diff --git a/juno_frontend/src/lang.l b/juno_frontend/src/lang.l
index 6399e5f266640966ce660c5ec28c9c5c5be2beb2..9daf3f41c5352f2e9ec59ced31dd84c607a5e9f8 100644
--- a/juno_frontend/src/lang.l
+++ b/juno_frontend/src/lang.l
@@ -129,7 +129,7 @@ _ "_"
0x[0-9a-fA-F]+ "HEX_INT"
0b[0-1]+ "BIN_INT"
0o[0-7]+ "OCT_INT"
-[0-9]+\.[0-9]*(|e[0-9]+) "FLOAT_LIT"
+[0-9]+\.[0-9]+(|e[0-9]+) "FLOAT_LIT"
@[a-zA-Z0-9_]+ "LABEL"
. "UNMATCHED"
diff --git a/juno_frontend/src/lang.y b/juno_frontend/src/lang.y
index a5b82452d5aa588782dd01396c208ef2d159be45..be9161aaf4515123995602b8d6077fc8157a1c96 100644
--- a/juno_frontend/src/lang.y
+++ b/juno_frontend/src/lang.y
@@ -302,7 +302,7 @@ Stmt -> Result<Stmt, ()>
inclusive: false, step: None, body: Box::new($7?) }) }
| 'for' VarBind 'in' NonStructExpr '..' '=' NonStructExpr Stmts
{ Ok(Stmt::ForStmt{ span: $span, var: $2?, init: $4?, bound: $7?,
- inclusive: false, step: None, body: Box::new($8?) }) }
+ inclusive: true, step: None, body: Box::new($8?) }) }
| 'while' NonStructExpr Stmts
{ Ok(Stmt::WhileStmt{ span : $span, cond : $2?, body : Box::new($3?) }) }
| 'return' ';'
diff --git a/juno_samples/rodinia/backprop/src/backprop.jn b/juno_samples/rodinia/backprop/src/backprop.jn
index e94e097a79fc7afade2073fd8e3b0d59bb05bb42..2927dbb59ef55681160fae56dcea64a3b8329a27 100644
--- a/juno_samples/rodinia/backprop/src/backprop.jn
+++ b/juno_samples/rodinia/backprop/src/backprop.jn
@@ -7,12 +7,12 @@ fn layer_forward<n, m: usize>(vals: f32[n + 1], weights: f32[n + 1, m + 1]) -> f
let result : f32[m + 1];
result[0] = 1.0;
- for j = 0 to m {
+ for j in 1..=m {
let sum = 0.0;
- for k = 0 to n+1 {
- sum += weights[k, j+1] * vals[k];
+ for k in 0..=n {
+ sum += weights[k, j] * vals[k];
}
- result[j + 1] = squash(sum);
+ result[j] = squash(sum);
}
return result;
@@ -22,11 +22,11 @@ fn output_error<n: usize>(target: f32[n + 1], actual: f32[n + 1]) -> (f32, f32[n
let errsum = 0.0;
let delta : f32[n + 1];
- for j = 0 to n {
- let a = actual[j + 1];
- let t = target[j + 1];
- delta[j + 1] = a * (1.0 - a) * (t - a);
- errsum += abs!(delta[j + 1]);
+ for j in 1..=n {
+ let a = actual[j];
+ let t = target[j];
+ delta[j] = a * (1.0 - a) * (t - a);
+ errsum += abs!(delta[j]);
}
return (errsum, delta);
@@ -40,16 +40,16 @@ fn hidden_error<hidden_n, output_n: usize>(
let errsum = 0.0;
let delta : f32[hidden_n + 1];
- for j = 0 to hidden_n {
- let h = hidden_vals[j + 1];
+ for j in 1..=hidden_n {
+ let h = hidden_vals[j];
let sum = 0.0;
- for k = 0 to output_n {
- sum += out_delta[k + 1] * hidden_weights[j + 1, k + 1];
+ for k in 1..=output_n {
+ sum += out_delta[k] * hidden_weights[j, k];
}
- delta[j + 1] = h * (1.0 - h) * sum;
- errsum += abs!(delta[j + 1]);
+ delta[j] = h * (1.0 - h) * sum;
+ errsum += abs!(delta[j]);
}
