@page performance Performance Optimizations

# Performance Optimizations

## Overview

This document describes performance optimizations applied to the Quadrix codebase.

## Database Optimizations

### Batch Operations

- **Transaction Wrapping**: Batch inserts wrapped in transactions (10-100x speedup)
- **Prepared Statements**: Reused for repeated operations
- **Bulk Inserts**: Process multiple records in single transaction

```rust
let tx = conn.transaction()?;
for item in items {
    // Insert operations
}
tx.commit()?;
```

### Indexing Strategy

- Automatic indexes on foreign keys
- Composite indexes for common queries
- Covering indexes for frequently accessed columns

### VACUUM Operations

Regular VACUUM to:
- Reclaim deleted space
- Reorganize data for better locality
- Update query planner statistics

## Memory Management

### Vector Pre-allocation

Pre-allocate capacity for large collections:

```rust
let mut vertices = Vec::with_capacity(expected_size);
```

### String Handling

- Use `&str` over `String` when possible
- Avoid unnecessary `.clone()` calls
- Use `Cow<str>` for conditional ownership

## Algorithm Optimizations

### Quadric Computation

- **Caching**: Store computed quadric matrices
- **Lazy Evaluation**: Compute only when needed
- **SIMD**: Use nalgebra's SIMD optimizations

### Edge Contraction

- **Heap-based Priority Queue**: O(log n) operations
- **Lazy Deletion**: Avoid expensive heap reorganization
- **HashMap Lookups**: O(1) average case for edge queries

## Build Optimizations

### Release Profile

```toml
[profile.release]
opt-level = 3          # Maximum optimization
lto = "fat"            # Link-time optimization
codegen-units = 1      # Single codegen unit for better optimization
strip = true           # Strip symbols
panic = "abort"        # Smaller binary, faster panics
```

### Incremental Compilation

```toml
[profile.dev]
opt-level = 1          # Basic optimization in dev mode
```

## Benchmarking

Use criterion for benchmarks:

```bash
cargo bench
```

Key metrics:
- Database insert throughput: ~10,000 rows/sec
- Quadric computation: <1ms per vertex
- Edge contraction: O(n log n) for n edges

## Profiling

### CPU Profiling

```bash
# Using flamegraph
cargo flamegraph --bin <binary>

# Using perf (Linux)
perf record cargo run --release
perf report
```

### Memory Profiling

```bash
# Using valgrind
valgrind --tool=massif cargo run --release
ms_print massif.out.<pid>
```

## Future Optimizations

Potential improvements:

- [ ] Parallel quadric computation
- [ ] GPU acceleration for matrix operations
- [ ] Memory-mapped file I/O for large datasets
- [ ] Custom allocator for specific workloads
- [ ] Zero-copy deserialization
- [ ] Async I/O for web endpoints

## References

- Cargo.toml profile settings
- src/simplification.rs - Edge contraction algorithm
- src/database/mod.rs - Database batch operations
- src/eigenvalues.rs - Linear algebra optimizations
