Introduce benchmarks using Criterion

Signed-off-by: Julius Koskela <julius.koskela@unikie.com>

Cargo.lock

@@ -299,6 +299,7 @@ dependencies = [
  "criterion",
  "getset",
  "itertools 0.12.0",
+ "ndarray",
  "num",
  "rand",
  "serde",
@@ -307,12 +308,35 @@ dependencies = [
  "thiserror",
 ]
 
+[[package]]
+name = "matrixmultiply"
+version = "0.3.8"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "7574c1cf36da4798ab73da5b215bbf444f50718207754cb522201d78d1cd0ff2"
+dependencies = [
+ "autocfg",
+ "rawpointer",
+]
+
 [[package]]
 name = "memchr"
 version = "2.7.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "523dc4f511e55ab87b694dc30d0f820d60906ef06413f93d4d7a1385599cc149"
 
+[[package]]
+name = "ndarray"
+version = "0.15.6"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "adb12d4e967ec485a5f71c6311fe28158e9d6f4bc4a447b474184d0f91a8fa32"
+dependencies = [
+ "matrixmultiply",
+ "num-complex",
+ "num-integer",
+ "num-traits",
+ "rawpointer",
+]
+
 [[package]]
 name = "num"
 version = "0.4.1"
@@ -507,6 +531,12 @@ dependencies = [
  "getrandom",
 ]
 
+[[package]]
+name = "rawpointer"
+version = "0.2.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "60a357793950651c4ed0f3f52338f53b2f809f32d83a07f72909fa13e4c6c1e3"
+
 [[package]]
 name = "rayon"
 version = "1.8.0"

Cargo.toml

@@ -27,3 +27,8 @@ rand = "0.8.5"
 criterion = "0.5.1"
 serde_json = "1.0.108"
 static_assertions = "1.1.0"
+ndarray = "0.15.6"
+
+[[bench]]
+name = "manifold_benchmark"
+harness = false

benches/manifold_benchmark.rs

@@ -0,0 +1,60 @@
+use manifold::*;
+use rand::Rng;
+use criterion::Throughput;
+use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion};
+
+fn random_tensor_r2_manifold() -> Tensor<f64, 2> {
+	let mut rng = rand::thread_rng();
+	let mut tensor = tensor!([[0.0; 1000]; 1000]);
+	for i in 0..tensor.len() {
+		tensor[i] = rng.gen();
+	}
+	tensor
+}
+
+fn random_tensor_r2_ndarray() -> ndarray::Array2<f64> {
+    let mut rng = rand::thread_rng();
+    let (rows, cols) = (1000, 1000);
+    let mut tensor = ndarray::Array2::<f64>::zeros((rows, cols));
+    for i in 0..rows {
+        for j in 0..cols {
+            tensor[[i, j]] = rng.gen();
+        }
+    }
+    tensor
+}
+
+fn tensor_product(c: &mut Criterion) {
+	let b = 1000;
+
+	let mut group = c.benchmark_group("element-wise addition");
+
+	for (i, size) in [b].iter().enumerate() {
+		group.throughput(Throughput::Elements(*size as u64));
+
+		group.bench_with_input(BenchmarkId::new("manifold", size), &i, |b, _| {
+			b.iter(|| {
+				let a = random_tensor_r2_manifold();
+				let b = random_tensor_r2_manifold();
+				let c = a + b;
+				assert!(c.shape().as_array() == &[1000, 1000]);
+			})
+		});
+
+		group.bench_with_input(BenchmarkId::new("ndarray", size), &i, |b, _| {
+			b.iter(|| {
+				let a = random_tensor_r2_ndarray();
+				let b = random_tensor_r2_ndarray();
+				let c = a + b;
+				assert!(c.shape() == &[1000, 1000]);
+			})
+		});
+	}
+	group.finish();
+}
+
+criterion_group!(
+	benches,
+	tensor_product
+);
+criterion_main!(benches);