return (errsum, delta);
@@ -64,11 +64,11 @@ fn adjust_weights<n, m: usize>(
weights: f32[n + 1, m + 1],
prev_weights: f32[n + 1, m + 1]
) -> (f32[n + 1, m + 1], f32[n + 1, m + 1]) {
- for j = 0 to m {
- for k = 0 to n+1 {
- let new_dw = ETA * delta[j+1] * vals[k] + MOMENTUM * prev_weights[k, j+1];
- weights[k, j+1] += new_dw;
- prev_weights[k, j+1] = new_dw;
+ for j in 1..=m {
+ for k in 0..=n {
+ let new_dw = ETA * delta[j] * vals[k] + MOMENTUM * prev_weights[k, j];
+ weights[k, j] += new_dw;
+ prev_weights[k, j] = new_dw;
}
}
diff --git a/juno_samples/rodinia/bfs/src/bfs.jn b/juno_samples/rodinia/bfs/src/bfs.jn
index 21518083c412eda12ab7b43daa28a6c35fa0e9c3..cf2ea086619dd431e8edd30c51d86d35972296fc 100644
--- a/juno_samples/rodinia/bfs/src/bfs.jn
+++ b/juno_samples/rodinia/bfs/src/bfs.jn
@@ -14,7 +14,7 @@ fn bfs<n, m: usize>(graph_nodes: Node[n], source: u32, edges: u32[m]) -> i32[n]
visited[source as u64] = true;
let cost: i32[n];
- for i = 0 to n {
+ for i in 0..n {
cost[i] = -1;
}
cost[source as u64] = 0;
@@ -25,14 +25,14 @@ fn bfs<n, m: usize>(graph_nodes: Node[n], source: u32, edges: u32[m]) -> i32[n]
while !stop {
stop = true;
- for i = 0 to n {
+ for i in 0..n {
if mask[i] {
mask[i] = false;
let edge_start = graph_nodes[i].edge_start as u64;
let num_edges = graph_nodes[i].num_edges as u64;
- for edge = edge_start to edge_start + num_edges {
+ for edge in edge_start..edge_start + num_edges {
let id = edges[edge] as u64;
if !visited[id] {
cost[id] = cost[i] + 1;
@@ -42,7 +42,7 @@ fn bfs<n, m: usize>(graph_nodes: Node[n], source: u32, edges: u32[m]) -> i32[n]
}
}
- for i = 0 to n {
+ for i in 0..n {
if updated[i] {
mask[i] = true;
visited[i] = true;
diff --git a/juno_samples/rodinia/cfd/src/euler.jn b/juno_samples/rodinia/cfd/src/euler.jn
index 984d5a938c6128f6f1bb7ab22a9c6ac3ff71d952..203cfd96008237f57ec276973d70304e56159682 100644
--- a/juno_samples/rodinia/cfd/src/euler.jn
+++ b/juno_samples/rodinia/cfd/src/euler.jn
@@ -49,7 +49,7 @@ fn compute_speed_of_sound(density: f32, pressure: f32) -> f32 {
fn compute_step_factor<nelr: usize>(variables: Variables::<nelr>, areas: f32[nelr]) -> f32[nelr] {
let step_factors : f32[nelr];
- for i = 0 to nelr {
+ for i in 0..nelr {
let density = variables.density[i];
let momentum : float3;
@@ -108,7 +108,7 @@ fn compute_flux<nelr: usize>(
const smoothing_coefficient : f32 = 0.2;
let fluxes: Variables::<nelr>;
- for i = 0 to nelr {
+ for i in 0..nelr {
let density_i = variables.density[i];
let momentum_i = float3 { x: variables.momentum.x[i],
@@ -131,7 +131,7 @@ fn compute_flux<nelr: usize>(
let flux_i_momentum = float3 { x: 0.0, y: 0.0, z: 0.0 };
let flux_i_density_energy : f32 = 0.0;
- for j = 0 to NNB {
+ for j in 0..NNB {
let nb = elements_surrounding_elements[j, i];
