use crate::distributed_simulator::{DistributedQuantumSimulator, DistributedSimulatorConfig};
use crate::large_scale_simulator::{LargeScaleQuantumSimulator, LargeScaleSimulatorConfig};
use quantrs2_circuit::builder::{Circuit, Simulator};
use quantrs2_core::{
error::{QuantRS2Error, QuantRS2Result},
gate::GateOp,
qubit::QubitId,
};
use scirs2_core::parallel_ops::{current_num_threads, IndexedParallelIterator, ParallelIterator};
use scirs2_core::Complex64;
use std::collections::{BTreeMap, BTreeSet, HashMap, HashSet, VecDeque};
use std::sync::{Arc, Barrier, Mutex, RwLock};
use uuid::Uuid;
use super::types::{
AutoParallelConfig, DependencyGraph, GateNode, HardwareCharacteristics, LoadBalancer,
OptimizationRecommendation, ParallelPerformanceStats, ParallelTask, RecommendationComplexity,
RecommendationType, TaskPriority,
};
use super::autoparallelengine_type::AutoParallelEngine;
impl AutoParallelEngine {
#[must_use]
pub fn new(config: AutoParallelConfig) -> Self {
let num_threads = config.max_threads;
Self {
config,
analysis_cache: Arc::new(RwLock::new(HashMap::new())),
performance_stats: Arc::new(Mutex::new(ParallelPerformanceStats::default())),
load_balancer: Arc::new(Mutex::new(LoadBalancer::new(num_threads))),
}
}
pub fn execute_parallel<const N: usize>(
&self,
circuit: &Circuit<N>,
simulator: &mut LargeScaleQuantumSimulator,
) -> QuantRS2Result<Vec<Complex64>> {
let analysis = self.analyze_circuit(circuit)?;
if analysis.tasks.len() < self.config.min_gates_for_parallel {
return Self::execute_sequential(circuit, simulator);
}
let barrier = Arc::new(Barrier::new(self.config.max_threads));
let shared_state = Arc::new(RwLock::new(simulator.get_dense_state()?));
let task_results = Arc::new(Mutex::new(Vec::new()));
self.execute_parallel_tasks(&analysis.tasks, shared_state.clone(), task_results, barrier)?;
let final_state = shared_state
.read()
.expect("shared state read lock should not be poisoned")
.clone();
Ok(final_state)
}
pub(super) fn execute_distributed_tasks(
&self,
distributed_tasks: &[Vec<ParallelTask>],
distributed_sim: &DistributedQuantumSimulator,
) -> QuantRS2Result<Vec<Vec<Complex64>>> {
use scirs2_core::parallel_ops::{parallel_map, IndexedParallelIterator, ParallelIterator};
let cluster_status = distributed_sim.get_cluster_status();
let num_nodes = cluster_status.len();
let node_results: Vec<Vec<Complex64>> =
parallel_map(&(0..num_nodes).collect::<Vec<_>>(), |&node_id| {
let tasks = &distributed_tasks[node_id];
let mut node_result = Vec::new();
for task in tasks {
let task_result = Self::execute_task_on_node(task, node_id);
node_result.extend(task_result);
}
node_result
});
Ok(node_results)
}
pub(super) const fn execute_task_on_node(
task: &ParallelTask,
node_id: usize,
) -> Vec<Complex64> {
Vec::new()
}
pub(super) fn build_dependency_graph<const N: usize>(
&self,
circuit: &Circuit<N>,
) -> QuantRS2Result<DependencyGraph> {
let gates = circuit.gates();
let mut nodes = Vec::with_capacity(gates.len());
let mut edges: HashMap<usize, Vec<usize>> = HashMap::new();
let mut reverse_edges: HashMap<usize, Vec<usize>> = HashMap::new();
for (i, gate) in gates.iter().enumerate() {
let qubits: HashSet<QubitId> = gate.qubits().into_iter().collect();
let cost = Self::estimate_gate_cost(gate.as_ref());
nodes.push(GateNode {
gate_index: i,
gate: gate.clone(),
qubits,
layer: 0,
cost,
});
edges.insert(i, Vec::new());
reverse_edges.insert(i, Vec::new());
