scirs2-core 0.4.2

//! Hardware profiling and environment detection for tensor operations
//!
//! This module contains components for detecting and monitoring hardware
//! characteristics, thermal management, power profiling, and system environment.

use super::*;
use crate::error::{CoreError, CoreResult};

#[cfg(feature = "gpu")]
use std::collections::HashMap;
#[cfg(feature = "gpu")]
use std::time::{Duration, Instant};

#[cfg(feature = "gpu")]
use crate::gpu::{tensor_cores::TensorDataType, GpuBackend};

#[cfg(all(feature = "serde", feature = "gpu"))]
#[cfg(feature = "serialization")]
use serde::{Deserialize, Serialize};

/// Hardware profiler for device characteristics
#[allow(dead_code)]
#[derive(Debug)]
pub struct HardwareProfiler {
    /// Device specifications
    device_specs: HashMap<GpuBackend, DeviceSpecifications>,
    /// Performance characteristics
    performance_characteristics: HashMap<GpuBackend, PerformanceCharacteristics>,
    /// Thermal profiles
    thermal_profiles: HashMap<GpuBackend, ThermalProfile>,
    /// Power profiles
    power_profiles: HashMap<GpuBackend, PowerProfile>,
}

/// Detailed device specifications
#[allow(dead_code)]
#[derive(Debug, Clone)]
pub struct DeviceSpecifications {
    /// Compute units
    pub compute_units: usize,
    /// Clock speeds
    pub base_clock_mhz: u32,
    pub boost_clock_mhz: u32,
    /// Memory specifications
    pub memory_size_gb: f64,
    pub memory_bandwidth_gbps: f64,
    /// Cache sizes
    pub l1_cache_kb: usize,
    pub l2_cache_kb: usize,
    /// Tensor core specifications
    pub tensor_cores: Option<TensorCoreSpecs>,
}

/// Tensor core specifications
#[allow(dead_code)]
#[derive(Debug, Clone)]
pub struct TensorCoreSpecs {
    /// Number of tensor cores
    pub count: usize,
    /// Supported precisions
    pub supported_precisions: Vec<TensorDataType>,
    /// Peak throughput
    pub peak_tops: f64,
    /// Matrix dimensions
    pub matrix_dimensions: Vec<(usize, usize, usize)>,
}

/// Performance characteristics
#[allow(dead_code)]
#[derive(Debug, Clone)]
pub struct PerformanceCharacteristics {
    /// Peak compute throughput
    pub peak_compute_tflops: f64,
    /// Memory bandwidth utilization
    pub memory_bandwidth_efficiency: f64,
    /// Cache hit rates
    pub typical_cache_hit_rates: HashMap<String, f64>,
    /// Thermal throttling thresholds
    pub thermal_throttle_temp: f64,
    /// Power efficiency
    pub performance_per_watt: f64,
}

/// Thermal profile for temperature management
#[allow(dead_code)]
#[derive(Debug, Clone)]
pub struct ThermalProfile {
    /// Idle temperature
    pub idle_temp_celsius: f64,
    /// Load temperature
    pub load_temp_celsius: f64,
    /// Maximum safe temperature
    pub max_temp_celsius: f64,
    /// Thermal design power
    pub tdp_watts: f64,
    /// Cooling efficiency
    pub cooling_efficiency: f64,
}

/// Power profile for energy optimization
#[allow(dead_code)]
#[derive(Debug, Clone)]
pub struct PowerProfile {
    /// Idle power consumption
    pub idle_power_watts: f64,
    /// Peak power consumption
    pub peak_power_watts: f64,
    /// Voltage ranges
    pub voltage_range: (f64, f64),
    /// Frequency scaling capabilities
    pub frequency_scaling: bool,
    /// Power states
    pub power_states: Vec<PowerState>,
}

/// Power state configuration
#[allow(dead_code)]
#[derive(Debug, Clone)]
pub struct PowerState {
    /// State name
    pub name: String,
    /// Core frequency
    pub core_frequency_mhz: u32,
    /// Memory frequency
    pub memory_frequency_mhz: u32,
    /// Voltage
    pub voltage: f64,
    /// Power consumption
    pub power_watts: f64,
}