let normal = float3 {
x: normals.x[j, i],
@@ -235,7 +235,7 @@ fn time_step<nelr: usize>(
step_factors: f32[nelr],
fluxes: Variables::<nelr>,
) -> Variables::<nelr> {
- for i = 0 to nelr {
+ for i in 0..nelr {
let factor = step_factors[i] / (RK + 1 - j) as f32;
variables.density[i] = old_variables.density[i] + factor * fluxes.density[i];
@@ -251,7 +251,7 @@ fn time_step<nelr: usize>(
fn copy_vars<nelr: usize>(variables: Variables::<nelr>) -> Variables::<nelr> {
let result : Variables::<nelr>;
- for i = 0 to nelr {
+ for i in 0..nelr {
result.density[i] = variables.density[i];
result.momentum.x[i] = variables.momentum.x[i];
result.momentum.y[i] = variables.momentum.y[i];
@@ -275,11 +275,11 @@ fn euler<nelr: usize>(
ff_flux_contribution_momentum_y: float3,
ff_flux_contribution_momentum_z: float3,
) -> Variables::<nelr> {
- for i = 0 to iterations {
+ for i in 0..iterations {
let old_variables = copy_vars::<nelr>(variables);
let step_factors = compute_step_factor::<nelr>(variables, areas);
- for j = 0 to RK {
+ for j in 0..RK {
let fluxes = compute_flux::<nelr>(variables, elements_surrounding_elements,
normals, ff_variable, ff_flux_contribution_density_energy,
ff_flux_contribution_momentum_x,
diff --git a/juno_samples/rodinia/cfd/src/pre_euler.jn b/juno_samples/rodinia/cfd/src/pre_euler.jn
index 22f40b57073cc5da4903040459a8bd4afcf4d77b..c200f2db9a2be4708c4cf1c90c60eef0b7d7a11e 100644
--- a/juno_samples/rodinia/cfd/src/pre_euler.jn
+++ b/juno_samples/rodinia/cfd/src/pre_euler.jn
@@ -60,7 +60,7 @@ fn compute_speed_of_sound(density: f32, pressure: f32) -> f32 {
fn compute_step_factor<nelr: usize>(variables: Variables::<nelr>, areas: f32[nelr]) -> f32[nelr] {
let step_factors : f32[nelr];
- for i = 0 to nelr {
+ for i in 0..nelr {
let density = variables.density[i];
let momentum : float3;
@@ -114,7 +114,7 @@ fn compute_flux_contributions<nelr: usize>(
let fc_momentum_z: Momentum::<nelr>;
let fc_density_energy: Momentum::<nelr>;
- for i = 0 to nelr {
+ for i in 0..nelr {
let density_i = variables.density[i];
let momentum_i = float3 { x: variables.momentum.x[i],
@@ -169,7 +169,7 @@ fn compute_flux<nelr: usize>(
const smoothing_coefficient : f32 = 0.2;
let fluxes: Variables::<nelr>;
- for i = 0 to nelr {
+ for i in 0..nelr {
let density_i = variables.density[i];
let momentum_i = float3 { x: variables.momentum.x[i],
@@ -201,7 +201,7 @@ fn compute_flux<nelr: usize>(
let flux_i_momentum = float3 { x: 0.0, y: 0.0, z: 0.0 };
let flux_i_density_energy : f32 = 0.0;
- for j = 0 to NNB {
+ for j in 0..NNB {
let nb = elements_surrounding_elements[j, i];
let normal = float3 {
x: normals.x[j, i],
@@ -314,7 +314,7 @@ fn time_step<nelr: usize>(
step_factors: f32[nelr],
fluxes: Variables::<nelr>,
) -> Variables::<nelr> {
- for i = 0 to nelr {
