quantrs2_device/algorithm_marketplace/
optimization.rs

1//! Algorithm Optimization Engine
2//!
3//! This module provides optimization services for quantum algorithms including
4//! performance tuning, resource optimization, and adaptive parameter selection.
5
6use super::*;
7
8/// Algorithm optimization engine
9pub struct AlgorithmOptimizationEngine {
10    config: OptimizationConfig,
11    optimization_strategies: Vec<Box<dyn OptimizationStrategy + Send + Sync>>,
12    performance_analyzer: PerformanceAnalyzer,
13    parameter_optimizer: ParameterOptimizer,
14    resource_optimizer: ResourceOptimizer,
15}
16
17/// Optimization configuration
18#[derive(Debug, Clone, Serialize, Deserialize)]
19pub struct OptimizationConfig {
20    pub enabled: bool,
21    pub optimization_level: OptimizationLevel,
22    pub target_metrics: Vec<String>,
23    pub optimization_budget: OptimizationBudget,
24    pub parallel_optimization: bool,
25    pub caching_enabled: bool,
26}
27
28/// Optimization levels
29#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
30pub enum OptimizationLevel {
31    None,
32    Basic,
33    Aggressive,
34    Experimental,
35    Custom(String),
36}
37
38/// Optimization budget
39#[derive(Debug, Clone, Serialize, Deserialize)]
40pub struct OptimizationBudget {
41    pub max_iterations: usize,
42    pub max_time: Duration,
43    pub max_cost: f64,
44    pub max_resource_usage: f64,
45}
46
47/// Optimization strategy trait
48pub trait OptimizationStrategy {
49    fn optimize(
50        &self,
51        algorithm: &AlgorithmOptimizationContext,
52    ) -> DeviceResult<OptimizationResult>;
53    fn get_strategy_name(&self) -> String;
54    fn supports_algorithm_type(&self, algorithm_type: &AlgorithmCategory) -> bool;
55}
56
57/// Algorithm optimization context
58#[derive(Debug, Clone)]
59pub struct AlgorithmOptimizationContext {
60    pub algorithm_id: String,
61    pub algorithm_type: AlgorithmCategory,
62    pub current_parameters: HashMap<String, f64>,
63    pub performance_history: Vec<PerformanceSnapshot>,
64    pub target_platform: String,
65    pub constraints: OptimizationConstraints,
66    pub objectives: Vec<OptimizationObjective>,
67}
68
69/// Performance snapshot
70#[derive(Debug, Clone)]
71pub struct PerformanceSnapshot {
72    pub timestamp: SystemTime,
73    pub parameters: HashMap<String, f64>,
74    pub metrics: HashMap<String, f64>,
75    pub resource_usage: ResourceUsage,
76    pub execution_context: ExecutionContext,
77}
78
79/// Execution context
80#[derive(Debug, Clone)]
81pub struct ExecutionContext {
82    pub platform: String,
83    pub hardware_specs: HashMap<String, String>,
84    pub problem_size: usize,
85    pub noise_level: f64,
86    pub environmental_conditions: HashMap<String, f64>,
87}
88
89/// Optimization constraints
90#[derive(Debug, Clone)]
91pub struct OptimizationConstraints {
92    pub parameter_bounds: HashMap<String, (f64, f64)>,
93    pub resource_limits: ResourceLimits,
94    pub performance_requirements: PerformanceRequirements,
95    pub platform_constraints: Vec<String>,
96    pub time_constraints: Duration,
97}
98
99/// Optimization objectives
100#[derive(Debug, Clone)]
101pub struct OptimizationObjective {
102    pub metric_name: String,
103    pub objective_type: ObjectiveType,
104    pub weight: f64,
105    pub target_value: Option<f64>,
106}
107
108/// Objective types
109#[derive(Debug, Clone, PartialEq)]
110pub enum ObjectiveType {
111    Minimize,
112    Maximize,
113    Target,
114    Constraint,
115}
116
117/// Optimization result
118#[derive(Debug, Clone)]
119pub struct OptimizationResult {
120    pub success: bool,
121    pub optimized_parameters: HashMap<String, f64>,
122    pub performance_improvement: f64,
123    pub iterations_used: usize,
124    pub time_taken: Duration,
