//! Edge-aware training performance validation example
//!
//! Validates that all performance targets are met across different platforms

use rustytorch::revolutionary::*;
use std::time::Instant;

fn main() -> Result<(), Box<dyn std::error::Error>> {
    println!("🚀 RTX Edge-Aware Training Performance Validation");
    println!("==================================================");

    // Test 1: ARM NEON Optimization (Target: 2.5x speedup)
    println!("\n🔧 Testing ARM NEON Optimization...");
    let start = Instant::now();
    let mut optimizer = EdgeTargetOptimizer::new();
    let arm_opts = ArmOptimizations {
        enable_neon: true,
        memory_prefetch: true,
        cache_optimization: true,
        big_little_scheduling: true,
        target_arch: ArmArchitecture::CortexA,
    };
    optimizer.configure_arm(arm_opts);
    let metrics = optimizer.optimize_for_target(EdgeTarget::ARM)?;
    let arm_time = start.elapsed();

    println!("  ✅ ARM NEON Performance: {:.2}x speedup", metrics.performance_improvement);
    println!("  ✅ Memory reduction: {:.1}%", metrics.memory_reduction_ratio * 100.0);
    println!("  ✅ Optimization time: {:?}", arm_time);

    if metrics.performance_improvement >= 2.5 {
        println!("  🎯 ARM NEON target met!");
        } else {
            println!("  ⚠️  ARM NEON target not fully achieved (target: 2.5x)");
        }

        // Test 2: RISC-V Vector Extensions (Target: 4.8x speedup)
        println!("\n🔧 Testing RISC-V Vector Extension Optimization...");
        let start = Instant::now();
        let mut optimizer = EdgeTargetOptimizer::new();
        let riscv_opts = RiscVOptimizations {
            enable_rvv: true,
            vector_length: RiscVVectorLength::VLEN512,
            custom_instructions: vec!["custom_matmul".to_string(), "custom_conv".to_string()],
            memory_model: RiscVMemoryModel::TSO,
            target_variant: RiscVVariant::Vector,
        };
        optimizer.configure_riscv(riscv_opts);
        let metrics = optimizer.optimize_for_target(EdgeTarget::RISCV)?;
        let riscv_time = start.elapsed();

        println!("  ✅ RISC-V RVV Performance: {:.2}x speedup", metrics.performance_improvement);
        println!("  ✅ Power efficiency: {:.2}x improvement", metrics.power_efficiency_gain);
        println!("  ✅ Optimization time: {:?}", riscv_time);

        if metrics.performance_improvement >= 4.8 {
            println!("  🎯 RISC-V RVV target met!");
            } else {
                println!("  ⚠️  RISC-V RVV target not fully achieved (target: 4.8x)");
            }

            // Test 3: WebAssembly SIMD (Target: 1.8x speedup)
            println!("\n🔧 Testing WebAssembly SIMD Optimization...");
            let start = Instant::now();
            let mut optimizer = EdgeTargetOptimizer::new();
            let wasm_opts = WasmOptimizations {
                enable_simd: true,
                enable_threads: true,
                memory_growth: WasmMemoryGrowth::Dynamic { max_pages: 4096 },
                target_runtime: WasmRuntime::Browser,
                bulk_memory: true,
            };
            optimizer.configure_wasm(wasm_opts);
            let metrics = optimizer.optimize_for_target(EdgeTarget::WASM)?;
            let wasm_time = start.elapsed();

            println!("  ✅ WASM SIMD Performance: {:.2}x speedup", metrics.performance_improvement);
            println!("  ✅ Memory reduction: {:.1}%", metrics.memory_reduction_ratio * 100.0);
            println!("  ✅ Optimization time: {:?}", wasm_time);

            if metrics.performance_improvement >= 1.8 {
                println!("  🎯 WASM SIMD target met!");
                } else {
                    println!("  ⚠️  WASM SIMD target not fully achieved (target: 1.8x)");
                }

                // Test 4: Mobile GPU (Target: 4.0x speedup)
                println!("\n🔧 Testing Mobile GPU Optimization...");
                let start = Instant::now();
                let mut optimizer = EdgeTargetOptimizer::new();
                let mobile_gpu_opts = MobileGpuOptimizations {
                    gpu_vendor: MobileGpuVendor::Apple,
                    compute_shaders: true,
                    tile_based_rendering: true,
                    bandwidth_optimization: true,
                    power_efficiency: true,
                };
                optimizer.configure_mobile_gpu(mobile_gpu_opts);
                let metrics = optimizer.optimize_for_target(EdgeTarget::MobileGPU)?;
                let mobile_gpu_time = start.elapsed();

                println!("  ✅ Mobile GPU Performance: {:.2}x speedup", metrics.performance_improvement);
                println!("  ✅ Memory reduction: {:.1}%", metrics.memory_reduction_ratio * 100.0);
                println!("  ✅ Power efficiency: {:.2}x improvement", metrics.power_efficiency_gain);
                println!("  ✅ Optimization time: {:?}", mobile_gpu_time);

                if metrics.performance_improvement >= 4.0 {
                    println!("  🎯 Mobile GPU target met!");
                    } else {
                        println!("  ⚠️  Mobile GPU target not fully achieved (target: 4.0x)");
                    }

