AdvancedGpuOptimizer

scirs2_datasets::gpu_optimization

Struct AdvancedGpuOptimizer 

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

Advanced-advanced GPU performance optimizer

Implementations§

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impl AdvancedGpuOptimizer

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pub fn new() -> Self

Create a new advanced GPU optimizer

Examples found in repository?
examples/advanced_showcase.rs (line 144)
130fn demonstrate_advanced_gpu_optimization() -> Result<(), Box<dyn std::error::Error>> {
131    println!("\n⚡ Advanced-GPU Optimization Demonstration");
132    println!("=====================================");
133
134    // Create GPU context (falls back to CPU if no GPU available)
135    println!("🔧 Initializing GPU context...");
136    let gpu_config = GpuConfig {
137        backend: GpuBackend::Cpu,
138        ..Default::default()
139    };
140    let gpu_context = GpuContext::new(gpu_config)?; // Using CPU backend for demo
141    println!("   Backend: {:?}", gpu_context.backend());
142
143    // Create advanced-GPU optimizer
144    let optimizer = AdvancedGpuOptimizer::new()
145        .with_adaptive_kernels(true)
146        .with_memory_prefetch(true)
147        .with_multi_gpu(false) // Single GPU for demo
148        .with_auto_tuning(true);
149
150    // Generate advanced-optimized matrix
151    println!("🔥 Generating advanced-optimized matrix...");
152    let start_time = Instant::now();
153    let matrix = optimizer.generate_advanced_optimized_matrix(
154        &gpu_context,
155        500,      // rows
156        200,      // cols
157        "normal", // distribution
158    )?;
159    let generation_time = start_time.elapsed();
160
161    println!(
162        "   Generated {}x{} matrix in: {:?}",
163        matrix.nrows(),
164        matrix.ncols(),
165        generation_time
166    );
167    let matrix_mean = matrix.clone().mean();
168    let matrix_std = matrix.var(1.0).sqrt();
169    println!(
170        "   Matrix stats: mean={:.3}, std={:.3}",
171        matrix_mean, matrix_std
172    );
173
174    // Benchmark performance
175    println!("📊 Running performance benchmarks...");
176    let datashapes = vec![(100, 50), (500, 200), (1000, 500)];
177    let benchmark_results =
178        optimizer.benchmark_performance(&gpu_context, "matrix_generation", &datashapes)?;
179
180    println!("   Benchmark Results:");
181    println!(
182        "     Best Speedup: {:.2}x",
183        benchmark_results.best_speedup()
184    );
185    println!(
186        "     Average Speedup: {:.2}x",
187        benchmark_results.average_speedup()
188    );
189    println!(
190        "     Total Memory Usage: {:.1} MB",
191        benchmark_results.total_memory_usage()
192    );
193
194    Ok(())
195}
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pub fn with_adaptive_kernels(self, enabled: bool) -> Self

