Rodinia benches

• Set up benches for rodinia samples.

juno_samples/rodinia/backprop/benches/backprop_bench.rs

+#![feature(concat_idents)]
+use criterion::{criterion_group, criterion_main, Criterion};
+use rand::rngs::StdRng;
+use rand::{Rng, SeedableRng};
+
+use hercules_rt::{runner, HerculesImmBox, HerculesImmBoxTo, HerculesMutBox, HerculesMutBoxTo};
+
+juno_build::juno!("backprop");
+
+fn backprop_bench(c: &mut Criterion) {
+    let mut group = c.benchmark_group("backprop bench");
+    group.sample_size(10);
+
+    let mut rng = StdRng::seed_from_u64(7);
+
+    let input_n = 65536;
+    let hidden_n = 16;
+    let output_n = 1;
+
+    let mut input_vals = vec![0.0f32; input_n + 1];
+    input_vals[0] = 1.0;
+
+    // For some reason the bpnn_randomize_row function used on target just sets it to 0.1
+    let target = vec![0.1f32; output_n + 1];
+
+    let input_weights = (0..(input_n + 1) * (hidden_n + 1))
+        .map(|_| rng.random::<f32>())
+        .collect::<Vec<_>>();
+    let hidden_weights = (0..(hidden_n + 1) * (output_n + 1))
+        .map(|_| rng.random::<f32>())
+        .collect::<Vec<_>>();
+
+    let input_prev_weights = vec![0.0; (input_n + 1) * (hidden_n + 1)];
+    let hidden_prev_weights = vec![0.0; (hidden_n + 1) * (output_n + 1)];
+
+    let mut r = runner!(backprop);
+    let input_vals = HerculesImmBox::from(&input_vals as &[f32]);
+    let target = HerculesImmBox::from(&target as &[f32]);
+    let mut input_weights = HerculesMutBox::from(input_weights.to_vec());
+    let mut hidden_weights = HerculesMutBox::from(hidden_weights.to_vec());
+    let mut input_prev_weights = HerculesMutBox::from(input_prev_weights.to_vec());
+    let mut hidden_prev_weights = HerculesMutBox::from(hidden_prev_weights.to_vec());
+
+    group.bench_function("backprop bench", |b| {
+        b.iter(|| {
+            async_std::task::block_on(async {
+                r.run(
+                    input_n as u64,
+                    hidden_n as u64,
+                    output_n as u64,
+                    input_vals.to(),
+                    input_weights.to(),
+                    hidden_weights.to(),
+                    target.to(),
+                    input_prev_weights.to(),
+                    hidden_prev_weights.to(),
+                )
+                .await
+            });
+        })
+    });
+}
+
+criterion_group!(benches, backprop_bench);
+criterion_main!(benches);