fix(optimizer): fix performance regression

compilers/concrete-optimizer/concrete-optimizer/src/optimization/dag/multi_parameters/analyze.rs

@@ -235,6 +235,7 @@ impl VariancedDag {
                         nb_constraints: out_shape.flat_size(),
                         safe_variance_bound: max_variance,
                         noise_expression: variance.clone(),
+                        noise_evaluator: None,
                         location: op.location.clone(),
                     };
                     self.external_variance_constraints.push(constraint);
@@ -273,6 +274,7 @@ impl VariancedDag {
                     nb_constraints: out_shape.flat_size(),
                     safe_variance_bound: max_variance,
                     noise_expression: variance.clone(),
+                    noise_evaluator: None,
                     location: dag_op.location.clone(),
                 };
                 self.external_variance_constraints.push(constraint);
@@ -646,6 +648,7 @@ fn variance_constraint(
         safe_variance_bound,
         nb_partitions,
         noise_expression: noise,
+        noise_evaluator: None,
         location,
     }
 }

compilers/concrete-optimizer/concrete-optimizer/src/optimization/dag/multi_parameters/complexity.rs

@@ -2,7 +2,7 @@ use std::{fmt, ops::Add};
 
 use super::{
     partitions::PartitionIndex,
-    symbolic::{fast_keyswitch, keyswitch, Symbol, SymbolMap},
+    symbolic::{fast_keyswitch, keyswitch, Symbol, SymbolArray, SymbolMap, SymbolScheme},
 };
 
 /// A structure storing the number of times an fhe operation gets executed in a circuit.
@@ -29,36 +29,44 @@ impl fmt::Display for OperationsCount {
 
 /// An ensemble of costs associated with fhe operation symbols.
 #[derive(Clone, Debug)]
-pub struct ComplexityValues(SymbolMap<f64>);
+pub struct ComplexityValues(SymbolArray<f64>);
 
 impl ComplexityValues {
     /// Returns an empty set of cost values.
-    pub fn new() -> Self {
-        ComplexityValues(SymbolMap::new())
+    pub fn from_scheme(scheme: &SymbolScheme) -> ComplexityValues {
+        ComplexityValues(SymbolArray::from_scheme(scheme))
     }
 
     /// Sets the cost associated with an fhe operation symbol.
     pub fn set_cost(&mut self, source: Symbol, value: f64) {
-        self.0.set(source, value);
+        self.0.set(&source, value);
     }
 }
 
 /// A complexity expression is a sum of complexity terms associating operation
 /// symbols with the number of time they gets executed in the circuit.
 #[derive(Clone, Debug)]
-pub struct ComplexityExpression(SymbolMap<usize>);
+pub struct ComplexityEvaluator(SymbolArray<usize>);
 
-impl ComplexityExpression {
+impl ComplexityEvaluator {
     /// Creates a complexity expression from a set of operation counts.
-    pub fn from(counts: &OperationsCount) -> Self {
-        Self(counts.0.clone())
+    pub fn from_scheme_and_counts(
+        scheme: &SymbolScheme,
+        counts: &OperationsCount,
+    ) -> ComplexityEvaluator {
+        Self(SymbolArray::from_scheme_and_map(scheme, &counts.0))
+    }
+
+    pub fn scheme(&self) -> &SymbolScheme {
+        self.0.scheme()
     }
 
     /// Evaluates the total cost expression on a set of cost values.
     pub fn evaluate_total_cost(&self, costs: &ComplexityValues) -> f64 {
-        self.0.iter().fold(0.0, |acc, (symbol, n_ops)| {
-            acc + (n_ops as f64) * costs.0.get(symbol)
-        })
+        self.0
+            .iter()
+            .zip(costs.0.iter())
+            .fold(0.0, |acc, (n_ops, cost)| acc + (*n_ops as f64) * *cost)
     }
 
     /// Evaluates the max ks cost expression on a set of cost values.
@@ -69,11 +77,11 @@ impl ComplexityExpression {
         src_partition: PartitionIndex,
         dst_partition: PartitionIndex,
     ) -> f64 {
-        let actual_ks_cost = costs.0.get(keyswitch(src_partition, dst_partition));
-        let ks_coeff = self.0.get(keyswitch(src_partition, dst_partition));
+        let actual_ks_cost = costs.0.get(&keyswitch(src_partition, dst_partition));
+        let ks_coeff = self.0.get(&keyswitch(src_partition, dst_partition));
         let actual_complexity =
-            self.evaluate_total_cost(costs) - (ks_coeff as f64) * actual_ks_cost;
-        (complexity_cut - actual_complexity) / (ks_coeff as f64)
+            self.evaluate_total_cost(costs) - (*ks_coeff as f64) * actual_ks_cost;
+        (complexity_cut - actual_complexity) / (*ks_coeff as f64)
     }
 
