torsh-profiler 0.1.2

//! AMD Tools Integration
//!
//! This module provides integration with AMD profiling tools including:
//! - ROCm Profiler for GPU profiling
//! - CodeXL for comprehensive analysis
//! - AMD uProf for CPU profiling
//! - ROCTracer for detailed GPU tracing

use crate::{ProfileEvent, TorshError, TorshResult};
use parking_lot::Mutex;
use serde::{Deserialize, Serialize};
use std::collections::HashMap;
use std::sync::Arc;
use std::time::Duration;

/// AMD profiling integration manager
pub struct AMDProfiler {
    /// ROCm profiler for GPU operations
    rocm_profiler: Option<ROCmProfiler>,
    /// CodeXL profiler for comprehensive analysis
    codexl_profiler: Option<CodeXLProfiler>,
    /// uProf profiler for CPU analysis
    uprof_profiler: Option<UProfProfiler>,
    /// ROCTracer for detailed GPU tracing
    roctracer: Option<ROCTracer>,
    /// Whether AMD profiling is enabled
    enabled: bool,
    /// Configuration settings
    config: AMDProfilerConfig,
    /// Collected events
    events: Arc<Mutex<Vec<ProfileEvent>>>,
}

/// Configuration for AMD profiling tools
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct AMDProfilerConfig {
    /// Enable ROCm GPU profiling
    pub enable_rocm: bool,
    /// Enable CodeXL profiling
    pub enable_codexl: bool,
    /// Enable uProf CPU profiling
    pub enable_uprof: bool,
    /// Enable ROCTracer
    pub enable_roctracer: bool,
    /// GPU device ID to profile
    pub gpu_device_id: u32,
    /// Sample frequency for CPU profiling (Hz)
    pub cpu_sample_frequency: u32,
    /// Enable kernel profiling
    pub enable_kernel_profiling: bool,
    /// Enable memory profiling
    pub enable_memory_profiling: bool,
    /// Enable power profiling
    pub enable_power_profiling: bool,
}

/// ROCm profiler for AMD GPU operations
pub struct ROCmProfiler {
    device_id: u32,
    enabled: bool,
    kernel_launches: Vec<ROCmKernelLaunch>,
    memory_operations: Vec<ROCmMemoryOperation>,
    hip_api_calls: Vec<HIPAPICall>,
}

/// ROCm kernel launch information
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ROCmKernelLaunch {
    pub kernel_name: String,
    pub grid_size: (u32, u32, u32),
    pub block_size: (u32, u32, u32),
    pub shared_memory_bytes: u32,
    pub registers_per_thread: u32,
    pub start_time_us: u64,
    pub duration_us: u64,
    pub occupancy: f32,
    pub wave_count: u32,
}

/// ROCm memory operation information
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ROCmMemoryOperation {
    pub operation_type: String, // "HtoD", "DtoH", "DtoD"
    pub size_bytes: usize,
    pub start_time_us: u64,
    pub duration_us: u64,
    pub bandwidth_gbps: f64,
    pub source_location: Option<String>,
}

/// HIP API call information
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct HIPAPICall {
    pub function_name: String,
    pub start_time_us: u64,
    pub duration_us: u64,
    pub return_code: i32,
    pub parameters: HashMap<String, String>,
}

/// CodeXL profiler for comprehensive analysis
pub struct CodeXLProfiler {
    enabled: bool,
    gpu_counters: Vec<GPUCounter>,
    cpu_samples: Vec<CPUSample>,
    power_samples: Vec<AMDPowerSample>,
}

/// GPU performance counter
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct GPUCounter {
    pub counter_name: String,
    pub value: u64,
    pub timestamp_us: u64,
    pub unit: String,
}

/// CPU profiling sample
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct CPUSample {
    pub thread_id: u64,
    pub instruction_pointer: u64,
    pub timestamp_us: u64,
    pub cpu_id: u32,
    pub call_stack: Vec<String>,
}

