foxhunt/tests/benches/small_batch_performance.rs

//! Small Batch Performance Benchmark
//!
//! Validates the optimizations for small batch order processing
//! Target: 10K+ orders/sec (sub-100μs latency) for 1-10 order batches

use criterion::{black_box, criterion_group, criterion_main, BenchmarkId, Criterion};
use std::time::{Duration, Instant};
use common::OrderSide;
use common::OrderType;
use trading_engine::{
    lockfree::{BatchMode, SmallBatchOrdersSoA, SmallBatchRing},
    prelude::*,
};

/// Benchmark small batch processor vs standard processing
fn benchmark_small_batch_vs_standard(c: &mut Criterion) {
    let mut group = c.benchmark_group("small_batch_vs_standard");
    group.measurement_time(Duration::from_secs(10));

    for batch_size in [1, 2, 4, 8, 10].iter() {
        // Small batch optimized processor
        group.bench_with_input(
            BenchmarkId::new("optimized_processor", batch_size),
            batch_size,
            |b, &batch_size| {
                let mut processor = SmallBatchProcessor::new();

                b.iter_custom(|iters| {
                    let mut total_duration = Duration::from_nanos(0);

                    for i in 0..iters {
                        let start = Instant::now();

                        // Add orders to batch
                        for j in 0..batch_size {
                            let order = OrderRequest::new(
                                (i * batch_size + j) as u64,
                                "BTCUSD",
                                if j % 2 == 0 { Side::Buy } else { Side::Sell },
                                OrderType::Limit,
                                1000.0 + j as f64,
                                50000.0 + (j as f64 * 0.01),
                            );
                            processor.add_order(order).expect("Failed to add order");
                        }

                        // Process batch
                        let _result = processor.process_batch().expect("Failed to process batch");

                        let end = Instant::now();
                        total_duration += end.duration_since(start);

                        black_box(&_result);
                    }

                    total_duration
                });
            },
        );

        // Standard processing (simulated)
        group.bench_with_input(
            BenchmarkId::new("standard_processing", batch_size),
            batch_size,
            |b, &batch_size| {
                b.iter_custom(|iters| {
                    let mut total_duration = Duration::from_nanos(0);

                    for i in 0..iters {
                        let start = Instant::now();

                        // Simulate standard order processing overhead
                        for j in 0..batch_size {
                            // Simulate heap allocation
                            let order_data = vec![(i * batch_size + j) as u64, 50000 + j, 1000 + j];

                            // Simulate validation
                            let _valid = order_data[1] > 0 && order_data[2] > 0;

                            // Simulate atomic operations (expensive)
                            let counter = std::sync::atomic::AtomicU64::new(0);
                            counter.fetch_add(1, std::sync::atomic::Ordering::SeqCst);
                            let _count = counter.load(std::sync::atomic::Ordering::SeqCst);

                            black_box(&order_data);
                        }

                        let end = Instant::now();
                        total_duration += end.duration_since(start);
                    }

                    total_duration
                });
            },
        );
    }

    group.finish();
}

/// Benchmark lock-free ring buffer optimizations
fn benchmark_lockfree_optimizations(c: &mut Criterion) {
    let mut group = c.benchmark_group("lockfree_optimizations");
    group.measurement_time(Duration::from_secs(5));

    // Standard lock-free ring buffer
    group.bench_function("standard_lockfree", |b| {
        let buffer = LockFreeRingBuffer::<u64>::new(1024).expect("Failed to create buffer");

        b.iter_custom(|iters| {
            let mut total_duration = Duration::from_nanos(0);

            for i in 0..iters {
                let start = Instant::now();

                // Push small batch (1-8 items) one at a time
                for j in 0..8 {
                    let _ = buffer.try_push(i * 8 + j);
                }

                // Pop small batch one at a time
                for _ in 0..8 {
                    let _ = buffer.try_pop();
                }

                let end = Instant::now();
                total_duration += end.duration_since(start);
            }

            total_duration
        });
    });