Configure adaptive kernel selection

Examples found in repository?
examples/advanced_showcase.rs (line 145)
130fn demonstrate_advanced_gpu_optimization() -> Result<(), Box<dyn std::error::Error>> {
131    println!("\n⚡ Advanced-GPU Optimization Demonstration");
132    println!("=====================================");
133
134    // Create GPU context (falls back to CPU if no GPU available)
135    println!("🔧 Initializing GPU context...");
136    let gpu_config = GpuConfig {
137        backend: GpuBackend::Cpu,
138        ..Default::default()
139    };
140    let gpu_context = GpuContext::new(gpu_config)?; // Using CPU backend for demo
141    println!("   Backend: {:?}", gpu_context.backend());
142
143    // Create advanced-GPU optimizer
144    let optimizer = AdvancedGpuOptimizer::new()
145        .with_adaptive_kernels(true)
146        .with_memory_prefetch(true)
147        .with_multi_gpu(false) // Single GPU for demo
148        .with_auto_tuning(true);
149
150    // Generate advanced-optimized matrix
151    println!("🔥 Generating advanced-optimized matrix...");
152    let start_time = Instant::now();
153    let matrix = optimizer.generate_advanced_optimized_matrix(
154        &gpu_context,
155        500,      // rows
156        200,      // cols
157        "normal", // distribution
158    )?;
159    let generation_time = start_time.elapsed();
160
161    println!(
162        "   Generated {}x{} matrix in: {:?}",
163        matrix.nrows(),
164        matrix.ncols(),
165        generation_time
166    );
167    let matrix_mean = matrix.clone().mean();
168    let matrix_std = matrix.var(1.0).sqrt();
169    println!(
170        "   Matrix stats: mean={:.3}, std={:.3}",
171        matrix_mean, matrix_std
172    );
173
174    // Benchmark performance
175    println!("📊 Running performance benchmarks...");
176    let datashapes = vec![(100, 50), (500, 200), (1000, 500)];
177    let benchmark_results =
178        optimizer.benchmark_performance(&gpu_context, "matrix_generation", &datashapes)?;
179
180    println!("   Benchmark Results:");
181    println!(
182        "     Best Speedup: {:.2}x",
183        benchmark_results.best_speedup()
184    );
185    println!(
186        "     Average Speedup: {:.2}x",
187        benchmark_results.average_speedup()
188    );
189    println!(
190        "     Total Memory Usage: {:.1} MB",
191        benchmark_results.total_memory_usage()
192    );
193
194    Ok(())
195}
Source

pub fn with_memory_prefetch(self, enabled: bool) -> Self

Configure memory prefetching

Examples found in repository?
examples/advanced_showcase.rs (line 146)
130fn demonstrate_advanced_gpu_optimization() -> Result<(), Box<dyn std::error::Error>> {
131    println!("\n⚡ Advanced-GPU Optimization Demonstration");
132    println!("=====================================");
133
134    // Create GPU context (falls back to CPU if no GPU available)
135    println!("🔧 Initializing GPU context...");
136    let gpu_config = GpuConfig {
137        backend: GpuBackend::Cpu,
138        ..Default::default()
139    };
140    let gpu_context = GpuContext::new(gpu_config)?; // Using CPU backend for demo
141    println!("   Backend: {:?}", gpu_context.backend());
142
143    // Create advanced-GPU optimizer
144    let optimizer = AdvancedGpuOptimizer::new()
145        .with_adaptive_kernels(true)
146        .with_memory_prefetch(true)
147        .with_multi_gpu(false) // Single GPU for demo
148        .with_auto_tuning(true);
149
150    // Generate advanced-optimized matrix
151    println!("🔥 Generating advanced-optimized matrix...");
152    let start_time = Instant::now();
153    let matrix = optimizer.generate_advanced_optimized_matrix(
154        &gpu_context,
155        500,      // rows
156        200,      // cols
157        "normal", // distribution
158    )?;
159    let generation_time = start_time.elapsed();
160
161    println!(
162        "   Generated {}x{} matrix in: {:?}",
163        matrix.nrows(),
164        matrix.ncols(),
165        generation_time
166    );
167    let matrix_mean = matrix.clone().mean();
168    let matrix_std = matrix.var(1.0).sqrt();
169    println!(
170        "   Matrix stats: mean={:.3}, std={:.3}",
171        matrix_mean, matrix_std
172    );
173
174    // Benchmark performance
175    println!("📊 Running performance benchmarks...");
176    let datashapes = vec![(100, 50), (500, 200), (1000, 500)];
177    let benchmark_results =
178        optimizer.benchmark_performance(&gpu_context, "matrix_generation", &datashapes)?;
179
180    println!("   Benchmark Results:");
181    println!(
182        "     Best Speedup: {:.2}x",
183        benchmark_results.best_speedup()
184    );
185    println!(
186        "     Average Speedup: {:.2}x",
187        benchmark_results.average_speedup()
188    );
189    println!(
190        "     Total Memory Usage: {:.1} MB",
191        benchmark_results.total_memory_usage()
192    );
193
194    Ok(())
195}
Source