/// Environment detector for system context
#[allow(dead_code)]
#[derive(Debug)]
pub struct EnvironmentDetector {
    /// System load monitor
    system_load: SystemLoadMonitor,
    /// Temperature monitor
    temperature_monitor: TemperatureMonitor,
    /// Power monitor
    power_monitor: PowerMonitor,
    /// Network monitor
    network_monitor: NetworkMonitor,
}

/// System load monitoring
#[allow(dead_code)]
#[derive(Debug)]
pub struct SystemLoadMonitor {
    /// CPU utilization
    pub cpu_utilization: f64,
    /// Memory utilization
    pub memory_utilization: f64,
    /// GPU utilization
    pub gpu_utilization: HashMap<GpuBackend, f64>,
    /// I/O wait time
    pub io_wait: f64,
}

/// Temperature monitoring
#[allow(dead_code)]
#[derive(Debug)]
pub struct TemperatureMonitor {
    /// GPU temperatures
    pub gpu_temperatures: HashMap<GpuBackend, f64>,
    /// CPU temperature
    pub cpu_temperature: f64,
    /// Ambient temperature
    pub ambient_temperature: f64,
    /// Thermal events
    pub thermal_events: Vec<ThermalEvent>,
}

/// Thermal event tracking
#[allow(dead_code)]
#[derive(Debug, Clone)]
pub struct ThermalEvent {
    /// Event type
    pub event_type: ThermalEventType,
    /// Timestamp
    pub timestamp: Instant,
    /// Temperature at event
    pub temperature: f64,
    /// Action taken
    pub action: String,
}

/// Types of thermal events
#[allow(dead_code)]
#[derive(Debug, Clone)]
pub enum ThermalEventType {
    TemperatureRise,
    TemperatureDrop,
    ThermalThrottling,
    CoolingActivation,
    ThermalAlert,
}

/// Power monitoring
#[allow(dead_code)]
#[derive(Debug)]
pub struct PowerMonitor {
    /// Current power consumption
    pub current_power_watts: f64,
    /// Power budget
    pub power_budget_watts: f64,
    /// Energy consumption
    pub energy_consumed_joules: f64,
    /// Power efficiency
    pub power_efficiency: f64,
    /// Power events
    pub power_events: Vec<PowerEvent>,
}

/// Power event tracking
#[allow(dead_code)]
#[derive(Debug, Clone)]
pub struct PowerEvent {
    /// Event type
    pub event_type: PowerEventType,
    /// Timestamp
    pub timestamp: Instant,
    /// Power level
    pub power_watts: f64,
    /// Duration
    pub duration: Duration,
}

/// Types of power events
#[allow(dead_code)]
#[derive(Debug, Clone)]
pub enum PowerEventType {
    PowerSpike,
    PowerDrop,
    PowerThrottling,
    PowerStateChange,
    PowerAlert,
}

/// Network monitoring for distributed optimization
#[allow(dead_code)]
#[derive(Debug)]
pub struct NetworkMonitor {
    /// Network bandwidth
    pub bandwidth_mbps: f64,
    /// Network latency
    pub latency_ms: f64,
    /// Packet loss rate
    pub packet_loss_rate: f64,
    /// Connection quality
    pub connection_quality: ConnectionQuality,
}

/// Network connection quality assessment
#[allow(dead_code)]
#[derive(Debug, Clone)]
pub enum ConnectionQuality {
    Excellent,
    Good,
    Fair,
    Poor,
    Unavailable,
}

// Implementation blocks

impl HardwareProfiler {
    pub fn new() -> CoreResult<Self> {
        Ok(Self {
            device_specs: HashMap::new(),
            performance_characteristics: HashMap::new(),
            thermal_profiles: HashMap::new(),
            power_profiles: HashMap::new(),
        })
    }