    // Optimized small batch ring buffer
    group.bench_function("optimized_small_batch", |b| {
        let buffer = SmallBatchRing::<u64>::new(1024, BatchMode::SingleThreaded)
            .expect("Failed to create buffer");

        b.iter_custom(|iters| {
            let mut total_duration = Duration::from_nanos(0);

            for i in 0..iters {
                let start = Instant::now();

                // Push small batch as single operation
                let items: Vec<u64> = (0..8).map(|j| i * 8 + j).collect();
                let _ = buffer.push_batch(&items);

                // Pop small batch as single operation
                let mut output = [0u64; 8];
                let _ = buffer.pop_batch(&mut output);

                let end = Instant::now();
                total_duration += end.duration_since(start);

                black_box(&output);
            }

            total_duration
        });
    });

    group.finish();
}

/// Benchmark SIMD optimizations for small batches
fn benchmark_simd_optimizations(c: &mut Criterion) {
    let mut group = c.benchmark_group("simd_optimizations");
    group.measurement_time(Duration::from_secs(5));

    // Test structure-of-arrays layout
    group.bench_function("structure_of_arrays", |b| {
        b.iter_custom(|iters| {
            let mut total_duration = Duration::from_nanos(0);

            for _i in 0..iters {
                let start = Instant::now();

                let mut soa = SmallBatchOrdersSoA::new();

                // Add orders in SoA layout
                for j in 0..8 {
                    soa.add_order(
                        j as u64,
                        0x123456 + j as u64,
                        j % 2,
                        1,
                        1000.0 + j as f64,
                        50000.0 + j as f64,
                        1000 + j as u64,
                    );
                }

                // Calculate total notional using SIMD
                #[cfg(target_arch = "x86_64")]
                let _total_notional = soa.calculate_total_notional_simd();

                #[cfg(not(target_arch = "x86_64"))]
                let _total_notional = soa.calculate_total_notional_scalar();

                let end = Instant::now();
                total_duration += end.duration_since(start);

                black_box(&soa);
            }

            total_duration
        });
    });

    // Test array-of-structures layout (standard)
    group.bench_function("array_of_structures", |b| {
        // Use canonical Order types from common module
        use common::OrderId;
use common::OrderSide;
use common::OrderType;
    
        #[derive(Clone, Copy)]
        struct BenchOrder {
            order_id: u64,
            symbol_hash: u64,
            side: u8,
            order_type: u8,
            quantity: f64,
            price: f64,
            timestamp: u64,
        }

        b.iter_custom(|iters| {
            let mut total_duration = Duration::from_nanos(0);

            for _i in 0..iters {
                let start = Instant::now();

                let mut orders = Vec::with_capacity(8);
                
                // Add orders in AoS layout
                for j in 0..8 {
                    orders.push(BenchOrder {
                        order_id: j as u64,
                        symbol_hash: 0x123456 + j as u64,
                        side: j % 2,
                        order_type: 1,
                        quantity: 1000.0 + j as f64,
                        price: 50000.0 + j as f64,
                        timestamp: 1000 + j as u64,
                    });
                }

                // Calculate total notional (scalar)
                let _total_notional: f64 = orders.iter().map(|o| o.price * o.quantity).sum();

                let end = Instant::now();
                total_duration += end.duration_since(start);

                black_box(&orders);
            }

            total_duration
        });
    });

    group.finish();
}

/// Benchmark memory allocation patterns
fn benchmark_memory_allocation(c: &mut Criterion) {
    let mut group = c.benchmark_group("memory_allocation");
    group.measurement_time(Duration::from_secs(5));

    // Stack allocation
    group.bench_function("stack_allocation", |b| {
        b.iter_custom(|iters| {
            let mut total_duration = Duration::from_nanos(0);

            for i in 0..iters {
                let start = Instant::now();

                // Stack allocated array
                let mut orders = [0u64; 10];
                for j in 0..10 {
                    orders[j] = i * 10 + j as u64;
                }

                // Process stack array
                let _sum: u64 = orders.iter().sum();

                let end = Instant::now();
                total_duration += end.duration_since(start);

                black_box(&orders);
            }

            total_duration
        });
    });