}
for i in 0..nodes.len() {
for j in (i + 1)..nodes.len() {
if !nodes[i].qubits.is_disjoint(&nodes[j].qubits) {
if let Some(edge_list) = edges.get_mut(&i) {
edge_list.push(j);
}
if let Some(reverse_edge_list) = reverse_edges.get_mut(&j) {
reverse_edge_list.push(i);
}
}
}
}
let layers = Self::compute_topological_layers(&nodes, &edges)?;
for (layer_idx, layer) in layers.iter().enumerate() {
for &node_idx in layer {
if let Some(node) = nodes.get_mut(node_idx) {
node.layer = layer_idx;
}
}
}
Ok(DependencyGraph {
nodes,
edges,
reverse_edges,
layers,
})
}
pub(super) fn compute_topological_layers(
nodes: &[GateNode],
edges: &HashMap<usize, Vec<usize>>,
) -> QuantRS2Result<Vec<Vec<usize>>> {
let mut in_degree: HashMap<usize, usize> = HashMap::new();
let mut layers = Vec::new();
let mut queue = VecDeque::new();
for i in 0..nodes.len() {
in_degree.insert(i, 0);
}
for to_list in edges.values() {
for &to in to_list {
if let Some(degree) = in_degree.get_mut(&to) {
*degree += 1;
}
}
}
for i in 0..nodes.len() {
if in_degree[&i] == 0 {
queue.push_back(i);
}
}
while !queue.is_empty() {
let mut current_layer = Vec::new();
let layer_size = queue.len();
for _ in 0..layer_size {
if let Some(node) = queue.pop_front() {
current_layer.push(node);
if let Some(neighbors) = edges.get(&node) {
for &neighbor in neighbors {
let new_degree = in_degree[&neighbor] - 1;
in_degree.insert(neighbor, new_degree);
if new_degree == 0 {
queue.push_back(neighbor);
}
}
}
}
}
if !current_layer.is_empty() {
layers.push(current_layer);
}
}
Ok(layers)
}
pub(super) fn dependency_based_parallelization(
&self,
graph: &DependencyGraph,
) -> QuantRS2Result<Vec<ParallelTask>> {
let mut tasks = Vec::new();
for layer in &graph.layers {
if layer.len() > 1 {
let chunks = self.partition_layer_into_tasks(layer, graph)?;
for chunk in chunks {
let task = self.create_parallel_task(chunk, graph)?;
tasks.push(task);
}
} else {
if let Some(&gate_idx) = layer.first() {
let task = self.create_parallel_task(vec![gate_idx], graph)?;
tasks.push(task);
}
}
}
Ok(tasks)
}
pub(super) fn layer_based_parallelization(
&self,
graph: &DependencyGraph,
) -> QuantRS2Result<Vec<ParallelTask>> {
let mut tasks = Vec::new();
for layer in &graph.layers {
let max_gates_per_task = self.config.resource_constraints.max_gates_per_thread;
for chunk in layer.chunks(max_gates_per_task) {
let task = self.create_parallel_task(chunk.to_vec(), graph)?;
tasks.push(task);
}
}
Ok(tasks)
}
pub(super) fn qubit_partitioning_parallelization<const N: usize>(
&self,
circuit: &Circuit<N>,
graph: &DependencyGraph,
) -> QuantRS2Result<Vec<ParallelTask>> {
let qubit_partitions = self.partition_qubits(circuit)?;
let mut tasks = Vec::new();
for partition in qubit_partitions {
let mut partition_gates = Vec::new();
for (i, node) in graph.nodes.iter().enumerate() {
if node.qubits.iter().all(|q| partition.contains(q)) {
partition_gates.push(i);
}
}
if !partition_gates.is_empty() {
let task = self.create_parallel_task(partition_gates, graph)?;
tasks.push(task);
}
}
Ok(tasks)
}
pub(super) fn hybrid_parallelization<const N: usize>(
&self,
circuit: &Circuit<N>,
graph: &DependencyGraph,
) -> QuantRS2Result<Vec<ParallelTask>> {
let dependency_tasks = self.dependency_based_parallelization(graph)?;
let layer_tasks = self.layer_based_parallelization(graph)?;
let partition_tasks = self.qubit_partitioning_parallelization(circuit, graph)?;
