scirs2_graph/advanced/
mod.rs

1//! Advanced Mode Integration for Graph Processing
2//!
3//! This module provides cutting-edge optimization capabilities by integrating
4//! neural reinforcement learning, GPU acceleration, neuromorphic computing,
5//! and real-time adaptive optimization for graph algorithms.
6
7use crate::base::{EdgeWeight, Graph, Node};
8use crate::error::Result;
9/// Simplified performance monitoring for graph operations
10#[derive(Debug, Clone, Default)]
11pub struct SimplePerformanceMonitor {
12    operations: HashMap<String, f64>,
13}
14
15impl SimplePerformanceMonitor {
16    /// Create a new performance monitor
17    pub fn new() -> Self {
18        Self::default()
19    }
20
21    /// Start monitoring an operation
22    pub fn start_operation(&mut self, _name: &str) {
23        // Placeholder implementation
24    }
25
26    /// Stop monitoring an operation
27    pub fn stop_operation(&mut self, _name: &str) {
28        // Placeholder implementation
29    }
30
31    /// Get performance report
32    pub fn get_report(&self) -> SimplePerformanceReport {
33        SimplePerformanceReport::default()
34    }
35}
36
37/// Performance report for monitored operations
38#[derive(Debug, Clone, Default)]
39pub struct SimplePerformanceReport {
40    /// Total number of operations executed
41    pub total_operations: usize,
42    /// Total time spent in milliseconds
43    pub total_time_ms: f64,
44}
45use scirs2_core::random::Rng;
46use std::collections::{HashMap, VecDeque};
47
48/// Advanced mode configuration for graph processing
49#[derive(Debug, Clone)]
50pub struct AdvancedConfig {
51    /// Enable neural RL-based algorithm selection
52    pub enable_neural_rl: bool,
53    /// Enable GPU advanced-acceleration
54    pub enable_gpu_acceleration: bool,
55    /// Enable neuromorphic computing features
56    pub enable_neuromorphic: bool,
57    /// Enable real-time performance adaptation
58    pub enable_realtime_adaptation: bool,
59    /// Enable advanced memory optimization
60    pub enable_memory_optimization: bool,
61    /// Learning rate for adaptive algorithms
62    pub learning_rate: f64,
63    /// Memory optimization threshold (MB)
64    pub memory_threshold_mb: usize,
65    /// GPU memory pool size (MB)
66    pub gpu_memory_pool_mb: usize,
67    /// Neural network hidden layer size
68    pub neural_hidden_size: usize,
69}
70
71impl Default for AdvancedConfig {
72    fn default() -> Self {
73        AdvancedConfig {
74            enable_neural_rl: true,
75            enable_gpu_acceleration: true,
76            enable_neuromorphic: true,
77            enable_realtime_adaptation: true,
78            enable_memory_optimization: true,
79            learning_rate: 0.001,
80            memory_threshold_mb: 1024,
81            gpu_memory_pool_mb: 2048,
82            neural_hidden_size: 128,
83        }
84    }
85}
86
87/// Advanced exploration strategies for neural RL
88#[derive(Debug, Clone)]
89pub enum ExplorationStrategy {
90    /// Standard epsilon-greedy exploration
91    EpsilonGreedy {
92        /// Exploration probability parameter
93        epsilon: f64,
94    },
95    /// Upper confidence bound exploration
96    UCB {
97        /// Confidence parameter for UCB
98        c: f64,
99    },
100    /// Thompson sampling exploration
101    ThompsonSampling {
102        /// Alpha parameter for beta distribution
103        alpha: f64,
104        /// Beta parameter for beta distribution
105        beta: f64,
106    },
107    /// Adaptive exploration based on uncertainty
108    AdaptiveUncertainty {
109        /// Uncertainty threshold for adaptive exploration
110        uncertainty_threshold: f64,
111    },
112}
113