    // Heap allocation
    group.bench_function("heap_allocation", |b| {
        b.iter_custom(|iters| {
            let mut total_duration = Duration::from_nanos(0);

            for i in 0..iters {
                let start = Instant::now();

                // Heap allocated vector
                let mut orders = Vec::with_capacity(10);
                for j in 0..10 {
                    orders.push(i * 10 + j);
                }

                // Process heap vector
                let _sum: u64 = orders.iter().sum();

                let end = Instant::now();
                total_duration += end.duration_since(start);

                black_box(&orders);
            }

            total_duration
        });
    });

    group.finish();
}

/// Comprehensive latency validation for small batches
fn benchmark_latency_validation(c: &mut Criterion) {
    let mut group = c.benchmark_group("latency_validation");
    group.measurement_time(Duration::from_secs(15));

    group.bench_function("target_validation", |b| {
        let mut processor = SmallBatchProcessor::new();

        b.iter_custom(|iters| {
            let mut latencies = Vec::with_capacity(iters as usize);
            let mut under_100us = 0u64;
            let mut under_50us = 0u64;

            for i in 0..iters {
                let start = Instant::now();

                // Create small batch (5 orders)
                for j in 0..5 {
                    let order = OrderRequest::new(
                        (i * 5 + j) as u64,
                        "EURUSD",
                        if j % 2 == 0 { Side::Buy } else { Side::Sell },
                        OrderType::Limit,
                        1000.0 + j as f64,
                        1.1000 + (j as f64 * 0.0001),
                    );
                    processor.add_order(order).expect("Failed to add order");
                }

                // Process batch
                let _result = processor.process_batch().expect("Failed to process batch");

                let latency = start.elapsed();
                let latency_us = latency.as_micros() as u64;

                latencies.push(latency_us);

                if latency_us <= 100 {
                    under_100us += 1;
                }
                if latency_us <= 50 {
                    under_50us += 1;
                }

                black_box(&_result);
            }

            // Calculate statistics
            if !latencies.is_empty() {
                latencies.sort_unstable();
                let avg_latency = latencies.iter().sum::<u64>() / latencies.len() as u64;
                let p50_latency = latencies[latencies.len() / 2];
                let p95_latency = latencies[(latencies.len() * 95) / 100];
                let p99_latency = latencies[(latencies.len() * 99) / 100];

                let percent_under_100us = (under_100us as f64 / iters as f64) * 100.0;
                let percent_under_50us = (under_50us as f64 / iters as f64) * 100.0;

                eprintln!("\nSmall Batch Latency Results:");
                eprintln!("  Average latency: {}μs", avg_latency);
                eprintln!("  P50 latency: {}μs", p50_latency);
                eprintln!("  P95 latency: {}μs", p95_latency);
                eprintln!("  P99 latency: {}μs", p99_latency);
                eprintln!("  {:.1}% under 100μs target", percent_under_100us);
                eprintln!("  {:.1}% under 50μs stretch target", percent_under_50us);

                // Calculate throughput
                let throughput = if avg_latency > 0 {
                    1_000_000.0 / avg_latency as f64 // Convert μs to ops/sec
                } else {
                    0.0
                };
                eprintln!("  Throughput: {:.0} orders/sec", throughput);

                if throughput >= 10000.0 {
                    eprintln!("  ✅ TARGET ACHIEVED: 10K+ orders/sec");
                } else {
                    eprintln!("  ❌ TARGET MISSED: {:.0} < 10K orders/sec", throughput);
                }
            }

            // Return total processing time for Criterion
            Duration::from_micros(latencies.iter().sum::<u64>())
        });
    });

    group.finish();
}

criterion_group!(
    small_batch_benches,
    benchmark_small_batch_vs_standard,
    benchmark_lockfree_optimizations,
    benchmark_simd_optimizations,
    benchmark_memory_allocation,
    benchmark_latency_validation
);

criterion_main!(small_batch_benches);