let strategies = vec![
("dependency", dependency_tasks),
("layer", layer_tasks),
("partition", partition_tasks),
];
let best_strategy = strategies.into_iter().max_by(|(_, tasks_a), (_, tasks_b)| {
let efficiency_a = Self::calculate_strategy_efficiency(tasks_a);
let efficiency_b = Self::calculate_strategy_efficiency(tasks_b);
efficiency_a
.partial_cmp(&efficiency_b)
.unwrap_or(std::cmp::Ordering::Equal)
});
match best_strategy {
Some((_, tasks)) => Ok(tasks),
None => Ok(Vec::new()),
}
}
pub(super) fn aggressive_parallelization(
&self,
graph: &DependencyGraph,
) -> QuantRS2Result<Vec<ParallelTask>> {
let mut tasks = Vec::new();
let mut visited = vec![false; graph.nodes.len()];
for (idx, node) in graph.nodes.iter().enumerate() {
if visited[idx] {
continue;
}
let mut parallel_group = vec![idx];
visited[idx] = true;
for (other_idx, other_node) in graph.nodes.iter().enumerate() {
if visited[other_idx] {
continue;
}
if !Self::gates_have_dependency(idx, other_idx, graph)
&& !Self::gates_share_qubits(&node.qubits, &other_node.qubits)
{
parallel_group.push(other_idx);
visited[other_idx] = true;
}
}
if !parallel_group.is_empty() {
tasks.push(self.create_parallel_task(parallel_group, graph)?);
}
}
Ok(tasks)
}
pub(super) fn calculate_gate_distribution(
gates: &[Arc<dyn GateOp + Send + Sync>],
) -> HashMap<String, usize> {
let mut distribution = HashMap::new();
for gate in gates {
let gate_type = format!("{gate:?}");
*distribution.entry(gate_type).or_insert(0) += 1;
}
distribution
}
pub(super) fn merge_small_tasks(
&self,
tasks: Vec<ParallelTask>,
) -> QuantRS2Result<Vec<ParallelTask>> {
let mut merged = Vec::new();
let mut current_batch = Vec::new();
let mut current_cost = 0.0;
const COST_THRESHOLD: f64 = 10.0;
for task in tasks {
if task.cost < COST_THRESHOLD {
current_batch.push(task);
if let Some(last_task) = current_batch.last() {
current_cost += last_task.cost;
}
if current_cost >= COST_THRESHOLD {
merged.push(Self::merge_task_batch(current_batch)?);
current_batch = Vec::new();
current_cost = 0.0;
}
} else {
merged.push(task);
}
}
if !current_batch.is_empty() {
merged.push(Self::merge_task_batch(current_batch)?);
}
Ok(merged)
}
pub(super) fn split_large_tasks(tasks: Vec<ParallelTask>) -> QuantRS2Result<Vec<ParallelTask>> {
let mut split_tasks = Vec::new();
const COST_THRESHOLD: f64 = 100.0;
for task in tasks {
if task.cost > COST_THRESHOLD && task.gates.len() > 4 {
let mid = task.gates.len() / 2;
let (gates1, gates2) = task.gates.split_at(mid);
split_tasks.push(ParallelTask {
id: Uuid::new_v4(),
gates: gates1.to_vec(),
qubits: task.qubits.clone(),
cost: task.cost / 2.0,
memory_requirement: task.memory_requirement / 2,
dependencies: task.dependencies.clone(),
priority: task.priority,
});
split_tasks.push(ParallelTask {
id: Uuid::new_v4(),
gates: gates2.to_vec(),
qubits: task.qubits.clone(),
cost: task.cost / 2.0,
memory_requirement: task.memory_requirement / 2,
dependencies: HashSet::new(),
priority: task.priority,
});
} else {
split_tasks.push(task);
}
}
Ok(split_tasks)
}
pub(super) fn merge_task_batch(batch: Vec<ParallelTask>) -> QuantRS2Result<ParallelTask> {
let mut merged_gates = Vec::new();
let mut merged_qubits = HashSet::new();
let mut merged_cost = 0.0;
let mut merged_memory = 0;
let mut merged_deps = HashSet::new();
let mut max_priority = TaskPriority::Low;
for task in batch {
merged_gates.extend(task.gates);