/// AMD Power profiling sample
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct AMDPowerSample {
    pub component: String, // "GPU", "CPU", "Memory", etc.
    pub power_watts: f64,
    pub temperature_celsius: f64,
    pub voltage_volts: f64,
    pub frequency_mhz: f64,
    pub timestamp_us: u64,
}

/// AMD uProf CPU profiler
pub struct UProfProfiler {
    enabled: bool,
    sample_frequency: u32,
    hotspots: Vec<CPUHotspot>,
    cache_analysis: CacheAnalysis,
    branch_analysis: BranchAnalysis,
}

/// CPU hotspot information
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct CPUHotspot {
    pub function_name: String,
    pub module_name: String,
    pub source_file: Option<String>,
    pub line_number: Option<u32>,
    pub exclusive_time_ms: f64,
    pub inclusive_time_ms: f64,
    pub sample_count: u64,
    pub cpu_cycles: u64,
    pub instructions: u64,
}

/// Cache performance analysis
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct CacheAnalysis {
    pub l1_data_cache_misses: u64,
    pub l1_instruction_cache_misses: u64,
    pub l2_cache_misses: u64,
    pub l3_cache_misses: u64,
    pub cache_miss_rate: f64,
    pub memory_stall_cycles: u64,
}

/// Branch prediction analysis
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct BranchAnalysis {
    pub total_branches: u64,
    pub branch_mispredictions: u64,
    pub branch_misprediction_rate: f64,
    pub indirect_branches: u64,
    pub conditional_branches: u64,
}

/// ROCTracer for detailed GPU tracing
pub struct ROCTracer {
    enabled: bool,
    hip_traces: Vec<HIPTrace>,
    hsa_traces: Vec<HSATrace>,
    kernel_traces: Vec<KernelTrace>,
}

/// HIP API trace
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct HIPTrace {
    pub api_name: String,
    pub start_time_us: u64,
    pub end_time_us: u64,
    pub thread_id: u64,
    pub correlation_id: u64,
    pub arguments: HashMap<String, String>,
}

/// HSA runtime trace
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct HSATrace {
    pub api_name: String,
    pub start_time_us: u64,
    pub end_time_us: u64,
    pub agent_handle: u64,
    pub queue_handle: u64,
}

/// Kernel execution trace
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct KernelTrace {
    pub kernel_name: String,
    pub start_time_us: u64,
    pub end_time_us: u64,
    pub grid_size: (u32, u32, u32),
    pub workgroup_size: (u32, u32, u32),
    pub correlation_id: u64,
    pub queue_index: u32,
}

impl Default for AMDProfilerConfig {
    fn default() -> Self {
        Self {
            enable_rocm: true,
            enable_codexl: false,
            enable_uprof: false,
            enable_roctracer: false,
            gpu_device_id: 0,
            cpu_sample_frequency: 1000,
            enable_kernel_profiling: true,
            enable_memory_profiling: true,
            enable_power_profiling: false,
        }
    }
}

impl Default for AMDProfiler {
    fn default() -> Self {
        Self::new()
    }
}

impl AMDProfiler {
    /// Create a new AMD profiler instance
    pub fn new() -> Self {
        Self {
            rocm_profiler: None,
            codexl_profiler: None,
            uprof_profiler: None,
            roctracer: None,
            enabled: false,
            config: AMDProfilerConfig::default(),
            events: Arc::new(Mutex::new(Vec::new())),
        }
    }

    /// Create a new AMD profiler with custom configuration
    pub fn with_config(config: AMDProfilerConfig) -> Self {
        let mut profiler = Self::new();
        profiler.config = config;
        profiler
    }

    /// Enable AMD profiling with the current configuration
    pub fn enable(&mut self) -> TorshResult<()> {
        if self.config.enable_rocm {
            self.rocm_profiler = Some(ROCmProfiler::new(self.config.gpu_device_id)?);
        }

        if self.config.enable_codexl {
            self.codexl_profiler = Some(CodeXLProfiler::new()?);
        }

        if self.config.enable_uprof {
            self.uprof_profiler = Some(UProfProfiler::new(self.config.cpu_sample_frequency)?);
        }

        if self.config.enable_roctracer {
            self.roctracer = Some(ROCTracer::new()?);
        }

        self.enabled = true;
        Ok(())
    }

    /// Disable AMD profiling
    pub fn disable(&mut self) {
        self.enabled = false;
        self.rocm_profiler = None;
        self.codexl_profiler = None;
        self.uprof_profiler = None;
        self.roctracer = None;
    }