125    pub cost_incurred: f64,
126    pub convergence_info: ConvergenceInfo,
127    pub recommendations: Vec<OptimizationRecommendation>,
128}
129
130/// Convergence information
131#[derive(Debug, Clone)]
132pub struct ConvergenceInfo {
133    pub converged: bool,
134    pub final_objective_value: f64,
135    pub improvement_rate: f64,
136    pub convergence_criteria_met: Vec<String>,
137    pub optimization_trajectory: Vec<IterationSnapshot>,
138}
139
140/// Iteration snapshot
141#[derive(Debug, Clone)]
142pub struct IterationSnapshot {
143    pub iteration: usize,
144    pub parameters: HashMap<String, f64>,
145    pub objective_value: f64,
146    pub constraint_violations: Vec<ConstraintViolation>,
147    pub step_size: f64,
148}
149
150/// Constraint violation
151#[derive(Debug, Clone)]
152pub struct ConstraintViolation {
153    pub constraint_name: String,
154    pub violation_magnitude: f64,
155    pub tolerance: f64,
156}
157
158/// Optimization recommendation
159#[derive(Debug, Clone)]
160pub struct OptimizationRecommendation {
161    pub recommendation_type: RecommendationType,
162    pub description: String,
163    pub expected_benefit: f64,
164    pub implementation_effort: ImplementationEffort,
165    pub confidence: f64,
166}
167
168/// Recommendation types
169#[derive(Debug, Clone, PartialEq)]
170pub enum RecommendationType {
171    ParameterAdjustment,
172    AlgorithmVariant,
173    PlatformChange,
174    ResourceReallocation,
175    PreprocessingStep,
176    PostprocessingStep,
177}
178
179/// Implementation effort
180#[derive(Debug, Clone, PartialEq)]
181pub enum ImplementationEffort {
182    Low,
183    Medium,
184    High,
185    VeryHigh,
186}
187
188/// Performance analyzer
189pub struct PerformanceAnalyzer {
190    analysis_methods: Vec<Box<dyn PerformanceAnalysisMethod + Send + Sync>>,
191    benchmark_database: BenchmarkDatabase,
192    performance_models: Vec<PerformanceModel>,
193}
194
195/// Performance analysis method trait
196pub trait PerformanceAnalysisMethod {
197    fn analyze(&self, data: &[PerformanceSnapshot]) -> DeviceResult<PerformanceAnalysis>;
198    fn get_method_name(&self) -> String;
199}
200
201/// Performance analysis
202#[derive(Debug, Clone)]
203pub struct PerformanceAnalysis {
204    pub bottlenecks: Vec<PerformanceBottleneck>,
205    pub trends: Vec<PerformanceTrend>,
206    pub anomalies: Vec<PerformanceAnomaly>,
207    pub suggestions: Vec<PerformanceSuggestion>,
208}
209
210/// Performance bottleneck
211#[derive(Debug, Clone)]
212pub struct PerformanceBottleneck {
213    pub bottleneck_type: BottleneckType,
214    pub severity: f64,
215    pub affected_metrics: Vec<String>,
216    pub root_cause: String,
217    pub resolution_suggestions: Vec<String>,
218}
219
220/// Bottleneck types
221#[derive(Debug, Clone, PartialEq)]
222pub enum BottleneckType {
223    ComputeBottleneck,
224    MemoryBottleneck,
225    NetworkBottleneck,
226    QuantumResourceBottleneck,
227    AlgorithmicBottleneck,
228}
229
230/// Performance trend
231#[derive(Debug, Clone)]
232pub struct PerformanceTrend {
233    pub metric: String,
234    pub trend_direction: TrendDirection,
235    pub trend_strength: f64,
236    pub statistical_significance: f64,
237    pub projected_evolution: Vec<(Duration, f64)>,
238}
239
240/// Performance anomaly
241#[derive(Debug, Clone)]
242pub struct PerformanceAnomaly {
243    pub anomaly_type: AnomalyType,
244    pub detection_time: SystemTime,
245    pub severity: f64,
246    pub affected_metrics: Vec<String>,
247    pub potential_causes: Vec<String>,
248}
249
250/// Anomaly types
251#[derive(Debug, Clone, PartialEq)]
252pub enum AnomalyType {
253    SuddenDegradation,
254    GradualDecline,
255    UnexpectedImprovement,
256    PeriodicFluctuation,
257    OutlierBehavior,