merged_qubits.extend(task.qubits);
merged_cost += task.cost;
merged_memory += task.memory_requirement;
merged_deps.extend(task.dependencies);
if task.priority as u8 > max_priority as u8 {
max_priority = task.priority;
}
}
Ok(ParallelTask {
id: Uuid::new_v4(),
gates: merged_gates,
qubits: merged_qubits,
cost: merged_cost,
memory_requirement: merged_memory,
dependencies: merged_deps,
priority: max_priority,
})
}
pub(super) fn cache_optimized_parallelization(
&self,
graph: &DependencyGraph,
hw_char: &HardwareCharacteristics,
) -> QuantRS2Result<Vec<ParallelTask>> {
let max_task_size = hw_char.l2_cache_size / (16 * 2);
let mut tasks = Vec::new();
let mut current_group = Vec::new();
let mut current_size = 0;
for (idx, node) in graph.nodes.iter().enumerate() {
let gate_size = (1 << node.qubits.len()) * 16;
if current_size + gate_size > max_task_size && !current_group.is_empty() {
tasks.push(self.create_parallel_task(current_group, graph)?);
current_group = Vec::new();
current_size = 0;
}
current_group.push(idx);
current_size += gate_size;
}
if !current_group.is_empty() {
tasks.push(self.create_parallel_task(current_group, graph)?);
}
Ok(tasks)
}
pub(super) fn simd_optimized_parallelization(
&self,
graph: &DependencyGraph,
hw_char: &HardwareCharacteristics,
) -> QuantRS2Result<Vec<ParallelTask>> {
let mut rotation_gates = Vec::new();
let mut other_gates = Vec::new();
for (idx, node) in graph.nodes.iter().enumerate() {
if Self::is_rotation_gate(node.gate.as_ref()) {
rotation_gates.push(idx);
} else {
other_gates.push(idx);
}
}
let mut tasks = Vec::new();
let vec_width = hw_char.simd_width / 128;
for chunk in rotation_gates.chunks(vec_width) {
tasks.push(self.create_parallel_task(chunk.to_vec(), graph)?);
}
for idx in other_gates {
tasks.push(self.create_parallel_task(vec![idx], graph)?);
}
Ok(tasks)
}
pub(super) fn numa_aware_parallelization(
&self,
graph: &DependencyGraph,
hw_char: &HardwareCharacteristics,
) -> QuantRS2Result<Vec<ParallelTask>> {
let num_nodes = hw_char.num_numa_nodes;
let mut node_tasks: Vec<Vec<usize>> = vec![Vec::new(); num_nodes];
for (idx, node) in graph.nodes.iter().enumerate() {
let numa_node = Self::select_numa_node(node, num_nodes);
node_tasks[numa_node].push(idx);
}
let mut tasks = Vec::new();
for node_task_indices in node_tasks {
if !node_task_indices.is_empty() {
tasks.push(self.create_parallel_task(node_task_indices, graph)?);
}
}
Ok(tasks)
}
pub(super) fn refine_for_cache(
tasks: Vec<ParallelTask>,
hw_char: &HardwareCharacteristics,
) -> QuantRS2Result<Vec<ParallelTask>> {
let max_cache_size = hw_char.l2_cache_size;
let mut refined = Vec::new();
for task in tasks {
if task.memory_requirement > max_cache_size {
let mid = task.gates.len() / 2;
let (gates1, gates2) = task.gates.split_at(mid);
refined.push(ParallelTask {
id: Uuid::new_v4(),
gates: gates1.to_vec(),
qubits: task.qubits.clone(),
cost: task.cost / 2.0,
memory_requirement: task.memory_requirement / 2,
dependencies: task.dependencies.clone(),
priority: task.priority,
});
refined.push(ParallelTask {
id: Uuid::new_v4(),
gates: gates2.to_vec(),
qubits: task.qubits,
cost: task.cost / 2.0,
memory_requirement: task.memory_requirement / 2,
dependencies: HashSet::new(),
priority: task.priority,
});
} else {
refined.push(task);
}
}
Ok(refined)
}
pub(super) fn create_parallel_task(
&self,
gate_indices: Vec<usize>,
graph: &DependencyGraph,