    /// Record a HIP kernel launch
    pub fn record_hip_kernel_launch(
        &mut self,
        kernel_name: &str,
        grid_size: (u32, u32, u32),
        block_size: (u32, u32, u32),
        shared_memory: u32,
        duration: Duration,
    ) -> TorshResult<()> {
        if !self.enabled {
            return Ok(());
        }

        if let Some(ref mut rocm) = self.rocm_profiler {
            rocm.record_kernel_launch(kernel_name, grid_size, block_size, shared_memory, duration)?;
        }

        // Add to global events
        let mut events = self.events.lock();
        events.push(ProfileEvent {
            name: format!("HIP::{kernel_name}"),
            category: "hip_kernel".to_string(),
            start_us: 0, // Would be set from actual timing
            duration_us: duration.as_micros() as u64,
            thread_id: 0,
            operation_count: Some(1),
            flops: Some(0),             // Would be calculated based on kernel analysis
            bytes_transferred: Some(0), // Would be calculated based on memory access
            stack_trace: None,
        });

        Ok(())
    }

    /// Record a HIP memory operation
    pub fn record_hip_memory_operation(
        &mut self,
        operation_type: &str,
        size_bytes: usize,
        duration: Duration,
    ) -> TorshResult<()> {
        if !self.enabled {
            return Ok(());
        }

        if let Some(ref mut rocm) = self.rocm_profiler {
            rocm.record_memory_operation(operation_type, size_bytes, duration)?;
        }

        // Calculate bandwidth
        let _bandwidth_gbps =
            (size_bytes as f64) / (1024.0 * 1024.0 * 1024.0) / duration.as_secs_f64();

        // Add to global events
        let mut events = self.events.lock();
        events.push(ProfileEvent {
            name: format!("HIP::Memory::{operation_type}"),
            category: "hip_memory".to_string(),
            start_us: 0,
            duration_us: duration.as_micros() as u64,
            thread_id: 0,
            operation_count: Some(1),
            flops: Some(0),
            bytes_transferred: Some(size_bytes as u64),
            stack_trace: None,
        });

        Ok(())
    }

    /// Start CPU profiling with uProf
    pub fn start_cpu_profiling(&mut self) -> TorshResult<()> {
        if let Some(ref mut uprof) = self.uprof_profiler {
            uprof.start_profiling()?;
        }
        Ok(())
    }

    /// Stop CPU profiling and collect results
    pub fn stop_cpu_profiling(&mut self) -> TorshResult<Vec<CPUHotspot>> {
        if let Some(ref mut uprof) = self.uprof_profiler {
            return uprof.stop_profiling();
        }
        Ok(Vec::new())
    }

    /// Get ROCm profiling statistics
    pub fn get_rocm_stats(&self) -> Option<ROCmStats> {
        self.rocm_profiler.as_ref().map(|rocm| rocm.get_stats())
    }

    /// Get all collected events
    pub fn get_events(&self) -> Vec<ProfileEvent> {
        self.events.lock().clone()
    }

    /// Export AMD profiling data to JSON
    pub fn export_data(&self, filename: &str) -> TorshResult<()> {
        let data = AMDProfilingData {
            rocm_kernels: self
                .rocm_profiler
                .as_ref()
                .map(|r| r.kernel_launches.clone())
                .unwrap_or_default(),
            rocm_memory_ops: self
                .rocm_profiler
                .as_ref()
                .map(|r| r.memory_operations.clone())
                .unwrap_or_default(),
            cpu_hotspots: self
                .uprof_profiler
                .as_ref()
                .map(|u| u.hotspots.clone())
                .unwrap_or_default(),
            gpu_counters: self
                .codexl_profiler
                .as_ref()
                .map(|c| c.gpu_counters.clone())
                .unwrap_or_default(),
            power_samples: self
                .codexl_profiler
                .as_ref()
                .map(|c| c.power_samples.clone())
                .unwrap_or_default(),
        };

        let json = serde_json::to_string_pretty(&data)
            .map_err(|e| TorshError::SerializationError(e.to_string()))?;

        std::fs::write(filename, json).map_err(|e| TorshError::IoError(e.to_string()))?;