258}
259
260/// Performance suggestion
261#[derive(Debug, Clone)]
262pub struct PerformanceSuggestion {
263    pub suggestion_type: SuggestionType,
264    pub description: String,
265    pub expected_improvement: f64,
266    pub implementation_complexity: f64,
267    pub confidence: f64,
268}
269
270/// Suggestion types
271#[derive(Debug, Clone, PartialEq)]
272pub enum SuggestionType {
273    ParameterTuning,
274    AlgorithmModification,
275    ResourceReallocation,
276    PlatformOptimization,
277    WorkflowImprovement,
278}
279
280/// Benchmark database
281pub struct BenchmarkDatabase {
282    benchmarks: HashMap<String, AlgorithmBenchmark>,
283    performance_baselines: HashMap<String, PerformanceBaseline>,
284    comparison_metrics: Vec<ComparisonMetric>,
285}
286
287/// Algorithm benchmark
288#[derive(Debug, Clone)]
289pub struct AlgorithmBenchmark {
290    pub benchmark_id: String,
291    pub algorithm_type: AlgorithmCategory,
292    pub problem_instances: Vec<ProblemInstance>,
293    pub reference_implementations: Vec<ReferenceImplementation>,
294    pub performance_targets: HashMap<String, f64>,
295}
296
297/// Problem instance
298#[derive(Debug, Clone)]
299pub struct ProblemInstance {
300    pub instance_id: String,
301    pub problem_size: usize,
302    pub difficulty_level: DifficultyLevel,
303    pub instance_characteristics: HashMap<String, f64>,
304    pub optimal_solution: Option<Solution>,
305}
306
307/// Difficulty levels
308#[derive(Debug, Clone, PartialEq)]
309pub enum DifficultyLevel {
310    Trivial,
311    Easy,
312    Medium,
313    Hard,
314    Extreme,
315}
316
317/// Solution
318#[derive(Debug, Clone)]
319pub struct Solution {
320    pub solution_quality: f64,
321    pub computation_time: Duration,
322    pub resource_requirements: ResourceRequirements,
323    pub verification_status: bool,
324}
325
326/// Reference implementation
327#[derive(Debug, Clone)]
328pub struct ReferenceImplementation {
329    pub implementation_id: String,
330    pub platform: String,
331    pub algorithm_variant: String,
332    pub performance_characteristics: HashMap<String, f64>,
333    pub implementation_notes: String,
334}
335
336/// Performance baseline
337#[derive(Debug, Clone)]
338pub struct PerformanceBaseline {
339    pub baseline_id: String,
340    pub algorithm_type: AlgorithmCategory,
341    pub platform: String,
342    pub baseline_metrics: HashMap<String, f64>,
343    pub confidence_intervals: HashMap<String, (f64, f64)>,
344    pub measurement_conditions: MeasurementConditions,
345}
346
347/// Measurement conditions
348#[derive(Debug, Clone)]
349pub struct MeasurementConditions {
350    pub measurement_date: SystemTime,
351    pub hardware_configuration: HashMap<String, String>,
352    pub software_versions: HashMap<String, String>,
353    pub environmental_factors: HashMap<String, f64>,
354}
355
356/// Comparison metric
357#[derive(Debug, Clone)]
358pub struct ComparisonMetric {
359    pub metric_name: String,
360    pub metric_type: MetricType,
361    pub normalization_method: NormalizationMethod,
362    pub aggregation_method: AggregationMethod,
363}
364
365/// Normalization methods
366#[derive(Debug, Clone, PartialEq)]
367pub enum NormalizationMethod {
368    None,
369    ZScore,
370    MinMax,
371    Percentile,
372    Custom(String),
373}
374
375/// Aggregation methods
376#[derive(Debug, Clone, PartialEq)]
377pub enum AggregationMethod {
378    Mean,
379    Median,
380    WeightedAverage,
381    GeometricMean,
382    HarmonicMean,
383}
384
385/// Performance model
386#[derive(Debug, Clone)]
387pub struct PerformanceModel {
388    pub model_id: String,
389    pub model_type: PerformanceModelType,
390    pub input_features: Vec<String>,
391    pub output_metrics: Vec<String>,
392    pub model_parameters: Vec<f64>,
