Performance API

SIMD Optimizations

Enabling SIMD

// Enable SIMD optimizations globally
advancegg.EnableSIMD(true)

// Check SIMD support
if advancegg.SIMDSupported() {
    fmt.Println("SIMD optimizations available")
    fmt.Printf("SIMD instruction set: %s\n", advancegg.GetSIMDInstructionSet())
}

// Enable specific SIMD features
advancegg.EnableSIMDFeature(advancegg.SIMDFeatureSSE2, true)
advancegg.EnableSIMDFeature(advancegg.SIMDFeatureAVX2, true)
advancegg.EnableSIMDFeature(advancegg.SIMDFeatureAVX512, true)

// Per-context SIMD settings
dc.SetSIMDEnabled(true)
dc.SetSIMDInstructionSet(advancegg.SIMDInstructionSetAVX2)

SIMD-Optimized Operations

// Image processing with SIMD
blurred := advancegg.ApplyGaussianBlurSIMD(img, 5.0)
resized := advancegg.ResizeImageSIMD(img, 1920, 1080, advancegg.ResizeBicubic)

// Color space conversions
rgbToHsv := advancegg.ConvertRGBToHSVSIMD(rgbImage)
hsvToRgb := advancegg.ConvertHSVToRGBSIMD(hsvImage)

// Batch operations
images := []image.Image{img1, img2, img3, img4}
results := advancegg.BatchProcessSIMD(images, func(img image.Image) image.Image {
    return advancegg.ApplyBrightness(img, 1.2)
})

// Vector operations
points := []advancegg.Point{{100, 100}, {200, 200}, {300, 300}}
transformed := advancegg.TransformPointsSIMD(points, matrix)

Memory Management

Memory Pooling

// Enable memory pooling
advancegg.EnableMemoryPooling(true)

// Configure pool sizes
advancegg.SetMemoryPoolSize(advancegg.PoolTypeImage, 100*1024*1024) // 100MB for images
advancegg.SetMemoryPoolSize(advancegg.PoolTypeContext, 50*1024*1024) // 50MB for contexts
advancegg.SetMemoryPoolSize(advancegg.PoolTypePath, 10*1024*1024)    // 10MB for paths

// Get pool statistics
stats := advancegg.GetMemoryPoolStats()
fmt.Printf("Image pool: %d/%d bytes used\n", stats.ImagePool.Used, stats.ImagePool.Total)
fmt.Printf("Context pool: %d/%d bytes used\n", stats.ContextPool.Used, stats.ContextPool.Total)

// Manual pool management
advancegg.ClearMemoryPool(advancegg.PoolTypeImage)
advancegg.CompactMemoryPools()

Resource Management

// Automatic resource cleanup
defer advancegg.CleanupResources()

// Manual resource management
resource := advancegg.AcquireResource(advancegg.ResourceTypeImage, width*height*4)
defer advancegg.ReleaseResource(resource)

// Context resource management
dc := advancegg.NewContext(800, 600)
defer dc.Dispose() // Explicit cleanup

// Image cache management
advancegg.SetImageCacheSize(200 * 1024 * 1024) // 200MB cache
advancegg.ClearImageCache()

// Font cache management
advancegg.SetFontCacheSize(50 * 1024 * 1024) // 50MB cache
advancegg.ClearFontCache()

Garbage Collection Optimization

// Reduce GC pressure
advancegg.SetGCOptimizationLevel(advancegg.GCOptimizationHigh)

// Pre-allocate buffers
buffer := advancegg.AllocateBuffer(width * height * 4)
defer advancegg.FreeBuffer(buffer)

// Reuse contexts
contextPool := advancegg.NewContextPool(10) // Pool of 10 contexts
ctx := contextPool.Get()
defer contextPool.Put(ctx)

// Batch allocations
allocator := advancegg.NewBatchAllocator()
defer allocator.FreeAll()

img1 := allocator.AllocateImage(800, 600)
img2 := allocator.AllocateImage(1920, 1080)

Caching System

Automatic Caching

// Enable automatic caching
advancegg.EnableAutomaticCaching(true)

// Configure cache policies
advancegg.SetCachePolicy(advancegg.CachePolicyLRU) // Least Recently Used
advancegg.SetCachePolicy(advancegg.CachePolicyLFU) // Least Frequently Used
advancegg.SetCachePolicy(advancegg.CachePolicyTTL) // Time To Live

// Set cache sizes
advancegg.SetCacheSize(advancegg.CacheTypeImage, 500*1024*1024)    // 500MB
advancegg.SetCacheSize(advancegg.CacheTypeFont, 100*1024*1024)     // 100MB
advancegg.SetCacheSize(advancegg.CacheTypeGradient, 50*1024*1024)  // 50MB
advancegg.SetCacheSize(advancegg.CacheTypePath, 25*1024*1024)      // 25MB