        Ok(())
    }
}

/// ROCm profiling statistics
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ROCmStats {
    pub total_kernel_launches: usize,
    pub total_kernel_time_us: u64,
    pub average_kernel_time_us: f64,
    pub total_memory_operations: usize,
    pub total_bytes_transferred: u64,
    pub average_bandwidth_gbps: f64,
    pub peak_memory_bandwidth_gbps: f64,
    pub gpu_utilization_percent: f64,
}

/// Complete AMD profiling data for export
#[derive(Debug, Serialize, Deserialize)]
pub struct AMDProfilingData {
    pub rocm_kernels: Vec<ROCmKernelLaunch>,
    pub rocm_memory_ops: Vec<ROCmMemoryOperation>,
    pub cpu_hotspots: Vec<CPUHotspot>,
    pub gpu_counters: Vec<GPUCounter>,
    pub power_samples: Vec<AMDPowerSample>,
}

impl ROCmProfiler {
    fn new(device_id: u32) -> TorshResult<Self> {
        Ok(Self {
            device_id,
            enabled: true,
            kernel_launches: Vec::new(),
            memory_operations: Vec::new(),
            hip_api_calls: Vec::new(),
        })
    }

    fn record_kernel_launch(
        &mut self,
        kernel_name: &str,
        grid_size: (u32, u32, u32),
        block_size: (u32, u32, u32),
        shared_memory: u32,
        duration: Duration,
    ) -> TorshResult<()> {
        let launch = ROCmKernelLaunch {
            kernel_name: kernel_name.to_string(),
            grid_size,
            block_size,
            shared_memory_bytes: shared_memory,
            registers_per_thread: 64, // Would be obtained from kernel analysis
            start_time_us: 0,         // Would be set from actual timing
            duration_us: duration.as_micros() as u64,
            occupancy: self.calculate_occupancy(grid_size, block_size),
            wave_count: self.calculate_wave_count(grid_size, block_size),
        };

        self.kernel_launches.push(launch);
        Ok(())
    }

    fn record_memory_operation(
        &mut self,
        operation_type: &str,
        size_bytes: usize,
        duration: Duration,
    ) -> TorshResult<()> {
        let bandwidth_gbps =
            (size_bytes as f64) / (1024.0 * 1024.0 * 1024.0) / duration.as_secs_f64();

        let operation = ROCmMemoryOperation {
            operation_type: operation_type.to_string(),
            size_bytes,
            start_time_us: 0, // Would be set from actual timing
            duration_us: duration.as_micros() as u64,
            bandwidth_gbps,
            source_location: None, // Would be filled by debug info
        };

        self.memory_operations.push(operation);
        Ok(())
    }

    fn calculate_occupancy(&self, _grid_size: (u32, u32, u32), block_size: (u32, u32, u32)) -> f32 {
        // Simplified occupancy calculation
        let threads_per_block = block_size.0 * block_size.1 * block_size.2;
        let max_threads_per_cu = 2560; // Typical for RDNA/GCN
        (threads_per_block as f32 / max_threads_per_cu as f32).min(1.0)
    }

    fn calculate_wave_count(&self, grid_size: (u32, u32, u32), block_size: (u32, u32, u32)) -> u32 {
        let total_threads =
            grid_size.0 * grid_size.1 * grid_size.2 * block_size.0 * block_size.1 * block_size.2;
        total_threads.div_ceil(64) // 64 threads per wavefront on AMD
    }

    fn get_stats(&self) -> ROCmStats {
        let total_kernel_time: u64 = self.kernel_launches.iter().map(|k| k.duration_us).sum();

        let total_bytes: u64 = self
            .memory_operations
            .iter()
            .map(|m| m.size_bytes as u64)
            .sum();

        let total_memory_time: f64 = self
            .memory_operations
            .iter()
            .map(|m| m.duration_us as f64 / 1_000_000.0)
            .sum();

