it.
let dockerfile = #"""
FROM swift:6.0
WORKDIR /app
RUN cat > alloc_track.c <<'ALLOC'
#define _GNU_SOURCE
#include <dlfcn.h>
#include <malloc.h>
#include <stdatomic.h>
#include <stddef.h>
#include <stdint.h>
#include <stdlib.h>
#include <string.h>
static atomic_size_t live_bytes = 0;
static atomic_size_t peak_bytes = 0;
static void *(*real_malloc)(size_t) = NULL;
static void *(*real_calloc)(size_t, size_t) = NULL;
static void *(*real_realloc)(void *, size_t) = NULL;
static void (*real_free)(void *) = NULL;
static void init_reals(void) {
if (real_malloc) {
return;
}
real_malloc = (void *(*)(size_t))dlsym(RTLD_NEXT, "malloc");
real_calloc = (void *(*)(size_t, size_t))dlsym(RTLD_NEXT, "calloc");
real_realloc = (void *(*)(void *, size_t))dlsym(RTLD_NEXT, "realloc");
real_free = (void (*)(void *))dlsym(RTLD_NEXT, "free");
}
static void record_alloc(size_t size) {
size_t live = atomic_fetch_add(&live_bytes, size) + size;
size_t peak = atomic_load(&peak_bytes);
while (live > peak) {
if (atomic_compare_exchange_weak(&peak_bytes, &peak, live)) {
break;
}
}
}
void alloc_track_reset_peak(void) {
atomic_store(&peak_bytes, atomic_load(&live_bytes));
}
size_t alloc_track_live(void) { return atomic_load(&live_bytes); }
size_t alloc_track_peak(void) { return atomic_load(&peak_bytes); }
void *malloc(size_t size) {
init_reals();
void *p = real_malloc(size);
if (p) {
record_alloc(malloc_usable_size(p));
}
return p;
}
void *calloc(size_t nmemb, size_t size) {
init_reals();
void *p = real_calloc(nmemb, size);
if (p) {
record_alloc(malloc_usable_size(p));
}
return p;
}
void *realloc(void *ptr, size_t size) {
init_reals();
size_t old_size = 0;
if (ptr) {
old_size = malloc_usable_size(ptr);
}
void *p = real_realloc(ptr, size);
if (p) {
atomic_fetch_sub(&live_bytes, old_size);
record_alloc(malloc_usable_size(p));
} else if (size == 0) {
atomic_fetch_sub(&live_bytes, old_size);
}
return p;
}
void free(void *ptr) {
init_reals();
if (ptr) {
atomic_fetch_sub(&live_bytes, malloc_usable_size(ptr));
real_free(ptr);
}
}
ALLOC
RUN cat > main.swift <<'SWIFT'
import Foundation
#if canImport(Glibc)
import Glibc
#elseif canImport(Darwin)
import Darwin
#endif
@_silgen_name("alloc_track_live") func alloc_track_live() -> Int
@_silgen_name("alloc_track_peak") func alloc_track_peak() -> Int
@_silgen_name("alloc_track_reset_peak") func alloc_track_reset_peak()
extension UnsafeMutableBufferPointer where Element == Int {
func swapAt(_ i: Int, _ j: Int) {
let t = self[i]; self[i] = self[j]; self[j] = t
}
}
let MIN_POWER: Int = 8
let MAX_POWER: Int = 18
let RUNS: Int = 8192
func insertion_sort(_ a: inout [Int]) {
a.withUnsafeMutableBufferPointer { insertion_sort($0) }
}
func insertion_sort(_ a: UnsafeMutableBufferPointer<Int>) {
if a.count < 2 {
return
}
for i in 1..<a.count {
var j = i
while j > 0 && a[j - 1] > a[j] {
a.swapAt(j - 1, j)
j -= 1
}
}
}
func partition_at(_ a: UnsafeMutableBufferPointer<Int>, _ lo: Int, _ hi: Int, _ pivot_idx: Int) -> Int {
a.swapAt(pivot_idx, hi)
let pivot = a[hi]
var i = lo
for j in lo..<hi {
if a[j] < pivot {
a.swapAt(i, j)
i += 1
}
}
a.swapAt(i, hi)
return i
}
fileprivate func quick_median_of_three_idx(_ a: UnsafeMutableBufferPointer<Int>, _ lo: Int, _ hi: Int) -> Int {
let mid = lo + (hi - lo) / 2
let x = a[lo]
let y = a[mid]
let z = a[hi]
if (x <= y && y <= z) || (z <= y && y <= x) {
return mid
} else if (y <= x && x <= z) || (z <= x && x <= y) {
return lo
} else {
return hi
}
}
fileprivate func quick_median_of_three_sort_range(_ a: UnsafeMutableBufferPointer<Int>, _ lo: Int, _ hi: Int) {
if hi <= lo {
return
}
if hi - lo < 16 {
insertion_sort(UnsafeMutableBufferPointer(rebasing: a[lo..<(hi + 1)]))
return
}
let pivot_idx = quick_median_of_three_idx(a, lo, hi)
let p = partition_at(a, lo, hi, pivot_idx)
if p > 0 {
quick_median_of_three_sort_range(a, lo, p - 1)
}
quick_median_of_three_sort_range(a, p + 1, hi)
}
