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 118)
113fn print_performance_summary(results: &BenchmarkResults) {
114    println!("\n   Performance Summary:");
115    println!("   ===================");
116
117    // Print summaries for each benchmark
118    for (name, summary) in results.summaries() {
119        println!("   {name}:");
120        println!("     - Mean time: {:.3}s", summary.mean_time.as_secs_f64());
121        println!("     - Min time:  {:.3}s", summary.min_time.as_secs_f64());
122        println!("     - Max time:  {:.3}s", summary.max_time.as_secs_f64());
123        println!("     - Success rate: {:.1}%", summary.success_rate * 100.0);
124        if let Some(memory) = summary.mean_memory {
125            println!(
126                "     - Memory usage: {:.1} MB",
127                memory as f64 / 1024.0 / 1024.0
128            );
129        }
130        println!();
131    }
132}
133
134fn print_scaling_analysis(results: &BenchmarkResults) {
135    println!("   Scaling Analysis:");
136    println!("   =================");
137
138    // Group by algorithm type
139    let mut vqe_results = Vec::new();
140    let mut qaoa_results = Vec::new();
141    let mut qnn_results = Vec::new();
142
143    for (name, summary) in results.summaries() {
144        if name.starts_with("vqe_") {
145            vqe_results.push((name, summary));
146        } else if name.starts_with("qaoa_") {
147            qaoa_results.push((name, summary));
148        } else if name.starts_with("qnn_") {
149            qnn_results.push((name, summary));
150        }
151    }
152
153    // Analyze VQE scaling
154    if !vqe_results.is_empty() {
155        println!("   VQE Algorithm Scaling:");
156        vqe_results.sort_by_key(|(name, _)| (*name).clone());
157        for (name, summary) in vqe_results {
158            let qubits = extract_qubit_count(name);
159            println!(
160                "     - {} qubits: {:.3}s",
161                qubits,
162                summary.mean_time.as_secs_f64()
163            );
164        }
165        println!("     - Scaling trend: Exponential (as expected for VQE)");
166        println!();
167    }
168
169    // Analyze QAOA scaling
170    if !qaoa_results.is_empty() {
171        println!("   QAOA Algorithm Scaling:");
172        qaoa_results.sort_by_key(|(name, _)| (*name).clone());
173        for (name, summary) in qaoa_results {
174            let qubits = extract_qubit_count(name);
175            println!(
176                "     - {} qubits: {:.3}s",
177                qubits,
178                summary.mean_time.as_secs_f64()
179            );
180        }
181        println!("     - Scaling trend: Polynomial (as expected for QAOA)");
182        println!();
183    }
184
185    // Analyze QNN scaling
186    if !qnn_results.is_empty() {
187        println!("   QNN Algorithm Scaling:");
188        qnn_results.sort_by_key(|(name, _)| (*name).clone());
189        for (name, summary) in qnn_results {
190            let qubits = extract_qubit_count(name);
191            println!(
192                "     - {} qubits: {:.3}s",
193                qubits,
194                summary.mean_time.as_secs_f64()
195            );
196        }
197        println!("     - Scaling trend: Polynomial (training overhead)");
198        println!();
199    }
200}
201
202fn print_memory_analysis(results: &BenchmarkResults) {
203    println!("   Memory Usage Analysis:");
204    println!("   =====================");
205
206    let mut memory_data = Vec::new();
207    for (name, summary) in results.summaries() {
208        if let Some(memory) = summary.mean_memory {
209            let qubits = extract_qubit_count(name);
210            memory_data.push((qubits, memory, name));
211        }
212    }
213
214    if !memory_data.is_empty() {
215        memory_data.sort_by_key(|(qubits, _, _)| *qubits);
216
217        println!("   Memory scaling by qubit count:");
218        for (qubits, memory, name) in memory_data {
219            println!(
220                "     - {} qubits ({}): {:.1} MB",
221                qubits,
222                name,
223                memory as f64 / 1024.0 / 1024.0
224            );
225        }
226        println!("     - Expected scaling: O(2^n) for statevector simulation");
227        println!();
228    }
229
230    // Print recommendations
231    println!("   Recommendations:");
232    println!("     - Use statevector backend for circuits ≤ 12 qubits");
233    println!("     - Use MPS backend for larger circuits with limited entanglement");
234    println!("     - Consider circuit optimization for memory-constrained environments");
235}
236
237fn extract_qubit_count(benchmark_name: &str) -> usize {
238    // Extract number from strings like "vqe_4q_statevector", "qaoa_6q_mps", etc.
239    for part in benchmark_name.split('_') {
240        if part.ends_with('q') {
241            if let Ok(num) = part.trim_end_matches('q').parse::<usize>() {
242                return num;
243            }
244        }
245    }
246    0 // Default if not found
247}
248
249// Additional analysis functions
250fn analyze_backend_performance(results: &BenchmarkResults) {
251    println!("   Backend Performance Comparison:");
252    println!("   ==============================");
253
254    // Group results by backend type
255    let mut backend_performance = std::collections::HashMap::new();
256
257    for (name, summary) in results.summaries() {
258        let backend_type = extract_backend_type(name);
259        backend_performance
260            .entry(backend_type)
261            .or_insert_with(Vec::new)
262            .push(summary.mean_time.as_secs_f64());
263    }
264
265    for (backend, times) in backend_performance {
266        let avg_time = times.iter().sum::<f64>() / times.len() as f64;
267        println!("     - {backend} backend: {avg_time:.3}s average");
268    }
269}
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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