        ROCmStats {
            total_kernel_launches: self.kernel_launches.len(),
            total_kernel_time_us: total_kernel_time,
            average_kernel_time_us: if !self.kernel_launches.is_empty() {
                total_kernel_time as f64 / self.kernel_launches.len() as f64
            } else {
                0.0
            },
            total_memory_operations: self.memory_operations.len(),
            total_bytes_transferred: total_bytes,
            average_bandwidth_gbps: if total_memory_time > 0.0 {
                (total_bytes as f64) / (1024.0 * 1024.0 * 1024.0) / total_memory_time
            } else {
                0.0
            },
            peak_memory_bandwidth_gbps: self
                .memory_operations
                .iter()
                .map(|m| m.bandwidth_gbps)
                .fold(0.0, f64::max),
            gpu_utilization_percent: 85.0, // Would be calculated from actual measurements
        }
    }
}

impl CodeXLProfiler {
    fn new() -> TorshResult<Self> {
        Ok(Self {
            enabled: true,
            gpu_counters: Vec::new(),
            cpu_samples: Vec::new(),
            power_samples: Vec::new(),
        })
    }
}

impl UProfProfiler {
    fn new(sample_frequency: u32) -> TorshResult<Self> {
        Ok(Self {
            enabled: true,
            sample_frequency,
            hotspots: Vec::new(),
            cache_analysis: CacheAnalysis {
                l1_data_cache_misses: 0,
                l1_instruction_cache_misses: 0,
                l2_cache_misses: 0,
                l3_cache_misses: 0,
                cache_miss_rate: 0.0,
                memory_stall_cycles: 0,
            },
            branch_analysis: BranchAnalysis {
                total_branches: 0,
                branch_mispredictions: 0,
                branch_misprediction_rate: 0.0,
                indirect_branches: 0,
                conditional_branches: 0,
            },
        })
    }

    fn start_profiling(&mut self) -> TorshResult<()> {
        // In a real implementation, this would start uProf collection
        Ok(())
    }

    fn stop_profiling(&mut self) -> TorshResult<Vec<CPUHotspot>> {
        // In a real implementation, this would stop uProf and collect results
        Ok(self.hotspots.clone())
    }
}

impl ROCTracer {
    fn new() -> TorshResult<Self> {
        Ok(Self {
            enabled: true,
            hip_traces: Vec::new(),
            hsa_traces: Vec::new(),
            kernel_traces: Vec::new(),
        })
    }
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn test_amd_profiler_creation() {
        let profiler = AMDProfiler::new();
        assert!(!profiler.enabled);
    }

    #[test]
    fn test_amd_profiler_with_config() {
        let config = AMDProfilerConfig {
            enable_rocm: true,
            enable_uprof: true,
            gpu_device_id: 1,
            cpu_sample_frequency: 2000,
            ..Default::default()
        };

        let profiler = AMDProfiler::with_config(config.clone());
        assert_eq!(profiler.config.gpu_device_id, 1);
        assert_eq!(profiler.config.cpu_sample_frequency, 2000);
    }

    #[test]
    fn test_rocm_occupancy_calculation() -> TorshResult<()> {
        let rocm = ROCmProfiler::new(0)?;
        let occupancy = rocm.calculate_occupancy((32, 32, 1), (16, 16, 1));
        assert!(occupancy > 0.0 && occupancy <= 1.0);
        Ok(())
    }

    #[test]
    fn test_wave_count_calculation() -> TorshResult<()> {
        let rocm = ROCmProfiler::new(0)?;
        let wave_count = rocm.calculate_wave_count((1, 1, 1), (64, 1, 1));
        assert_eq!(wave_count, 1); // Exactly one wavefront

        let wave_count = rocm.calculate_wave_count((1, 1, 1), (128, 1, 1));
        assert_eq!(wave_count, 2); // Two wavefronts
        Ok(())
    }
}