393    pub accuracy_metrics: HashMap<String, f64>,
394    pub training_data: ModelTrainingData,
395}
396
397/// Performance model types
398#[derive(Debug, Clone, PartialEq)]
399pub enum PerformanceModelType {
400    LinearRegression,
401    PolynomialRegression,
402    RandomForest,
403    NeuralNetwork,
404    GaussianProcess,
405    Custom(String),
406}
407
408/// Model training data
409#[derive(Debug, Clone)]
410pub struct ModelTrainingData {
411    pub training_set_size: usize,
412    pub validation_set_size: usize,
413    pub feature_ranges: HashMap<String, (f64, f64)>,
414    pub training_time: Duration,
415    pub last_updated: SystemTime,
416}
417
418/// Parameter optimizer
419pub struct ParameterOptimizer {
420    optimization_algorithms: Vec<Box<dyn ParameterOptimizationAlgorithm + Send + Sync>>,
421    parameter_space: ParameterSpace,
422    optimization_history: Vec<OptimizationRun>,
423}
424
425/// Parameter optimization algorithm trait
426pub trait ParameterOptimizationAlgorithm {
427    fn optimize(
428        &self,
429        objective: &ObjectiveFunction,
430        space: &ParameterSpace,
431        budget: &OptimizationBudget,
432    ) -> DeviceResult<OptimizationResult>;
433    fn get_algorithm_name(&self) -> String;
434    fn supports_constraints(&self) -> bool;
435}
436
437/// Objective function
438pub struct ObjectiveFunction {
439    pub function_type: ObjectiveFunctionType,
440    pub evaluation_method: EvaluationMethod,
441    pub noise_level: f64,
442    pub computational_cost: ComputationalCost,
443}
444
445/// Objective function types
446#[derive(Debug, Clone, PartialEq)]
447pub enum ObjectiveFunctionType {
448    SingleObjective,
449    MultiObjective,
450    ConstrainedOptimization,
451    RobustOptimization,
452}
453
454/// Evaluation methods
455#[derive(Debug, Clone, PartialEq)]
456pub enum EvaluationMethod {
457    DirectEvaluation,
458    SimulationBased,
459    ModelBased,
460    HybridApproach,
461}
462
463/// Computational cost
464#[derive(Debug, Clone)]
465pub struct ComputationalCost {
466    pub cost_per_evaluation: f64,
467    pub evaluation_time: Duration,
468    pub resource_requirements: ResourceRequirements,
469    pub parallelization_factor: f64,
470}
471
472/// Parameter space
473#[derive(Debug, Clone)]
474pub struct ParameterSpace {
475    pub dimensions: Vec<ParameterDimension>,
476    pub constraints: Vec<ParameterConstraint>,
477    pub prior_knowledge: Option<PriorKnowledge>,
478}
479
480/// Parameter dimension
481#[derive(Debug, Clone)]
482pub struct ParameterDimension {
483    pub name: String,
484    pub dimension_type: DimensionType,
485    pub bounds: ParameterBounds,
486    pub initial_value: Option<f64>,
487    pub importance: f64,
488}
489
490/// Dimension types
491#[derive(Debug, Clone, PartialEq)]
492pub enum DimensionType {
493    Continuous,
494    Discrete,
495    Categorical,
496    Ordinal,
497}
498
499/// Parameter bounds
500#[derive(Debug, Clone)]
501pub enum ParameterBounds {
502    Continuous(f64, f64),
503    Discrete(Vec<i64>),
504    Categorical(Vec<String>),
505    Ordinal(Vec<String>),
506}
507
508/// Parameter constraint
509#[derive(Debug, Clone)]
510pub struct ParameterConstraint {
511    pub constraint_type: ConstraintType,
512    pub parameters: Vec<String>,
513    pub constraint_function: String,
514    pub tolerance: f64,
515}
516
517/// Constraint types
518#[derive(Debug, Clone, PartialEq)]
519pub enum ConstraintType {
520    Equality,
521    Inequality,
522    Box,
523    Linear,
524    Nonlinear,
525}
526
527/// Prior knowledge
528#[derive(Debug, Clone)]
529pub struct PriorKnowledge {
530    pub known_good_regions: Vec<ParameterRegion>,
531    pub known_bad_regions: Vec<ParameterRegion>,
532    pub parameter_correlations: HashMap<(String, String), f64>,