pub fn with_multi_gpu(self, enabled: bool) -> Self

Configure multi-GPU coordination

Examples found in repository?
examples/advanced_showcase.rs (line 147)
130fn demonstrate_advanced_gpu_optimization() -> Result<(), Box<dyn std::error::Error>> {
131    println!("\n⚡ Advanced-GPU Optimization Demonstration");
132    println!("=====================================");
133
134    // Create GPU context (falls back to CPU if no GPU available)
135    println!("🔧 Initializing GPU context...");
136    let gpu_config = GpuConfig {
137        backend: GpuBackend::Cpu,
138        ..Default::default()
139    };
140    let gpu_context = GpuContext::new(gpu_config)?; // Using CPU backend for demo
141    println!("   Backend: {:?}", gpu_context.backend());
142
143    // Create advanced-GPU optimizer
144    let optimizer = AdvancedGpuOptimizer::new()
145        .with_adaptive_kernels(true)
146        .with_memory_prefetch(true)
147        .with_multi_gpu(false) // Single GPU for demo
148        .with_auto_tuning(true);
149
150    // Generate advanced-optimized matrix
151    println!("🔥 Generating advanced-optimized matrix...");
152    let start_time = Instant::now();
153    let matrix = optimizer.generate_advanced_optimized_matrix(
154        &gpu_context,
155        500,      // rows
156        200,      // cols
157        "normal", // distribution
158    )?;
159    let generation_time = start_time.elapsed();
160
161    println!(
162        "   Generated {}x{} matrix in: {:?}",
163        matrix.nrows(),
164        matrix.ncols(),
165        generation_time
166    );
167    let matrix_mean = matrix.clone().mean();
168    let matrix_std = matrix.var(1.0).sqrt();
169    println!(
170        "   Matrix stats: mean={:.3}, std={:.3}",
171        matrix_mean, matrix_std
172    );
173
174    // Benchmark performance
175    println!("📊 Running performance benchmarks...");
176    let datashapes = vec![(100, 50), (500, 200), (1000, 500)];
177    let benchmark_results =
178        optimizer.benchmark_performance(&gpu_context, "matrix_generation", &datashapes)?;
179
180    println!("   Benchmark Results:");
181    println!(
182        "     Best Speedup: {:.2}x",
183        benchmark_results.best_speedup()
184    );
185    println!(
186        "     Average Speedup: {:.2}x",
187        benchmark_results.average_speedup()
188    );
189    println!(
190        "     Total Memory Usage: {:.1} MB",
191        benchmark_results.total_memory_usage()
192    );
193
194    Ok(())
195}
Source

