comprehensive_benchmarking_demo/
comprehensive_benchmarking_demo.rs

1//! Comprehensive Benchmarking Framework Example
2//!
3//! This example demonstrates the benchmarking framework for comparing quantum ML models
4//! across different algorithms, hardware backends, and problem sizes.
5
6use quantrs2_ml::benchmarking::algorithm_benchmarks::{QAOABenchmark, QNNBenchmark, VQEBenchmark};
7use quantrs2_ml::benchmarking::benchmark_utils::create_benchmark_backends;
8use quantrs2_ml::benchmarking::{Benchmark, BenchmarkConfig, BenchmarkFramework, BenchmarkResults};
9use quantrs2_ml::prelude::*;
10use quantrs2_ml::simulator_backends::Backend;
11use std::time::Duration;
12
13// Placeholder type for missing BenchmarkContext
14#[derive(Debug, Clone)]
15pub struct BenchmarkContext {
16    pub config: String,
17}
18
19impl Default for BenchmarkContext {
20    fn default() -> Self {
21        Self::new()
22    }
23}
24
25impl BenchmarkContext {
26    #[must_use]
27    pub fn new() -> Self {
28        Self {
29            config: "default".to_string(),
30        }
31    }
32}
33
34fn main() -> Result<()> {
35    println!("=== Comprehensive Quantum ML Benchmarking Demo ===\n");
36
37    // Step 1: Initialize benchmarking framework
38    println!("1. Initializing benchmarking framework...");
39
40    let config = BenchmarkConfig {
41        repetitions: 3,
42        warmup_runs: 1,
43        max_time_per_benchmark: 60.0, // 1 minute per benchmark
44        profile_memory: true,
45        analyze_convergence: true,
46        confidence_level: 0.95,
47        ..Default::default()
48    };
49
50    let mut framework = BenchmarkFramework::new().with_config(config);
51
52    println!("   - Framework initialized");
53    println!("   - Output directory: benchmark_results/");
54    println!("   - Repetitions per benchmark: 3");
55
56    // Step 2: Register benchmarks
57    println!("\n2. Registering benchmarks...");
58
59    // VQE benchmarks for different qubit counts
60    framework.register_benchmark("vqe_4q", Box::new(VQEBenchmark::new(4, 8)));
61    framework.register_benchmark("vqe_6q", Box::new(VQEBenchmark::new(6, 12)));
62    framework.register_benchmark("vqe_8q", Box::new(VQEBenchmark::new(8, 16)));
63
64    // QAOA benchmarks
65    framework.register_benchmark("qaoa_4q", Box::new(QAOABenchmark::new(4, 2, 8)));
66    framework.register_benchmark("qaoa_6q", Box::new(QAOABenchmark::new(6, 3, 12)));
67
68    // QNN benchmarks
69    framework.register_benchmark("qnn_4q", Box::new(QNNBenchmark::new(4, 2, 100)));
70    framework.register_benchmark("qnn_6q", Box::new(QNNBenchmark::new(6, 3, 100)));
71
72    println!("   - Registered 7 benchmarks total");
73
74    // Step 3: Create backend configurations
75    println!("\n3. Setting up backends...");
76
77    let backends = create_benchmark_backends();
78    let backend_refs: Vec<&Backend> = backends.iter().collect();
79
80    println!("   - Created {} backends", backends.len());
81    for backend in &backends {
82        println!("     - {}", backend.name());
83    }
84
85    // Step 4: Run all benchmarks
86    println!("\n4. Running all benchmarks...");
87
88    framework.run_all_benchmarks(&backend_refs)?;
89
90    println!("   - All benchmarks completed");
91
92    // Step 5: Generate and display report
93    println!("\n5. Generating benchmark report...");
94
95    let report = framework.generate_report();
96    println!("\n{}", report.to_string());
97
98    // Step 6: Print detailed results
99    println!("\n6. Detailed Results Analysis:");
100
101    // Get results again for analysis since we can't hold onto the reference
102    let results = framework.run_all_benchmarks(&backend_refs)?;
103    print_performance_summary(results);
104    print_scaling_analysis(results);
105    print_memory_analysis(results);
106
107    println!("\n=== Comprehensive Benchmarking Demo Complete ===");
108
109    Ok(())
110}
111
112fn print_performance_summary(results: &BenchmarkResults) {
113    println!("\n   Performance Summary:");
114    println!("   ===================");
115
116    // Print summaries for each benchmark
117    for (name, summary) in results.summaries() {
118        println!("   {name}:");
119        println!("     - Mean time: {:.3}s", summary.mean_time.as_secs_f64());
120        println!("     - Min time:  {:.3}s", summary.min_time.as_secs_f64());