     /// Evaluates the max fks cost expression on a set of cost values.
@@ -84,10 +92,10 @@ impl ComplexityExpression {
         src_partition: PartitionIndex,
         dst_partition: PartitionIndex,
     ) -> f64 {
-        let actual_fks_cost = costs.0.get(fast_keyswitch(src_partition, dst_partition));
-        let fks_coeff = self.0.get(fast_keyswitch(src_partition, dst_partition));
+        let actual_fks_cost = costs.0.get(&fast_keyswitch(src_partition, dst_partition));
+        let fks_coeff = self.0.get(&fast_keyswitch(src_partition, dst_partition));
         let actual_complexity =
-            self.evaluate_total_cost(costs) - (fks_coeff as f64) * actual_fks_cost;
-        (complexity_cut - actual_complexity) / (fks_coeff as f64)
+            self.evaluate_total_cost(costs) - (*fks_coeff as f64) * actual_fks_cost;
+        (complexity_cut - actual_complexity) / (*fks_coeff as f64)
     }
 }

compilers/concrete-optimizer/concrete-optimizer/src/optimization/dag/multi_parameters/feasible.rs

@@ -49,12 +49,18 @@ impl Feasible {
 
         for constraint in &self.undominated_constraints {
             let pbs_coeff = constraint
-                .noise_expression
+                .noise_evaluator
+                .as_ref()
+                .unwrap()
                 .coeff(bootstrap_noise(partition));
             if pbs_coeff == 0.0 {
                 continue;
             }
-            let actual_variance = constraint.noise_expression.evaluate(operations_variance)
+            let actual_variance = constraint
+                .noise_evaluator
+                .as_ref()
+                .unwrap()
+                .evaluate(operations_variance)
                 - pbs_coeff * actual_pbs_variance;
             let pbs_max_variance = (constraint.safe_variance_bound - actual_variance) / pbs_coeff;
             smallest_pbs_max_variance = smallest_pbs_max_variance.min(pbs_max_variance);
@@ -75,12 +81,18 @@ impl Feasible {
 
         for constraint in &self.undominated_constraints {
             let ks_coeff = constraint
-                .noise_expression
+                .noise_evaluator
+                .as_ref()
+                .unwrap()
                 .coeff(keyswitch_noise(src_partition, dst_partition));
             if ks_coeff == 0.0 {
                 continue;
             }
-            let actual_variance = constraint.noise_expression.evaluate(operations_variance)
+            let actual_variance = constraint
+                .noise_evaluator
+                .as_ref()
+                .unwrap()
+                .evaluate(operations_variance)
                 - ks_coeff * actual_ks_variance;
             let ks_max_variance = (constraint.safe_variance_bound - actual_variance) / ks_coeff;
             smallest_ks_max_variance = smallest_ks_max_variance.min(ks_max_variance);
@@ -102,12 +114,18 @@ impl Feasible {
 
         for constraint in &self.undominated_constraints {
             let fks_coeff = constraint
-                .noise_expression
+                .noise_evaluator
+                .as_ref()
+                .unwrap()
                 .coeff(fast_keyswitch_noise(src_partition, dst_partition));
             if fks_coeff == 0.0 {
                 continue;
             }
-            let actual_variance = constraint.noise_expression.evaluate(operations_variance)
+            let actual_variance = constraint
+                .noise_evaluator
+                .as_ref()
+                .unwrap()
+                .evaluate(operations_variance)
                 - fks_coeff * actual_fks_variance;
             let fks_max_variance = (constraint.safe_variance_bound - actual_variance) / fks_coeff;
             smallest_fks_max_variance = smallest_fks_max_variance.min(fks_max_variance);
@@ -126,7 +144,11 @@ impl Feasible {
 
     fn local_feasible(&self, operations_variance: &NoiseValues) -> bool {
         for constraint in &self.undominated_constraints {
-            if constraint.noise_expression.evaluate(operations_variance)
+            if constraint
+                .noise_evaluator
+                .as_ref()
+                .unwrap()
+                .evaluate(operations_variance)
                 > constraint.safe_variance_bound
             {
                 return false;
@@ -148,7 +170,11 @@ impl Feasible {
         let mut worst_relative_variance = 0.0;
         let mut worst_variance = 0.0;
         for constraint in &self.undominated_constraints {
-            let variance = constraint.noise_expression.evaluate(operations_variance);
+            let variance = constraint
+                .noise_evaluator
+                .as_ref()
+                .unwrap()
+                .evaluate(operations_variance);
             let relative_variance = variance / constraint.safe_variance_bound;
             if relative_variance > worst_relative_variance {
                 worst_relative_variance = relative_variance;
@@ -167,7 +193,11 @@ impl Feasible {
     fn global_p_error_with_cut(&self, operations_variance: &NoiseValues, cut: f64) -> Option<f64> {
         let mut global_p_error = 0.0;
         for constraint in &self.constraints {
-            let variance = constraint.noise_expression.evaluate(operations_variance);
+            let variance = constraint
+                .noise_evaluator
+                .as_ref()
+                .unwrap()
+                .evaluate(operations_variance);
             let relative_variance = variance / constraint.safe_variance_bound;
             let p_error = p_error_from_relative_variance(relative_variance, self.kappa);
             global_p_error = combine_errors(