func quick_median_of_three_sort(_ a: inout [Int]) {
a.withUnsafeMutableBufferPointer { quick_median_of_three_sort($0) }
}
func quick_median_of_three_sort(_ a: UnsafeMutableBufferPointer<Int>) {
if a.count > 0 {
let hi = a.count - 1
quick_median_of_three_sort_range(a, 0, hi)
}
}
func benchmark_sort(_ array: inout [Int]) {
quick_median_of_three_sort(&array)
}
func is_non_decreasing(_ a: [Int]) -> Bool {
guard a.count >= 2 else { return true }
for i in 1..<a.count {
if a[i - 1] > a[i] { return false }
}
return true
}
func same_multiset(_ a: [Int], _ b: [Int]) -> Bool {
if a.count != b.count {
return false
}
var left = a
var right = b
left.sort()
right.sort()
return left == right
}
func check_correctness_case(_ label: String, _ input: [Int]) {
var input = input
let original = input
benchmark_sort(&input)
if !is_non_decreasing(input) {
fatalError("correctness case \(label): output is not sorted")
}
if !same_multiset(input, original) {
fatalError("correctness case \(label): elements were lost or added")
}
}
// Skip cases larger than the algorithm's measured size cap (MAX_POWER). That
// cap exists because larger inputs are impractically slow; forcing them here
// would stall the published measurement script before any table rows print.
func check_correctness_case_within_limit(_ label: String, _ input: [Int]) {
if input.count > (1 << MAX_POWER) {
return
}
check_correctness_case(label, input)
}
func few_unique_values(_ size: Int, _ unique: Int, _ seed: UInt64) -> [Int] {
var state = seed
var result = [Int]()
result.reserveCapacity(size)
for _ in 0..<size {
state ^= state << 13
state ^= state >> 7
state ^= state << 17
result.append(Int(state % UInt64(unique)) + 1)
}
return result
}
func run_correctness_checks() {
check_correctness_case("empty", [])
check_correctness_case("single", [42])
check_correctness_case("duplicates", [3, 1, 3, 2, 1, 2])
check_correctness_case("sorted", [1, 2, 3, 4, 5])
check_correctness_case("reverse", [5, 4, 3, 2, 1])
check_correctness_case("all_equal", [7, 7, 7, 7])
check_correctness_case("skewed_range", [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",
[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(
"few_keys_len32_seed_\(seed)",
few_unique_values(32, 4, UInt64(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", [Int](repeating: 7, count: 256))
for seed in 1...4 {
check_correctness_case(
"few_keys_len256_seed_\(seed)",
few_unique_values(256, 4, UInt64(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.
// Respect MAX_POWER so algorithms with a low measured-size cap (slow,
// sleep) do not hang here for minutes or months.
check_correctness_case_within_limit("all_equal_len600", [Int](repeating: 7, count: 600))
for seed in 1...4 {
check_correctness_case_within_limit(
"few_keys_len2048_seed_\(seed)",
few_unique_values(2048, 4, UInt64(seed))
)
}
}
func shuffled(_ size: Int, seed: UInt64) -> [Int] {
guard size > 0 else { return [] }
var v = Array(1...size)
var state = seed
if size > 1 {
for i in stride(from: size - 1, through: 1, by: -1) {
state ^= state << 13
state ^= state >> 7
state ^= state << 17
let j = Int(state % UInt64(i + 1))
v.swapAt(i, j)
}
}
return v
}
func micros(_ d: Duration) -> UInt64 {
let c = d.components
let fromSeconds = UInt64(c.seconds) * 1_000_000
let fromAttos = UInt64(max(0, c.attoseconds / 1_000_000_000_000))
return fromSeconds + fromAttos
}
func padLeft(_ value: String, _ width: Int) -> String {
if value.count >= width {
return value
}
return String(repeating: " ", count: width - value.count) + value
}
func formatSeconds(_ micros: UInt64) -> String {
let whole = micros / 1_000_000
let frac = micros % 1_000_000
let fracStr = padLeft(String(frac), 6).replacingOccurrences(of: " ", with: "0")
return "\(whole).\(fracStr)"
}
func input_array(_ size: Int, seed: UInt64) -> [Int] {
shuffled(size, seed: 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.