121        println!("     - Max time:  {:.3}s", summary.max_time.as_secs_f64());
122        println!("     - Success rate: {:.1}%", summary.success_rate * 100.0);
123        if let Some(memory) = summary.mean_memory {
124            println!(
125                "     - Memory usage: {:.1} MB",
126                memory as f64 / 1024.0 / 1024.0
127            );
128        }
129        println!();
130    }
131}
132
133fn print_scaling_analysis(results: &BenchmarkResults) {
134    println!("   Scaling Analysis:");
135    println!("   =================");
136
137    // Group by algorithm type
138    let mut vqe_results = Vec::new();
139    let mut qaoa_results = Vec::new();
140    let mut qnn_results = Vec::new();
141
142    for (name, summary) in results.summaries() {
143        if name.starts_with("vqe_") {
144            vqe_results.push((name, summary));
145        } else if name.starts_with("qaoa_") {
146            qaoa_results.push((name, summary));
147        } else if name.starts_with("qnn_") {
148            qnn_results.push((name, summary));
149        }
150    }
151
152    // Analyze VQE scaling
153    if !vqe_results.is_empty() {
154        println!("   VQE Algorithm Scaling:");
155        vqe_results.sort_by_key(|(name, _)| (*name).to_string());
156        for (name, summary) in vqe_results {
157            let qubits = extract_qubit_count(name);
158            println!(
159                "     - {} qubits: {:.3}s",
160                qubits,
161                summary.mean_time.as_secs_f64()
162            );
163        }
164        println!("     - Scaling trend: Exponential (as expected for VQE)");
165        println!();
166    }
167
168    // Analyze QAOA scaling
169    if !qaoa_results.is_empty() {
170        println!("   QAOA Algorithm Scaling:");
171        qaoa_results.sort_by_key(|(name, _)| (*name).to_string());
172        for (name, summary) in qaoa_results {
173            let qubits = extract_qubit_count(name);
174            println!(
175                "     - {} qubits: {:.3}s",
176                qubits,
177                summary.mean_time.as_secs_f64()
178            );
179        }
180        println!("     - Scaling trend: Polynomial (as expected for QAOA)");
181        println!();
182    }
183
184    // Analyze QNN scaling
185    if !qnn_results.is_empty() {
186        println!("   QNN Algorithm Scaling:");
187        qnn_results.sort_by_key(|(name, _)| (*name).to_string());
188        for (name, summary) in qnn_results {
189            let qubits = extract_qubit_count(name);
190            println!(
191                "     - {} qubits: {:.3}s",
192                qubits,
193                summary.mean_time.as_secs_f64()
194            );
195        }
196        println!("     - Scaling trend: Polynomial (training overhead)");
197        println!();
198    }
199}
200
201fn print_memory_analysis(results: &BenchmarkResults) {
202    println!("   Memory Usage Analysis:");
203    println!("   =====================");
204
205    let mut memory_data = Vec::new();
206    for (name, summary) in results.summaries() {
207        if let Some(memory) = summary.mean_memory {
208            let qubits = extract_qubit_count(name);
209            memory_data.push((qubits, memory, name));
210        }
211    }
212
213    if !memory_data.is_empty() {
214        memory_data.sort_by_key(|(qubits, _, _)| *qubits);
215
216        println!("   Memory scaling by qubit count:");
217        for (qubits, memory, name) in memory_data {
218            println!(
219                "     - {} qubits ({}): {:.1} MB",
220                qubits,
221                name,
222                memory as f64 / 1024.0 / 1024.0
223            );
224        }
225        println!("     - Expected scaling: O(2^n) for statevector simulation");
226        println!();
227    }
228
229    // Print recommendations
230    println!("   Recommendations:");
231    println!("     - Use statevector backend for circuits ≤ 12 qubits");
232    println!("     - Use MPS backend for larger circuits with limited entanglement");
233    println!("     - Consider circuit optimization for memory-constrained environments");
234}
235
236fn extract_qubit_count(benchmark_name: &str) -> usize {
237    // Extract number from strings like "vqe_4q_statevector", "qaoa_6q_mps", etc.