    /// Profile a specific GPU backend
    pub fn profile_device(&mut self, backend: GpuBackend) -> CoreResult<()> {
        // Create device specifications based on backend type
        let device_spec = match backend {
            GpuBackend::Cuda => DeviceSpecifications {
                compute_units: 128,
                base_clock_mhz: 1500,
                boost_clock_mhz: 1800,
                memory_size_gb: 24.0,
                memory_bandwidth_gbps: 900.0,
                l1_cache_kb: 128,
                l2_cache_kb: 6144,
                tensor_cores: Some(TensorCoreSpecs {
                    count: 432,
                    supported_precisions: vec![
                        TensorDataType::Float16,
                        TensorDataType::BFloat16,
                        TensorDataType::Float32,
                        TensorDataType::Int8,
                    ],
                    peak_tops: 1000.0,
                    matrix_dimensions: vec![(16, 16, 16), (32, 8, 16), (8, 32, 16)],
                }),
            },
            GpuBackend::OpenCL => DeviceSpecifications {
                compute_units: 64,
                base_clock_mhz: 1200,
                boost_clock_mhz: 1500,
                memory_size_gb: 16.0,
                memory_bandwidth_gbps: 600.0,
                l1_cache_kb: 64,
                l2_cache_kb: 4096,
                tensor_cores: None,
            },
            GpuBackend::Metal => DeviceSpecifications {
                compute_units: 96,
                base_clock_mhz: 1300,
                boost_clock_mhz: 1600,
                memory_size_gb: 32.0,
                memory_bandwidth_gbps: 800.0,
                l1_cache_kb: 96,
                l2_cache_kb: 8192,
                tensor_cores: Some(TensorCoreSpecs {
                    count: 256,
                    supported_precisions: vec![TensorDataType::Float16, TensorDataType::Float32],
                    peak_tops: 700.0,
                    matrix_dimensions: vec![(16, 16, 16), (32, 32, 32)],
                }),
            },
            _ => DeviceSpecifications {
                compute_units: 32,
                base_clock_mhz: 1000,
                boost_clock_mhz: 1200,
                memory_size_gb: 8.0,
                memory_bandwidth_gbps: 400.0,
                l1_cache_kb: 32,
                l2_cache_kb: 2048,
                tensor_cores: None,
            },
        };

        // Create performance characteristics
        let perf_characteristics = PerformanceCharacteristics {
            peak_compute_tflops: if device_spec.tensor_cores.is_some() {
                100.0
            } else {
                20.0
            },
            memory_bandwidth_efficiency: 0.85,
            typical_cache_hit_rates: {
                let mut rates = HashMap::new();
                rates.insert("L1".to_string(), 0.95);
                rates.insert("L2".to_string(), 0.85);
                rates.insert("Shared".to_string(), 0.90);
                rates
            },
            thermal_throttle_temp: 83.0,
            performance_per_watt: 50.0,
        };

        // Create thermal profile
        let thermal_profile = ThermalProfile {
            idle_temp_celsius: 35.0,
            load_temp_celsius: 75.0,
            max_temp_celsius: 90.0,
            tdp_watts: 300.0,
            cooling_efficiency: 0.8,
        };

        // Create power profile
        let power_profile = PowerProfile {
            idle_power_watts: 30.0,
            peak_power_watts: 300.0,
            voltage_range: (0.8, 1.2),
            frequency_scaling: true,
            power_states: vec![
                PowerState {
                    name: "P0".to_string(),
                    core_frequency_mhz: device_spec.boost_clock_mhz,
                    memory_frequency_mhz: 9500,
                    voltage: 1.2,
                    power_watts: 300.0,
                },
                PowerState {
                    name: "P1".to_string(),
                    core_frequency_mhz: device_spec.base_clock_mhz,
                    memory_frequency_mhz: 8000,
                    voltage: 1.0,
                    power_watts: 200.0,
                },
                PowerState {
                    name: "P2".to_string(),
                    core_frequency_mhz: device_spec.base_clock_mhz / 2,
                    memory_frequency_mhz: 4000,
                    voltage: 0.8,
                    power_watts: 100.0,
                },
            ],
        };

        // Store profiles
        self.device_specs.insert(backend, device_spec);
        self.performance_characteristics
            .insert(backend, perf_characteristics);
        self.thermal_profiles.insert(backend, thermal_profile);
        self.power_profiles.insert(backend, power_profile);

        Ok(())
    }

    /// Get device specifications for a backend
    pub fn get_device_specs(&self, backend: &GpuBackend) -> Option<&DeviceSpecifications> {
        self.device_specs.get(backend)
    }

    /// Get performance characteristics for a backend
    pub fn get_performance_characteristics(
        &self,
        backend: &GpuBackend,
    ) -> Option<&PerformanceCharacteristics> {
        self.performance_characteristics.get(backend)
    }

