Struct ScientificPerformanceOptimizer 

pub struct ScientificPerformanceOptimizer {
    pub config: PerformanceOptimizationConfig,
    pub memory_manager: Arc<Mutex<HierarchicalMemoryManager>>,
    pub parallel_processor: Arc<Mutex<AdvancedParallelProcessor>>,
    pub algorithm_optimizer: Arc<Mutex<AlgorithmOptimizer>>,
    pub distributed_coordinator: Arc<Mutex<DistributedCoordinator>>,
    pub profiler: Arc<Mutex<PerformanceProfiler>>,
    pub gpu_accelerator: Arc<Mutex<GPUAccelerator>>,
}

Main scientific performance optimization system

Fields

config: PerformanceOptimizationConfig

Configuration

memory_manager: Arc<Mutex<HierarchicalMemoryManager>>

Memory manager

parallel_processor: Arc<Mutex<AdvancedParallelProcessor>>

Parallel processor

algorithm_optimizer: Arc<Mutex<AlgorithmOptimizer>>

Algorithm optimizer

distributed_coordinator: Arc<Mutex<DistributedCoordinator>>

Distributed coordinator

profiler: Arc<Mutex<PerformanceProfiler>>

Performance profiler

gpu_accelerator: Arc<Mutex<GPUAccelerator>>

GPU accelerator

Implementations

impl ScientificPerformanceOptimizer

pub fn new(config: PerformanceOptimizationConfig) -> Self

Create new performance optimizer

pub fn initialize(&self) -> ApplicationResult<()>

Initialize the performance optimization system

pub fn optimize_protein_folding( &self, problem: &ProteinFoldingProblem, ) -> ApplicationResult<OptimizedProteinFoldingResult>

Optimize protein folding problem performance

pub fn optimize_materials_science( &self, problem: &MaterialsOptimizationProblem, ) -> ApplicationResult<OptimizedMaterialsScienceResult>

Optimize materials science problem performance

pub fn optimize_drug_discovery( &self, problem: &DrugDiscoveryProblem, ) -> ApplicationResult<OptimizedDrugDiscoveryResult>

Optimize drug discovery problem performance

pub fn get_performance_report( &self, ) -> ApplicationResult<ComprehensivePerformanceReport>

Get comprehensive performance report

pub fn generate_optimization_recommendations() -> ApplicationResult<Vec<OptimizationRecommendation>>

Generate optimization recommendations