func run_once(size: Int, seed: Int) -> (UInt64, Int) {
var array = input_array(size, seed: UInt64(seed))
let baseBytes = alloc_track_live()
alloc_track_reset_peak()
let start = ContinuousClock.now
benchmark_sort(&array)
let elapsed = ContinuousClock.now - start
let peakBytes = alloc_track_peak()
let auxBytes = max(0, peakBytes - baseBytes)
let expected: [Int] = size > 0 ? Array(1...size) : []
if array != expected {
fatalError("sort failed with seed \(seed) for size \(size)")
}
return (micros(elapsed), auxBytes)
}
func run_child(_ args: [String]) {
let size = Int(args[2])!
let seed = Int(args[3])!
let (elapsedUs, mem) = run_once(size: size, seed: seed)
print("\(elapsedUs) \(mem)")
}
let args = CommandLine.arguments
if args.count > 1 && args[1] == "--run-once" {
run_child(args)
} else {
run_correctness_checks()
let tableHeader =
"| \(padLeft("Size", 10)) | " +
"\(padLeft("Average time (s)", 16)) | " +
"\(padLeft("Maximum time (s)", 16)) | " +
"\(padLeft("Average memory (KiB)", 20)) | " +
"\(padLeft("Maximum memory (KiB)", 20)) |"
print(tableHeader)
print("|-----------:|-----------------:|-----------------:|---------------------:|---------------------:|")
for power in MIN_POWER...MAX_POWER {
let size = 1 << power
var totalTime: UInt64 = 0
var maxTime: UInt64 = 0
var totalMem = 0
var maxMem = 0
for seed in 1...RUNS {
let process = Process()
process.executableURL = URL(fileURLWithPath: args[0])
process.arguments = ["--run-once", "\(size)", "\(seed)"]
let stdout = Pipe()
let stderr = Pipe()
process.standardOutput = stdout
process.standardError = stderr
do {
try process.run()
} catch {
fatalError("failed to run benchmark child process: \(error)")
}
process.waitUntilExit()
if process.terminationStatus != 0 {
let err = String(data: stderr.fileHandleForReading.readDataToEndOfFile(), encoding: .utf8) ?? ""
fatalError("benchmark child process failed: \(err)")
}
let data = stdout.fileHandleForReading.readDataToEndOfFile()
let stdoutText = String(data: data, encoding: .utf8) ?? ""
let fields = stdoutText.split(whereSeparator: \.isWhitespace)
guard fields.count >= 2,
let elapsedUs = UInt64(fields[0]),
let auxMem = Int(fields[1]) else {
fatalError("invalid child process output: \(stdoutText)")
}
totalTime += elapsedUs
if elapsedUs > maxTime {
maxTime = elapsedUs
}
totalMem += auxMem
if auxMem > maxMem {
maxMem = auxMem
}
}
let avgTime = totalTime / UInt64(RUNS)
// Memory is summed in bytes and converted to KiB once, after averaging.
let avgMemKb = totalMem / RUNS / 1024
let maxMemKb = maxMem / 1024
let tableRow =
"| \(padLeft(String(size), 10)) | " +
"\(padLeft(formatSeconds(avgTime), 16)) | " +
"\(padLeft(formatSeconds(maxTime), 16)) | " +
"\(padLeft(String(avgMemKb), 20)) | " +
"\(padLeft(String(maxMemKb), 20)) |"
print(tableRow)
}
}
SWIFT
RUN clang -O2 -fPIC -shared alloc_track.c -o liballoc_track.so -ldl
RUN swiftc -Ounchecked -whole-module-optimization \
main.swift \
-o swift-benchmark \
-L. -lalloc_track \
-Xlinker -rpath -Xlinker /app
ENV LD_PRELOAD=/app/liballoc_track.so
CMD ["./swift-benchmark"]
"""#
try dockerfile.write(
to: workdir.appendingPathComponent("Dockerfile"),
atomically: true,
encoding: .utf8
)
// Keeping build and run as separate child processes preserves Docker's
// normal output and the original image tag used by the benchmark skill.
try runCommand("docker", ["build", "-t", "swift-benchmark", workdir.path])
try runCommand("docker", ["run", "--rm", "--init", "swift-benchmark"])
} catch {
fputs("\(error)\n", stderr)
exit(1)
}