BenchmarkResults

Struct BenchmarkResults 

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pub struct BenchmarkResults { /* private fields */ }
Expand description

Aggregated benchmark results

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impl BenchmarkResults

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pub fn summaries(&self) -> &HashMap<String, BenchmarkSummary>

Get summaries

Examples found in repository?
examples/comprehensive_benchmarking_demo.rs (line 117)
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}
Source

pub fn results(&self) -> &HashMap<String, Vec<BenchmarkRunResult>>

Get results

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pub fn metadata(&self) -> &BenchmarkMetadata

Get metadata

Trait Implementations§

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impl Clone for BenchmarkResults

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fn clone(&self) -> BenchmarkResults

Returns a duplicate of the value. Read more
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fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more
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impl Debug for BenchmarkResults

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fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter. Read more

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