533    pub sensitivity_information: HashMap<String, f64>,
534}
535
536/// Parameter region
537#[derive(Debug, Clone)]
538pub struct ParameterRegion {
539    pub region_bounds: HashMap<String, (f64, f64)>,
540    pub quality_estimate: f64,
541    pub confidence: f64,
542}
543
544/// Optimization run
545#[derive(Debug, Clone)]
546pub struct OptimizationRun {
547    pub run_id: String,
548    pub algorithm_used: String,
549    pub start_time: SystemTime,
550    pub end_time: SystemTime,
551    pub iterations: usize,
552    pub best_parameters: HashMap<String, f64>,
553    pub best_objective_value: f64,
554    pub convergence_history: Vec<ConvergencePoint>,
555}
556
557/// Convergence point
558#[derive(Debug, Clone)]
559pub struct ConvergencePoint {
560    pub iteration: usize,
561    pub objective_value: f64,
562    pub parameters: HashMap<String, f64>,
563    pub improvement: f64,
564}
565
566/// Resource optimizer
567pub struct ResourceOptimizer {
568    resource_allocation_strategies: Vec<Box<dyn ResourceAllocationStrategy + Send + Sync>>,
569    resource_models: Vec<ResourceModel>,
570    cost_models: Vec<CostModel>,
571}
572
573/// Resource allocation strategy trait
574pub trait ResourceAllocationStrategy {
575    fn allocate(
576        &self,
577        requirements: &ResourceRequirements,
578        available: &[AvailableResources],
579    ) -> DeviceResult<ResourceAllocation>;
580    fn get_strategy_name(&self) -> String;
581}
582
583/// Resource model
584#[derive(Debug, Clone)]
585pub struct ResourceModel {
586    pub model_id: String,
587    pub resource_type: String,
588    pub utilization_model: UtilizationModel,
589    pub performance_impact: PerformanceImpactModel,
590    pub cost_model: ResourceCostModel,
591}
592
593/// Utilization model
594#[derive(Debug, Clone)]
595pub struct UtilizationModel {
596    pub base_utilization: f64,
597    pub scaling_factors: HashMap<String, f64>,
598    pub utilization_bounds: (f64, f64),
599    pub efficiency_curve: Vec<(f64, f64)>,
600}
601
602/// Performance impact model
603#[derive(Debug, Clone)]
604pub struct PerformanceImpactModel {
605    pub impact_metrics: HashMap<String, f64>,
606    pub bottleneck_thresholds: HashMap<String, f64>,
607    pub scaling_relationships: Vec<ScalingRelationship>,
608}
609
610/// Scaling relationship
611#[derive(Debug, Clone)]
612pub struct ScalingRelationship {
613    pub input_resource: String,
614    pub output_metric: String,
615    pub relationship_type: RelationshipType,
616    pub parameters: Vec<f64>,
617}
618
619/// Relationship types
620#[derive(Debug, Clone, PartialEq)]
621pub enum RelationshipType {
622    Linear,
623    Logarithmic,
624    Exponential,
625    Power,
626    Custom(String),
627}
628
629/// Resource cost model
630#[derive(Debug, Clone)]
631pub struct ResourceCostModel {
632    pub cost_structure: CostStructure,
633    pub pricing_tiers: Vec<PricingTier>,
634    pub discount_factors: HashMap<String, f64>,
635    pub cost_optimization_rules: Vec<CostOptimizationRule>,
636}
637
638/// Cost structure
639#[derive(Debug, Clone)]
640pub struct CostStructure {
641    pub fixed_costs: f64,
642    pub variable_costs: HashMap<String, f64>,
643    pub tiered_pricing: bool,
644    pub volume_discounts: bool,
645}
646
647/// Pricing tier
648#[derive(Debug, Clone)]
649pub struct PricingTier {
650    pub tier_name: String,
651    pub usage_threshold: f64,
652    pub price_per_unit: f64,
653    pub included_quota: f64,
654}
655
656/// Cost optimization rule
657#[derive(Debug, Clone)]
658pub struct CostOptimizationRule {
659    pub rule_name: String,
660    pub condition: String,
661    pub action: String,
662    pub expected_savings: f64,
663}
664
665/// Cost model
666#[derive(Debug, Clone)]
667pub struct CostModel {
