Add benchmarks for k_smallest implementation variants.

Cargo.toml

@@ -27,7 +27,7 @@ either = { version = "1.0", default-features = false }
 
 [dev-dependencies]
 rand = "0.7"
-criterion = "0.4.0"
+criterion = { version = "0.4.0", features = ["html_reports"] }
 paste = "1.0.0"  # Used in test_std to instantiate generic tests
 permutohedron = "0.2"
 quickcheck = { version = "0.9", default_features = false }
@@ -75,3 +75,7 @@ harness = false
 [[bench]]
 name = "specializations"
 harness = false
+
+[[bench]]
+name = "k_smallest"
+harness = false

benches/k_smallest.rs

@@ -0,0 +1,61 @@
+use criterion::{black_box, criterion_group, criterion_main, Bencher, BenchmarkId, Criterion};
+use itertools::Itertools;
+use rand::{rngs::StdRng, seq::SliceRandom, SeedableRng};
+
+fn strict(b: &mut Bencher, (k, vals): &(usize, &Vec<usize>)) {
+    b.iter(|| black_box(vals.iter()).k_smallest(*k))
+}
+
+fn relaxed(b: &mut Bencher, (k, vals): &(usize, &Vec<usize>)) {
+    b.iter(|| black_box(vals.iter()).k_smallest_relaxed(*k))
+}
+
+fn ascending(n: usize) -> Vec<usize> {
+    (0..n).collect()
+}
+
+fn random(n: usize) -> Vec<usize> {
+    let mut vals = (0..n).collect_vec();
+    vals.shuffle(&mut StdRng::seed_from_u64(42));
+    vals
+}
+
+fn descending(n: usize) -> Vec<usize> {
+    (0..n).rev().collect()
+}
+
+fn k_smallest(c: &mut Criterion, order: &str, vals: fn(usize) -> Vec<usize>) {
+    let mut g = c.benchmark_group(format!("k-smallest/{order}"));
+
+    for log_n in 20..23 {
+        let n = 1 << log_n;
+
+        let vals = vals(n);
+
+        for log_k in 7..10 {
+            let k = 1 << log_k;
+
+            let params = format!("{log_n}/{log_k}");
+            let input = (k, &vals);
+            g.bench_with_input(BenchmarkId::new("strict", &params), &input, strict);
+            g.bench_with_input(BenchmarkId::new("relaxed", &params), &input, relaxed);
+        }
+    }
+
+    g.finish()
+}
+
+fn k_smallest_asc(c: &mut Criterion) {
+    k_smallest(c, "asc", ascending);
+}
+
+fn k_smallest_rand(c: &mut Criterion) {
+    k_smallest(c, "rand", random);
+}
+
+fn k_smallest_desc(c: &mut Criterion) {
+    k_smallest(c, "desc", descending);
+}
+
+criterion_group!(benches, k_smallest_asc, k_smallest_rand, k_smallest_desc);
+criterion_main!(benches);

src/k_smallest.rs

@@ -114,6 +114,7 @@ where
             return;
         }
 
+        assert_ne!(buf.len(), buf.capacity());
         buf.push(val);
 
         if buf.len() == 2 * k {