pub fn with_auto_tuning(self, enabled: bool) -> Self

Configure auto-tuning

Examples found in repository?
examples/advanced_showcase.rs (line 148)
130fn demonstrate_advanced_gpu_optimization() -> Result<(), Box<dyn std::error::Error>> {
131    println!("\n⚡ Advanced-GPU Optimization Demonstration");
132    println!("=====================================");
133
134    // Create GPU context (falls back to CPU if no GPU available)
135    println!("🔧 Initializing GPU context...");
136    let gpu_config = GpuConfig {
137        backend: GpuBackend::Cpu,
138        ..Default::default()
139    };
140    let gpu_context = GpuContext::new(gpu_config)?; // Using CPU backend for demo
141    println!("   Backend: {:?}", gpu_context.backend());
142
143    // Create advanced-GPU optimizer
144    let optimizer = AdvancedGpuOptimizer::new()
145        .with_adaptive_kernels(true)
146        .with_memory_prefetch(true)
147        .with_multi_gpu(false) // Single GPU for demo
148        .with_auto_tuning(true);
149
150    // Generate advanced-optimized matrix
151    println!("🔥 Generating advanced-optimized matrix...");
152    let start_time = Instant::now();
153    let matrix = optimizer.generate_advanced_optimized_matrix(
154        &gpu_context,
155        500,      // rows
156        200,      // cols
157        "normal", // distribution
158    )?;
159    let generation_time = start_time.elapsed();
160
161    println!(
162        "   Generated {}x{} matrix in: {:?}",
163        matrix.nrows(),
164        matrix.ncols(),
165        generation_time
166    );
167    let matrix_mean = matrix.clone().mean();
168    let matrix_std = matrix.var(1.0).sqrt();
169    println!(
170        "   Matrix stats: mean={:.3}, std={:.3}",
171        matrix_mean, matrix_std
172    );
173
174    // Benchmark performance
175    println!("📊 Running performance benchmarks...");
176    let datashapes = vec![(100, 50), (500, 200), (1000, 500)];
177    let benchmark_results =
178        optimizer.benchmark_performance(&gpu_context, "matrix_generation", &datashapes)?;
179
180    println!("   Benchmark Results:");
181    println!(
182        "     Best Speedup: {:.2}x",
183        benchmark_results.best_speedup()
184    );
185    println!(
186        "     Average Speedup: {:.2}x",
187        benchmark_results.average_speedup()
188    );
189    println!(
190        "     Total Memory Usage: {:.1} MB",
191        benchmark_results.total_memory_usage()
192    );
193
194    Ok(())
195}
Source

pub fn optimize_execution( &self, gpu_context: &GpuContext, operation: &str, datashape: (usize, usize), ) -> Result<AdvancedKernelConfig>

Optimize GPU execution for a specific operation

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pub fn generate_advanced_optimized_matrix( &self, gpu_context: &GpuContext, rows: usize, cols: usize, distribution: &str, ) -> Result<Array2<f64>>

Advanced-optimized matrix generation on GPU

Examples found in repository?
examples/advanced_showcase.rs (lines 153-158)
130fn demonstrate_advanced_gpu_optimization() -> Result<(), Box<dyn std::error::Error>> {
131    println!("\n⚡ Advanced-GPU Optimization Demonstration");
132    println!("=====================================");
133
134    // Create GPU context (falls back to CPU if no GPU available)
135    println!("🔧 Initializing GPU context...");
136    let gpu_config = GpuConfig {
137        backend: GpuBackend::Cpu,
138        ..Default::default()
139    };
140    let gpu_context = GpuContext::new(gpu_config)?; // Using CPU backend for demo
141    println!("   Backend: {:?}", gpu_context.backend());
142
143    // Create advanced-GPU optimizer
144    let optimizer = AdvancedGpuOptimizer::new()
145        .with_adaptive_kernels(true)
146        .with_memory_prefetch(true)
147        .with_multi_gpu(false) // Single GPU for demo
148        .with_auto_tuning(true);
149
150    // Generate advanced-optimized matrix
151    println!("🔥 Generating advanced-optimized matrix...");
152    let start_time = Instant::now();
153    let matrix = optimizer.generate_advanced_optimized_matrix(
154        &gpu_context,
155        500,      // rows
156        200,      // cols
157        "normal", // distribution
158    )?;
159    let generation_time = start_time.elapsed();
160
161    println!(
162        "   Generated {}x{} matrix in: {:?}",
163        matrix.nrows(),
164        matrix.ncols(),
165        generation_time
166    );
167    let matrix_mean = matrix.clone().mean();
168    let matrix_std = matrix.var(1.0).sqrt();
169    println!(
170        "   Matrix stats: mean={:.3}, std={:.3}",
171        matrix_mean, matrix_std
172    );
173
174    // Benchmark performance
175    println!("📊 Running performance benchmarks...");
176    let datashapes = vec![(100, 50), (500, 200), (1000, 500)];
177    let benchmark_results =
178        optimizer.benchmark_performance(&gpu_context, "matrix_generation", &datashapes)?;
179
180    println!("   Benchmark Results:");
181    println!(
182        "     Best Speedup: {:.2}x",
183        benchmark_results.best_speedup()
184    );
185    println!(
186        "     Average Speedup: {:.2}x",
187        benchmark_results.average_speedup()
188    );
189    println!(
190        "     Total Memory Usage: {:.1} MB",
191        benchmark_results.total_memory_usage()
192    );
193
194    Ok(())
195}
Source

pub fn benchmark_performance( &self, gpu_context: &GpuContext, operation: &str, datashapes: &[(usize, usize)], ) -> Result<PerformanceBenchmarkResults>