668    pub model_id: String,
669    pub cost_components: Vec<CostComponent>,
670    pub optimization_objectives: Vec<CostOptimizationObjective>,
671    pub budget_constraints: BudgetConstraints,
672}
673
674/// Cost component
675#[derive(Debug, Clone)]
676pub struct CostComponent {
677    pub component_name: String,
678    pub cost_type: CostType,
679    pub cost_function: String,
680    pub parameters: HashMap<String, f64>,
681}
682
683/// Cost types
684#[derive(Debug, Clone, PartialEq)]
685pub enum CostType {
686    Fixed,
687    Variable,
688    StepFunction,
689    Tiered,
690    UsageBased,
691}
692
693/// Cost optimization objective
694#[derive(Debug, Clone)]
695pub struct CostOptimizationObjective {
696    pub objective_name: String,
697    pub target_metric: String,
698    pub optimization_direction: ObjectiveType,
699    pub weight: f64,
700}
701
702/// Budget constraints
703#[derive(Debug, Clone)]
704pub struct BudgetConstraints {
705    pub total_budget: f64,
706    pub time_horizon: Duration,
707    pub budget_allocation: HashMap<String, f64>,
708    pub cost_limits: HashMap<String, f64>,
709}
710
711impl AlgorithmOptimizationEngine {
712    /// Create a new optimization engine
713    pub fn new(config: &OptimizationConfig) -> DeviceResult<Self> {
714        Ok(Self {
715            config: config.clone(),
716            optimization_strategies: vec![],
717            performance_analyzer: PerformanceAnalyzer::new()?,
718            parameter_optimizer: ParameterOptimizer::new()?,
719            resource_optimizer: ResourceOptimizer::new()?,
720        })
721    }
722
723    /// Initialize the optimization engine
724    pub async fn initialize(&self) -> DeviceResult<()> {
725        // Initialize optimization components
726        Ok(())
727    }
728}
729
730impl PerformanceAnalyzer {
731    fn new() -> DeviceResult<Self> {
732        Ok(Self {
733            analysis_methods: vec![],
734            benchmark_database: BenchmarkDatabase::new(),
735            performance_models: vec![],
736        })
737    }
738}
739
740impl BenchmarkDatabase {
741    fn new() -> Self {
742        Self {
743            benchmarks: HashMap::new(),
744            performance_baselines: HashMap::new(),
745            comparison_metrics: vec![],
746        }
747    }
748}
749
750impl ParameterOptimizer {
751    fn new() -> DeviceResult<Self> {
752        Ok(Self {
753            optimization_algorithms: vec![],
754            parameter_space: ParameterSpace {
755                dimensions: vec![],
756                constraints: vec![],
757                prior_knowledge: None,
758            },
759            optimization_history: vec![],
760        })
761    }
762}
763
764impl ResourceOptimizer {
765    fn new() -> DeviceResult<Self> {
766        Ok(Self {
767            resource_allocation_strategies: vec![],
768            resource_models: vec![],
769            cost_models: vec![],
770        })
771    }
772}
773
774impl Default for OptimizationConfig {
775    fn default() -> Self {
776        Self {
777            enabled: true,
778            optimization_level: OptimizationLevel::Basic,
779            target_metrics: vec![
780                "execution_time".to_string(),
781                "resource_efficiency".to_string(),
782                "accuracy".to_string(),
783            ],
784            optimization_budget: OptimizationBudget {
785                max_iterations: 100,
786                max_time: Duration::from_secs(3600),
787                max_cost: 1000.0,
788                max_resource_usage: 0.8,
789            },
790            parallel_optimization: true,
791            caching_enabled: true,
792        }
793    }
794}
quantrs2_device/algorithm_marketplace/optimization.rs

quantrs2_device/algorithm_marketplace/
optimization.rs