+ for i in 0..nelr {
let factor = step_factors[i] / (RK + 1 - j) as f32;
variables.density[i] = old_variables.density[i] + factor * fluxes.density[i];
@@ -330,7 +330,7 @@ fn time_step<nelr: usize>(
fn copy_vars<nelr: usize>(variables: Variables::<nelr>) -> Variables::<nelr> {
let result : Variables::<nelr>;
- for i = 0 to nelr {
+ for i in 0..nelr {
result.density[i] = variables.density[i];
result.momentum.x[i] = variables.momentum.x[i];
result.momentum.y[i] = variables.momentum.y[i];
@@ -354,11 +354,11 @@ fn pre_euler<nelr: usize>(
ff_fc_momentum_y: float3,
ff_fc_momentum_z: float3,
) -> Variables::<nelr> {
- for i = 0 to iterations {
+ for i in 0..iterations {
let old_variables = copy_vars::<nelr>(variables);
let step_factors = compute_step_factor::<nelr>(variables, areas);
- for j = 0 to RK {
+ for j in 0..RK {
let (fc_momentum_x, fc_momentum_y, fc_momentum_z, fc_density_energy)
= compute_flux_contributions::<nelr>(variables);
let fluxes = compute_flux::<nelr>(variables, elements_surrounding_elements,
diff --git a/juno_samples/rodinia/srad/src/srad.jn b/juno_samples/rodinia/srad/src/srad.jn
index c49d7636e2a8d8fa009bad05e2b8653b42fe1d24..5eea647c58949ebd951149f57e1961cebe6fc443 100644
--- a/juno_samples/rodinia/srad/src/srad.jn
+++ b/juno_samples/rodinia/srad/src/srad.jn
@@ -1,16 +1,16 @@
// HPVM put the extract and compress kernels in the host code, but the CUDA and
// OpenCL versions of Rodinia put them on the device
fn extract<nrows, ncols: usize>(inout image: f32[ncols, nrows], max: f32) {
- for j = 0 to ncols {
- for i = 0 to nrows {
+ for j in 0..ncols {
+ for i in 0..nrows {
image[j, i] = exp!(image[j, i] / max);
}
}
}
fn compress<nrows, ncols: usize>(inout image: f32[ncols, nrows], max: f32) {
- for j = 0 to ncols {
- for i = 0 to nrows {
+ for j in 0..ncols {
+ for i in 0..nrows {
image[j, i] = ln!(image[j, i]) * max;
}
}
@@ -32,14 +32,14 @@ fn srad<nrows, ncols: usize>(
extract::<nrows, ncols>(&image, max);
- for iter = 0 to niter {
+ for iter in 0..niter {
let sum = 0;
let sum2 = 0;
// These loops should really be interchanged, but they aren't in the
// Rodinia source (though they are in the HPVM source)
- for i = 0 to nrows {
- for j = 0 to ncols {
+ for i in 0..nrows {
+ for j in 0..ncols {
let tmp = image[j, i];
sum += tmp;
sum2 += tmp * tmp;
@@ -57,8 +57,8 @@ fn srad<nrows, ncols: usize>(
let c : f32[ncols, nrows];
- for j = 0 to ncols {
- for i = 0 to nrows {
+ for j in 0..ncols {
+ for i in 0..nrows {
let Jc = image[j, i];
dN[j, i] = image[j, iN[i] as u64] - Jc;
dS[j, i] = image[j, iS[i] as u64] - Jc;
@@ -82,8 +82,8 @@ fn srad<nrows, ncols: usize>(
}
}
- for j = 0 to ncols {
- for i = 0 to nrows {
+ for j in 0..ncols {
+ for i in 0..nrows {
let cN = c[j, i];
let cS = c[j, iS[i] as u64];
let cW = c[j, i];