Benchmark GPU vs CPU performance

Examples found in repository?
examples/advanced_showcase.rs (line 178)
130fn demonstrate_advanced_gpu_optimization() -> Result<(), Box<dyn std::error::Error>> {
131    println!("\n⚡ Advanced-GPU Optimization Demonstration");
132    println!("=====================================");
133
134    // Create GPU context (falls back to CPU if no GPU available)
135    println!("🔧 Initializing GPU context...");
136    let gpu_config = GpuConfig {
137        backend: GpuBackend::Cpu,
138        ..Default::default()
139    };
140    let gpu_context = GpuContext::new(gpu_config)?; // Using CPU backend for demo
141    println!("   Backend: {:?}", gpu_context.backend());
142
143    // Create advanced-GPU optimizer
144    let optimizer = AdvancedGpuOptimizer::new()
145        .with_adaptive_kernels(true)
146        .with_memory_prefetch(true)
147        .with_multi_gpu(false) // Single GPU for demo
148        .with_auto_tuning(true);
149
150    // Generate advanced-optimized matrix
151    println!("🔥 Generating advanced-optimized matrix...");
152    let start_time = Instant::now();
153    let matrix = optimizer.generate_advanced_optimized_matrix(
154        &gpu_context,
155        500,      // rows
156        200,      // cols
157        "normal", // distribution
158    )?;
159    let generation_time = start_time.elapsed();
160
161    println!(
162        "   Generated {}x{} matrix in: {:?}",
163        matrix.nrows(),
164        matrix.ncols(),
165        generation_time
166    );
167    let matrix_mean = matrix.clone().mean();
168    let matrix_std = matrix.var(1.0).sqrt();
169    println!(
170        "   Matrix stats: mean={:.3}, std={:.3}",
171        matrix_mean, matrix_std
172    );
173
174    // Benchmark performance
175    println!("📊 Running performance benchmarks...");
176    let datashapes = vec![(100, 50), (500, 200), (1000, 500)];
177    let benchmark_results =
178        optimizer.benchmark_performance(&gpu_context, "matrix_generation", &datashapes)?;
179
180    println!("   Benchmark Results:");
181    println!(
182        "     Best Speedup: {:.2}x",
183        benchmark_results.best_speedup()
184    );
185    println!(
186        "     Average Speedup: {:.2}x",
187        benchmark_results.average_speedup()
188    );
189    println!(
190        "     Total Memory Usage: {:.1} MB",
191        benchmark_results.total_memory_usage()
192    );
193
194    Ok(())
195}
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impl AdvancedGpuOptimizer

Enhanced AdvancedGpuOptimizer with AI and real-time monitoring

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pub fn with_ai_monitoring() -> Self

Create optimizer with AI-driven optimization and real-time monitoring

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pub fn predict_optimal_config( &self, operation: &str, datashape: (usize, usize), historical_data: &[PerformanceDataPoint], ) -> Result<AdvancedKernelConfig>

Predict optimal configuration using AI

Trait Implementations§

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impl Clone for AdvancedGpuOptimizer

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fn clone(&self) -> AdvancedGpuOptimizer

Returns a duplicate of the value. Read more
1.0.0 · Source§

fn clone_from(&mut self, source: &Self)

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

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

Formats the value using the given formatter. Read more
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impl Default for AdvancedGpuOptimizer

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fn default() -> Self

Returns the “default value” for a type. Read more

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