238    for part in benchmark_name.split('_') {
239        if part.ends_with('q') {
240            if let Ok(num) = part.trim_end_matches('q').parse::<usize>() {
241                return num;
242            }
243        }
244    }
245    0 // Default if not found
246}
247
248// Additional analysis functions
249fn analyze_backend_performance(results: &BenchmarkResults) {
250    println!("   Backend Performance Comparison:");
251    println!("   ==============================");
252
253    // Group results by backend type
254    let mut backend_performance = std::collections::HashMap::new();
255
256    for (name, summary) in results.summaries() {
257        let backend_type = extract_backend_type(name);
258        backend_performance
259            .entry(backend_type)
260            .or_insert_with(Vec::new)
261            .push(summary.mean_time.as_secs_f64());
262    }
263
264    for (backend, times) in backend_performance {
265        let avg_time = times.iter().sum::<f64>() / times.len() as f64;
266        println!("     - {backend} backend: {avg_time:.3}s average");
267    }
268}
269
270fn extract_backend_type(benchmark_name: &str) -> &str {
271    if benchmark_name.contains("statevector") {
272        "Statevector"
273    } else if benchmark_name.contains("mps") {
274        "MPS"
275    } else if benchmark_name.contains("gpu") {
276        "GPU"
277    } else {
278        "Unknown"
279    }
280}
281
282// Test helper functions
283#[cfg(test)]
284mod tests {
285    use super::*;
286
287    #[test]
288    fn test_extract_qubit_count() {
289        assert_eq!(extract_qubit_count("vqe_4q_statevector"), 4);
290        assert_eq!(extract_qubit_count("qaoa_6q_mps"), 6);
291        assert_eq!(extract_qubit_count("qnn_8q_gpu"), 8);
292        assert_eq!(extract_qubit_count("unknown_format"), 0);
293    }
294
295    #[test]
296    fn test_extract_backend_type() {
297        assert_eq!(extract_backend_type("vqe_4q_statevector"), "Statevector");
298        assert_eq!(extract_backend_type("qaoa_6q_mps"), "MPS");
299        assert_eq!(extract_backend_type("qnn_8q_gpu"), "GPU");
300        assert_eq!(extract_backend_type("unknown_backend"), "Unknown");
301    }
302}
303
304// Placeholder functions to satisfy compilation errors
305fn create_algorithm_comparison_benchmarks() -> Result<Vec<Box<dyn Benchmark>>> {
306    let mut benchmarks = Vec::new();
307    Ok(benchmarks)
308}
309
310fn create_scaling_benchmarks() -> Result<Vec<Box<dyn Benchmark>>> {
311    let mut benchmarks = Vec::new();
312    Ok(benchmarks)
313}
314
315fn create_hardware_benchmarks() -> Result<Vec<Box<dyn Benchmark>>> {
316    let mut benchmarks = Vec::new();
317    Ok(benchmarks)
318}
319
320fn create_framework_benchmarks() -> Result<Vec<Box<dyn Benchmark>>> {
321    let mut benchmarks = Vec::new();
322    Ok(benchmarks)
323}
comprehensive_benchmarking_demo/comprehensive_benchmarking_demo.rs

comprehensive_benchmarking_demo/
comprehensive_benchmarking_demo.rs