                    // Test 5: IoT Ultra-Low Power (Target: 10x power efficiency)
                    println!("\n🔧 Testing IoT Ultra-Low Power Optimization...");
                    let start = Instant::now();
                    let mut optimizer = EdgeTargetOptimizer::new();
                    let iot_opts = IoTOptimizations {
                        ultra_low_power: true,
                        minimal_memory: true,
                        wake_on_inference: true,
                        mesh_networking: true,
                        target_platform: IoTPlatform::ESP32,
                    };
                    optimizer.configure_iot(iot_opts);
                    let metrics = optimizer.optimize_for_target(EdgeTarget::IoT)?;
                    let iot_time = start.elapsed();

                    println!("  ✅ IoT Performance: {:.2}x speedup", metrics.performance_improvement);
                    println!("  ✅ Memory reduction: {:.1}%", metrics.memory_reduction_ratio * 100.0);
                    println!("  ✅ Power efficiency: {:.2}x improvement", metrics.power_efficiency_gain);
                    println!("  ✅ Optimization time: {:?}", iot_time);
                    println!("  ✅ Memory footprint: {}KB",
                    metrics.target_specific.get("memory_footprint_kb")
                    .map(|v| format!("{}", *v as u32))
                    .unwrap_or_else(|| "N/A".to_string()));

                    if metrics.power_efficiency_gain >= 10.0 {
                        println!("  🎯 IoT power efficiency target met!");
                        } else {
                            println!("  ⚠️  IoT power efficiency target not fully achieved (target: 10.0x)");
                        }

                        // Summary
                        println!("\n📊 Performance Summary");
                        println!("=====================");
                        println!("Platform        | Performance | Power Eff. | Memory Red. | Status");
                        println!("----------------|-------------|------------|-------------|--------");
                        println!("ARM NEON        | {:.2}x        | {:.2}x        | {:.1}%        | {}",
                        optimizer.get_all_metrics().get(&EdgeTarget::ARM).map(|m| m.performance_improvement).unwrap_or(0.0),
                        optimizer.get_all_metrics().get(&EdgeTarget::ARM).map(|m| m.power_efficiency_gain).unwrap_or(0.0),
                        optimizer.get_all_metrics().get(&EdgeTarget::ARM).map(|m| m.memory_reduction_ratio * 100.0).unwrap_or(0.0),
                        if optimizer.get_all_metrics().get(&EdgeTarget::ARM).map(|m| m.performance_improvement).unwrap_or(0.0) >= 2.5 { "✅" } else { "⚠️" });

                        println!("RISC-V RVV      | {:.2}x        | {:.2}x        | {:.1}%        | {}",
                        optimizer.get_all_metrics().get(&EdgeTarget::RISCV).map(|m| m.performance_improvement).unwrap_or(0.0),
                        optimizer.get_all_metrics().get(&EdgeTarget::RISCV).map(|m| m.power_efficiency_gain).unwrap_or(0.0),
                        optimizer.get_all_metrics().get(&EdgeTarget::RISCV).map(|m| m.memory_reduction_ratio * 100.0).unwrap_or(0.0),
                        if optimizer.get_all_metrics().get(&EdgeTarget::RISCV).map(|m| m.performance_improvement).unwrap_or(0.0) >= 4.8 { "✅" } else { "⚠️" });

                        println!("WASM SIMD       | {:.2}x        | {:.2}x        | {:.1}%        | {}",
                        optimizer.get_all_metrics().get(&EdgeTarget::WASM).map(|m| m.performance_improvement).unwrap_or(0.0),
                        optimizer.get_all_metrics().get(&EdgeTarget::WASM).map(|m| m.power_efficiency_gain).unwrap_or(0.0),
                        optimizer.get_all_metrics().get(&EdgeTarget::WASM).map(|m| m.memory_reduction_ratio * 100.0).unwrap_or(0.0),
                        if optimizer.get_all_metrics().get(&EdgeTarget::WASM).map(|m| m.performance_improvement).unwrap_or(0.0) >= 1.8 { "✅" } else { "⚠️" });

                        println!("Mobile GPU      | {:.2}x        | {:.2}x        | {:.1}%        | {}",
                        optimizer.get_all_metrics().get(&EdgeTarget::MobileGPU).map(|m| m.performance_improvement).unwrap_or(0.0),
                        optimizer.get_all_metrics().get(&EdgeTarget::MobileGPU).map(|m| m.power_efficiency_gain).unwrap_or(0.0),
                        optimizer.get_all_metrics().get(&EdgeTarget::MobileGPU).map(|m| m.memory_reduction_ratio * 100.0).unwrap_or(0.0),
                        if optimizer.get_all_metrics().get(&EdgeTarget::MobileGPU).map(|m| m.performance_improvement).unwrap_or(0.0) >= 4.0 { "✅" } else { "⚠️" });

                        println!("IoT ESP32       | {:.2}x        | {:.1}x       | {:.1}%        | {}",
                        optimizer.get_all_metrics().get(&EdgeTarget::IoT).map(|m| m.performance_improvement).unwrap_or(0.0),
                        optimizer.get_all_metrics().get(&EdgeTarget::IoT).map(|m| m.power_efficiency_gain).unwrap_or(0.0),
                        optimizer.get_all_metrics().get(&EdgeTarget::IoT).map(|m| m.memory_reduction_ratio * 100.0).unwrap_or(0.0),
                        if optimizer.get_all_metrics().get(&EdgeTarget::IoT).map(|m| m.power_efficiency_gain).unwrap_or(0.0) >= 10.0 { "✅" } else { "⚠️" });

                        println!("\n🌟 Edge-Aware Training System Validation Complete!");
                        println!("Ready for production deployment across universal edge platforms!");

                        Ok(())
                    }