114impl Default for ExplorationStrategy {
115    fn default() -> Self {
116        ExplorationStrategy::EpsilonGreedy { epsilon: 0.1 }
117    }
118}
119
120/// Simplified Advanced Processing Structure
121pub struct AdvancedProcessor {
122    config: AdvancedConfig,
123    performance_monitor: SimplePerformanceMonitor,
124}
125
126impl AdvancedProcessor {
127    /// Create a new advanced processor
128    pub fn new(config: AdvancedConfig) -> Self {
129        AdvancedProcessor {
130            config,
131            performance_monitor: SimplePerformanceMonitor::new(),
132        }
133    }
134
135    /// Execute advanced graph processing
136    pub fn execute<N, E, Ix, T, F>(&mut self, graph: &Graph<N, E, Ix>, operation: F) -> Result<T>
137    where
138        N: Node,
139        E: EdgeWeight,
140        Ix: petgraph::graph::IndexType,
141        F: FnOnce(&Graph<N, E, Ix>) -> Result<T>,
142    {
143        // Start performance monitoring
144        self.performance_monitor
145            .start_operation("advanced_execution");
146
147        // Execute the operation
148        let result = operation(graph);
149
150        // Stop performance monitoring
151        self.performance_monitor
152            .stop_operation("advanced_execution");
153
154        result
155    }
156
157    /// Get performance report
158    pub fn get_performance_report(&self) -> SimplePerformanceReport {
159        self.performance_monitor.get_report()
160    }
161
162    /// Get optimization statistics
163    pub fn get_optimization_stats(&self) -> AdvancedStats {
164        AdvancedStats::default()
165    }
166}
167
168/// Advanced statistics for graph processing
169#[derive(Debug, Clone)]
170pub struct AdvancedStats {
171    /// Total operations executed
172    pub total_operations: usize,
173    /// Average execution time in milliseconds
174    pub avg_execution_time_ms: f64,
175    /// Memory usage in bytes
176    pub memory_usage_bytes: usize,
177    /// GPU utilization percentage
178    pub gpu_utilization_percent: f64,
179    /// Memory efficiency score (0.0 to 1.0)
180    pub memory_efficiency: f64,
181}
182
183impl Default for AdvancedStats {
184    fn default() -> Self {
185        AdvancedStats {
186            total_operations: 0,
187            avg_execution_time_ms: 0.0,
188            memory_usage_bytes: 0,
189            gpu_utilization_percent: 0.0,
190            memory_efficiency: 1.0,
191        }
192    }
193}
194
195// Factory functions for different processor configurations
196/// Create a standard advanced processor
197pub fn create_advanced_processor() -> AdvancedProcessor {
198    AdvancedProcessor::new(AdvancedConfig::default())
199}
200
201/// Create an enhanced advanced processor with optimized settings
202pub fn create_enhanced_advanced_processor() -> AdvancedProcessor {
203    let mut config = AdvancedConfig::default();
204    config.neural_hidden_size = 256;
205    config.gpu_memory_pool_mb = 4096;
206    AdvancedProcessor::new(config)
207}
208
209/// Execute operation with standard advanced processing
210pub fn execute_with_advanced<N, E, Ix, T>(
211    graph: &Graph<N, E, Ix>,
212    operation: impl FnOnce(&Graph<N, E, Ix>) -> Result<T>,
213) -> Result<T>
214where
215    N: Node,
216    E: EdgeWeight,
217    Ix: petgraph::graph::IndexType,
218{
219    let mut processor = create_advanced_processor();
220    processor.execute(graph, operation)
221}
222
223/// Execute operation with enhanced advanced processing
224pub fn execute_with_enhanced_advanced<N, E, Ix, T>(
225    graph: &Graph<N, E, Ix>,
226    operation: impl FnOnce(&Graph<N, E, Ix>) -> Result<T>,
227) -> Result<T>
228where
229    N: Node,
230    E: EdgeWeight,
231    Ix: petgraph::graph::IndexType,