) -> QuantRS2Result<ParallelTask> {
let mut gates = Vec::new();
let mut qubits = HashSet::new();
let mut total_cost = 0.0;
let mut memory_requirement = 0;
for &idx in &gate_indices {
if let Some(node) = graph.nodes.get(idx) {
gates.push(node.gate.clone());
qubits.extend(&node.qubits);
total_cost += node.cost;
memory_requirement += Self::estimate_gate_memory(node.gate.as_ref());
}
}
let dependencies = self.calculate_task_dependencies(&gate_indices, graph)?;
Ok(ParallelTask {
id: Uuid::new_v4(),
gates,
qubits,
cost: total_cost,
memory_requirement,
dependencies,
priority: TaskPriority::Normal,
})
}
pub(super) fn calculate_task_dependencies(
&self,
gate_indices: &[usize],
graph: &DependencyGraph,
) -> QuantRS2Result<HashSet<Uuid>> {
let mut dependencies = HashSet::new();
for &gate_idx in gate_indices {
if let Some(parent_indices) = graph.reverse_edges.get(&gate_idx) {
for &parent_idx in parent_indices {
if !gate_indices.contains(&parent_idx) {
let dep_uuid = Self::generate_gate_dependency_uuid(parent_idx);
dependencies.insert(dep_uuid);
}
}
}
}
Ok(dependencies)
}
pub(super) fn partition_layer_into_tasks(
&self,
layer: &[usize],
graph: &DependencyGraph,
) -> QuantRS2Result<Vec<Vec<usize>>> {
let max_gates_per_task = self.config.resource_constraints.max_gates_per_thread;
let mut chunks = Vec::new();
for chunk in layer.chunks(max_gates_per_task) {
chunks.push(chunk.to_vec());
}
Ok(chunks)
}
pub(super) fn partition_qubits<const N: usize>(
&self,
circuit: &Circuit<N>,
) -> QuantRS2Result<Vec<HashSet<QubitId>>> {
let mut partitions = Vec::new();
let mut used_qubits = HashSet::new();
for i in 0..N {
let qubit = QubitId::new(i as u32);
if used_qubits.insert(qubit) {
let mut partition = HashSet::new();
partition.insert(qubit);
partitions.push(partition);
}
}
Ok(partitions)
}
pub(super) fn generate_optimization_recommendations<const N: usize>(
&self,
circuit: &Circuit<N>,
graph: &DependencyGraph,
tasks: &[ParallelTask],
) -> Vec<OptimizationRecommendation> {
let mut recommendations = Vec::new();
if graph.layers.iter().any(|layer| layer.len() == 1) {
recommendations.push(OptimizationRecommendation {
recommendation_type: RecommendationType::GateReordering,
description: "Consider reordering gates to create larger parallel layers"
.to_string(),
expected_improvement: 0.2,
complexity: RecommendationComplexity::Medium,
});
}
let task_costs: Vec<f64> = tasks.iter().map(|t| t.cost).collect();
let cost_variance = Self::calculate_variance(&task_costs);
if cost_variance > 0.5 {
recommendations.push(OptimizationRecommendation {
recommendation_type: RecommendationType::ResourceAllocation,
description: "Task costs are unbalanced, consider load balancing optimization"
.to_string(),
expected_improvement: 0.15,
complexity: RecommendationComplexity::Low,
});
}
recommendations
}
pub(super) fn execute_sequential<const N: usize>(
circuit: &Circuit<N>,
simulator: &LargeScaleQuantumSimulator,
) -> QuantRS2Result<Vec<Complex64>> {
let result = simulator.run(circuit)?;
Ok(Vec::new())
}
pub(super) fn compute_circuit_hash<const N: usize>(circuit: &Circuit<N>) -> u64 {
use std::collections::hash_map::DefaultHasher;
use std::hash::{Hash, Hasher};
let mut hasher = DefaultHasher::new();
circuit.num_gates().hash(&mut hasher);
circuit.num_qubits().hash(&mut hasher);
for gate in circuit.gates() {
gate.name().hash(&mut hasher);
gate.qubits().len().hash(&mut hasher);
}
hasher.finish()
}
}