    /// Get thermal profile for a backend
    pub fn get_thermal_profile(&self, backend: &GpuBackend) -> Option<&ThermalProfile> {
        self.thermal_profiles.get(backend)
    }

    /// Get power profile for a backend
    pub fn get_power_profile(&self, backend: &GpuBackend) -> Option<&PowerProfile> {
        self.power_profiles.get(backend)
    }

    /// Check if device supports tensor cores
    pub fn supports_tensor_cores(&self, backend: &GpuBackend) -> bool {
        self.device_specs
            .get(backend)
            .and_then(|spec| spec.tensor_cores.as_ref())
            .is_some()
    }

    /// Get optimal power state for given performance target
    pub fn get_optimal_power_state(
        &self,
        backend: &GpuBackend,
        performance_target: f64,
    ) -> Option<&PowerState> {
        if let Some(power_profile) = self.power_profiles.get(backend) {
            // Simple heuristic: higher performance targets need higher power states
            if performance_target > 0.8 {
                power_profile.power_states.first()
            } else if performance_target > 0.5 {
                power_profile.power_states.get(1)
            } else {
                power_profile.power_states.last()
            }
        } else {
            None
        }
    }
}

impl EnvironmentDetector {
    pub fn new() -> CoreResult<Self> {
        Ok(Self {
            system_load: SystemLoadMonitor {
                cpu_utilization: 0.5,
                memory_utilization: 0.6,
                gpu_utilization: HashMap::new(),
                io_wait: 0.1,
            },
            temperature_monitor: TemperatureMonitor {
                gpu_temperatures: HashMap::new(),
                cpu_temperature: 65.0,
                ambient_temperature: 25.0,
                thermal_events: vec![],
            },
            power_monitor: PowerMonitor {
                current_power_watts: 150.0,
                power_budget_watts: 300.0,
                energy_consumed_joules: 0.0,
                power_efficiency: 0.8,
                power_events: vec![],
            },
            network_monitor: NetworkMonitor {
                bandwidth_mbps: 1000.0,
                latency_ms: 5.0,
                packet_loss_rate: 0.001,
                connection_quality: ConnectionQuality::Good,
            },
        })
    }

    /// Update system load measurements
    pub fn update_system_load(&mut self) -> CoreResult<()> {
        // Simulate system load monitoring
        // In a real implementation, this would query actual system metrics
        self.system_load.cpu_utilization = 0.3 + (rand::random::<f64>() * 0.4);
        self.system_load.memory_utilization = 0.4 + (rand::random::<f64>() * 0.3);
        self.system_load.io_wait = rand::random::<f64>() * 0.2;

        Ok(())
    }

    /// Update temperature measurements
    pub fn update_temperatures(&mut self) -> CoreResult<()> {
        // Simulate temperature monitoring
        self.temperature_monitor.cpu_temperature = 60.0 + (rand::random::<f64>() * 20.0);
        self.temperature_monitor.ambient_temperature = 20.0 + (rand::random::<f64>() * 10.0);

        // Check for thermal events
        if self.temperature_monitor.cpu_temperature > 80.0 {
            let event = ThermalEvent {
                event_type: ThermalEventType::ThermalThrottling,
                timestamp: Instant::now(),
                temperature: self.temperature_monitor.cpu_temperature,
                action: "Reducing clock speed".to_string(),
            };
            self.temperature_monitor.thermal_events.push(event);
        }

        Ok(())
    }

    /// Update power measurements
    pub fn update_power_consumption(&mut self) -> CoreResult<()> {
        // Simulate power monitoring
        let base_power = 100.0;
        let variable_power = rand::random::<f64>() * 200.0;
        self.power_monitor.current_power_watts = base_power + variable_power;

        // Update energy consumption
        let time_delta = 1.0; // Assume 1 second update interval
        self.power_monitor.energy_consumed_joules +=
            self.power_monitor.current_power_watts * time_delta;

        // Calculate efficiency
        self.power_monitor.power_efficiency = (self.power_monitor.power_budget_watts
            - self.power_monitor.current_power_watts)
            / self.power_monitor.power_budget_watts;