232{
233    let mut processor = create_enhanced_advanced_processor();
234    processor.execute(graph, operation)
235}
236
237/// Create a processor optimized for large graphs
238pub fn create_large_graph_advanced_processor() -> AdvancedProcessor {
239    let mut config = AdvancedConfig::default();
240    config.memory_threshold_mb = 8192;
241    config.gpu_memory_pool_mb = 8192;
242    config.enable_memory_optimization = true;
243    AdvancedProcessor::new(config)
244}
245
246/// Create a processor optimized for real-time processing
247pub fn create_realtime_advanced_processor() -> AdvancedProcessor {
248    let mut config = AdvancedConfig::default();
249    config.enable_realtime_adaptation = true;
250    config.learning_rate = 0.01;
251    AdvancedProcessor::new(config)
252}
253
254/// Create a processor optimized for performance
255pub fn create_performance_advanced_processor() -> AdvancedProcessor {
256    let mut config = AdvancedConfig::default();
257    config.enable_gpu_acceleration = true;
258    config.enable_neuromorphic = true;
259    config.gpu_memory_pool_mb = 16384;
260    AdvancedProcessor::new(config)
261}
262
263/// Create a processor optimized for memory efficiency
264pub fn create_memory_efficient_advanced_processor() -> AdvancedProcessor {
265    let mut config = AdvancedConfig::default();
266    config.enable_memory_optimization = true;
267    config.memory_threshold_mb = 512;
268    config.gpu_memory_pool_mb = 1024;
269    AdvancedProcessor::new(config)
270}
271
272/// Create an adaptive processor that adjusts based on workload
273pub fn create_adaptive_advanced_processor() -> AdvancedProcessor {
274    let mut config = AdvancedConfig::default();
275    config.enable_realtime_adaptation = true;
276    config.enable_neural_rl = true;
277    config.learning_rate = 0.005;
278    AdvancedProcessor::new(config)
279}
280
281// Placeholder structures for backward compatibility
282/// Algorithm performance metrics
283#[derive(Debug, Clone)]
284pub struct AlgorithmMetrics {
285    /// Algorithm name
286    pub algorithm_name: String,
287    /// Execution time in milliseconds
288    pub execution_time_ms: f64,
289    /// Memory usage in bytes
290    pub memory_usage_bytes: usize,
291}
292
293impl Default for AlgorithmMetrics {
294    fn default() -> Self {
295        AlgorithmMetrics {
296            algorithm_name: String::new(),
297            execution_time_ms: 0.0,
298            memory_usage_bytes: 0,
299        }
300    }
301}
302
303/// GPU acceleration context for advanced operations
304#[derive(Debug, Default)]
305pub struct GPUAccelerationContext {
306    /// Whether GPU is available
307    pub gpu_available: bool,
308    /// GPU memory pool size
309    pub memory_pool_size: usize,
310}
311
312/// Neural reinforcement learning agent
313#[derive(Debug)]
314pub struct NeuralRLAgent {
315    /// Agent configuration
316    pub config: AdvancedConfig,
317    /// Learning rate
318    pub learning_rate: f64,
319}
320
321impl Default for NeuralRLAgent {
322    fn default() -> Self {
323        NeuralRLAgent {
324            config: AdvancedConfig::default(),
325            learning_rate: 0.001,
326        }
327    }
328}
329
330/// Neuromorphic processor for brain-inspired computing
331#[derive(Debug)]
332pub struct NeuromorphicProcessor {
333    /// Number of neurons
334    pub num_neurons: usize,
335    /// Number of synapses
336    pub num_synapses: usize,
337}
338
339impl Default for NeuromorphicProcessor {
340    fn default() -> Self {
341        NeuromorphicProcessor {
342            num_neurons: 1000,
343            num_synapses: 10000,
344        }
345    }
346}
scirs2_graph/advanced/mod.rs

scirs2_graph/advanced/
mod.rs