compilers/concrete-optimizer/concrete-optimizer/src/optimization/dag/multi_parameters/noise_expression.rs

@@ -5,28 +5,27 @@ use std::{
 
 use super::{
     partitions::PartitionIndex,
-    symbolic::{Symbol, SymbolMap},
+    symbolic::{Symbol, SymbolArray, SymbolMap, SymbolScheme},
 };
 
 /// An ensemble of noise values for fhe operations.
 #[derive(Debug, Clone, PartialEq)]
-pub struct NoiseValues(SymbolMap<f64>);
+pub struct NoiseValues(SymbolArray<f64>);
 
 impl NoiseValues {
     /// Returns an empty set of noise values.
-    #[allow(clippy::new_without_default)]
-    pub fn new() -> Self {
-        NoiseValues(SymbolMap::new())
+    pub fn from_scheme(scheme: &SymbolScheme) -> NoiseValues {
+        NoiseValues(SymbolArray::from_scheme(scheme))
     }
 
     /// Sets the noise variance associated with a noise source.
     pub fn set_variance(&mut self, source: NoiseSource, value: f64) {
-        self.0.set(source.0, value);
+        self.0.set(&source.0, value);
     }
 
     /// Returns the variance associated with a noise source
     pub fn variance(&self, source: NoiseSource) -> f64 {
-        self.0.get(source.0)
+        *self.0.get(&source.0)
     }
 }
 
@@ -36,10 +35,36 @@ impl Display for NoiseValues {
     }
 }
 
+#[derive(Debug, Clone, PartialEq)]
+pub struct NoiseEvaluator(SymbolArray<f64>);
+
+impl NoiseEvaluator {
+    /// Returns a zero noise expression
+    pub fn from_scheme_and_expression(
+        scheme: &SymbolScheme,
+        expr: &NoiseExpression,
+    ) -> NoiseEvaluator {
+        NoiseEvaluator(SymbolArray::from_scheme_and_map(scheme, &expr.0))
+    }
+
+    /// Returns the coefficient associated with a noise source.
+    pub fn coeff(&self, source: NoiseSource) -> f64 {
+        *self.0.get(&source.0)
+    }
+
+    /// Evaluate the noise expression on a set of noise values.
+    pub fn evaluate(&self, values: &NoiseValues) -> f64 {
+        self.0
+            .iter()
+            .zip(values.0.iter())
+            .fold(0.0, |acc, (coef, var)| acc + coef * var)
+    }
+}
+
 /// A noise expression, i.e. a sum of noise terms associating a noise source,
 /// with a multiplicative coefficient.
 #[derive(Debug, Clone, PartialEq)]
-pub struct NoiseExpression(SymbolMap<f64>);
+pub struct NoiseExpression(pub SymbolMap<f64>);
 
 impl NoiseExpression {
     /// Returns a zero noise expression
@@ -70,12 +95,12 @@ impl NoiseExpression {
         lhs
     }
 
-    /// Evaluate the noise expression on a set of noise values.
-    pub fn evaluate(&self, values: &NoiseValues) -> f64 {
-        self.terms_iter().fold(0.0, |acc, term| {
-            acc + term.coefficient * values.variance(term.source)
-        })
-    }
+    // /// Evaluate the noise expression on a set of noise values.
+    // pub fn evaluate(&self, values: &NoiseValues) -> f64 {
+    //     self.terms_iter().fold(0.0, |acc, term| {
+    //         acc + term.coefficient * values.variance(term.source)
+    //     })
+    // }
 }
 
 impl Display for NoiseExpression {
@@ -196,7 +221,7 @@ impl Mul<NoiseSource> for f64 {
 
 /// A symbolic source of noise, or a noise source variable.
 #[derive(Debug, Hash, PartialEq, Eq, PartialOrd, Ord, Clone, Copy)]
-pub struct NoiseSource(Symbol);
+pub struct NoiseSource(pub Symbol);
 
 /// Returns an input noise source symbol.
 pub fn input_noise(partition: PartitionIndex) -> NoiseSource {