        // Check for power events
        if self.power_monitor.current_power_watts > self.power_monitor.power_budget_watts * 0.9 {
            let event = PowerEvent {
                event_type: PowerEventType::PowerAlert,
                timestamp: Instant::now(),
                power_watts: self.power_monitor.current_power_watts,
                duration: Duration::from_secs(1),
            };
            self.power_monitor.power_events.push(event);
        }

        Ok(())
    }

    /// Update network quality measurements
    pub fn update_network_quality(&mut self) -> CoreResult<()> {
        // Simulate network monitoring
        self.network_monitor.latency_ms = 1.0 + (rand::random::<f64>() * 10.0);
        self.network_monitor.packet_loss_rate = rand::random::<f64>() * 0.01;

        // Update connection quality based on metrics
        self.network_monitor.connection_quality = if self.network_monitor.latency_ms < 5.0
            && self.network_monitor.packet_loss_rate < 0.001
        {
            ConnectionQuality::Excellent
        } else if self.network_monitor.latency_ms < 20.0
            && self.network_monitor.packet_loss_rate < 0.005
        {
            ConnectionQuality::Good
        } else if self.network_monitor.latency_ms < 50.0
            && self.network_monitor.packet_loss_rate < 0.01
        {
            ConnectionQuality::Fair
        } else {
            ConnectionQuality::Poor
        };

        Ok(())
    }

    /// Get current system load
    pub fn get_system_load(&self) -> &SystemLoadMonitor {
        &self.system_load
    }

    /// Get current temperatures
    pub fn get_temperatures(&self) -> &TemperatureMonitor {
        &self.temperature_monitor
    }

    /// Get current power consumption
    pub fn get_power_consumption(&self) -> &PowerMonitor {
        &self.power_monitor
    }

    /// Get network quality
    pub fn get_network_quality(&self) -> &NetworkMonitor {
        &self.network_monitor
    }

    /// Check if system is under thermal stress
    pub fn is_thermal_stressed(&self) -> bool {
        self.temperature_monitor.cpu_temperature > 75.0
            || self
                .temperature_monitor
                .gpu_temperatures
                .values()
                .any(|&temp| temp > 80.0)
    }

    /// Check if system is power constrained
    pub fn is_power_constrained(&self) -> bool {
        self.power_monitor.current_power_watts > self.power_monitor.power_budget_watts * 0.8
    }

    /// Get system health score (0.0 to 1.0)
    pub fn get_system_health_score(&self) -> f64 {
        let temp_score = if self.temperature_monitor.cpu_temperature > 80.0 {
            0.0
        } else {
            1.0
        };
        let power_score = if self.is_power_constrained() {
            0.5
        } else {
            1.0
        };
        let load_score = 1.0
            - self
                .system_load
                .cpu_utilization
                .max(self.system_load.memory_utilization);

        (temp_score + power_score + load_score) / 3.0
    }
}

// Utility function to simulate random values
fn rand() -> f64 {
    use std::collections::hash_map::DefaultHasher;
    use std::hash::{Hash, Hasher};
    use std::time::SystemTime;

    let mut hasher = DefaultHasher::new();
    SystemTime::now().hash(&mut hasher);
    let hash = hasher.finish();
    (hash % 1000000) as f64 / 1000000.0
}

// Mock random module for compilation
mod rand {
    pub fn random<T>() -> T
    where
        T: Default,
    {
        T::default()
    }
}

impl Default for SystemLoadMonitor {
    fn default() -> Self {
        Self {
            cpu_utilization: 0.0,
            memory_utilization: 0.0,
            gpu_utilization: HashMap::new(),
            io_wait: 0.0,
        }
    }
}

impl Default for TemperatureMonitor {
    fn default() -> Self {
        Self {
            gpu_temperatures: HashMap::new(),
            cpu_temperature: 25.0,
            ambient_temperature: 20.0,
            thermal_events: Vec::new(),
        }
    }
}

impl Default for PowerMonitor {
    fn default() -> Self {
        Self {
            current_power_watts: 0.0,
            power_budget_watts: 300.0,
            energy_consumed_joules: 0.0,
            power_efficiency: 1.0,
            power_events: Vec::new(),
        }
    }
}

impl Default for NetworkMonitor {
    fn default() -> Self {
        Self {
            bandwidth_mbps: 1000.0,
            latency_ms: 1.0,
            packet_loss_rate: 0.0,
            connection_quality: ConnectionQuality::Excellent,
        }
    }
}