// Cache statistics
cacheStats := advancegg.GetCacheStatistics()
fmt.Printf("Image cache hit rate: %.2f%%\n", cacheStats.ImageCache.HitRate*100)
fmt.Printf("Font cache hit rate: %.2f%%\n", cacheStats.FontCache.HitRate*100)

Manual Caching

// Cache expensive operations
cacheKey := "processed_image_" + imageHash
if cached := advancegg.GetFromCache(cacheKey); cached != nil {
    return cached.(image.Image)
}

// Perform expensive operation
processed := expensiveImageProcessing(img)

// Store in cache
advancegg.StoreInCache(cacheKey, processed, 3600) // Cache for 1 hour

// Preload cache
advancegg.PreloadCache([]string{"common_image_1.jpg", "common_image_2.jpg"})

// Cache warming
advancegg.WarmCache(func() {
    // Perform operations that should be cached
    advancegg.LoadFont("arial.ttf", 12)
    advancegg.LoadFont("arial.ttf", 14)
    advancegg.LoadFont("arial.ttf", 16)
})

Parallel Processing

Multi-threading

// Set number of worker threads
advancegg.SetWorkerThreads(runtime.NumCPU())

// Parallel image processing
images := []image.Image{img1, img2, img3, img4}
results := advancegg.ProcessImagesParallel(images, func(img image.Image) image.Image {
    return advancegg.ApplyGaussianBlur(img, 3.0)
})

// Parallel drawing operations
dc := advancegg.NewContext(1920, 1080)
advancegg.DrawParallel(dc, func(ctx *advancegg.Context, threadID int) {
    // Each thread draws different parts
    startY := threadID * (1080 / advancegg.GetWorkerThreads())
    endY := (threadID + 1) * (1080 / advancegg.GetWorkerThreads())
    
    for y := startY; y < endY; y++ {
        // Draw scanline
        drawComplexScanline(ctx, y)
    }
})

// Thread-safe operations
mutex := advancegg.NewRenderMutex()
go func() {
    mutex.Lock()
    defer mutex.Unlock()
    dc.DrawCircle(100, 100, 50)
    dc.Fill()
}()

GPU Acceleration

// Check GPU support
if advancegg.GPUSupported() {
    fmt.Printf("GPU: %s\n", advancegg.GetGPUInfo())
    advancegg.EnableGPUAcceleration(true)
}

// GPU-accelerated operations
gpuBlurred := advancegg.ApplyGaussianBlurGPU(img, 5.0)
gpuResized := advancegg.ResizeImageGPU(img, 1920, 1080)

// GPU memory management
advancegg.SetGPUMemoryLimit(1024 * 1024 * 1024) // 1GB
advancegg.ClearGPUMemory()

// Batch GPU operations
gpuBatch := advancegg.NewGPUBatch()
gpuBatch.AddOperation(advancegg.NewBlurOperation(img1, 3.0))
gpuBatch.AddOperation(advancegg.NewBrightnessOperation(img2, 1.2))
gpuBatch.AddOperation(advancegg.NewContrastOperation(img3, 1.5))
results := gpuBatch.Execute()

Profiling and Debugging

Performance Profiling

// Enable profiling
profiler := advancegg.NewProfiler()
profiler.Start()

// Profile specific operations
profiler.BeginSection("image_processing")
processed := advancegg.ApplyGaussianBlur(img, 5.0)
profiler.EndSection("image_processing")

profiler.BeginSection("drawing")
dc.DrawCircle(400, 300, 100)
dc.Fill()
profiler.EndSection("drawing")

// Get profiling results
results := profiler.GetResults()
for _, section := range results.Sections {
    fmt.Printf("%s: %v (%.2f%%)\n", section.Name, section.Duration, section.Percentage)
}

// Memory profiling
memProfiler := advancegg.NewMemoryProfiler()
memProfiler.Start()
// ... operations ...
memStats := memProfiler.GetStats()
fmt.Printf("Peak memory usage: %d bytes\n", memStats.PeakUsage)

Performance Monitoring

// Real-time performance monitoring
monitor := advancegg.NewPerformanceMonitor()
monitor.SetUpdateInterval(100 * time.Millisecond)
monitor.Start()

// Get current metrics
metrics := monitor.GetCurrentMetrics()
fmt.Printf("FPS: %.1f\n", metrics.FPS)
fmt.Printf("Memory usage: %d MB\n", metrics.MemoryUsage/1024/1024)
fmt.Printf("GPU usage: %.1f%%\n", metrics.GPUUsage)

// Performance alerts
monitor.SetAlert(advancegg.AlertTypeMemoryUsage, 500*1024*1024, func(value float64) {
    fmt.Printf("High memory usage: %.1f MB\n", value/1024/1024)
})

monitor.SetAlert(advancegg.AlertTypeFPS, 30, func(value float64) {
    fmt.Printf("Low FPS: %.1f\n", value)
})

Debug Mode

// Enable debug mode
advancegg.SetDebugMode(true)
advancegg.SetDebugLevel(advancegg.DebugLevelVerbose)

// Debug visualization
dc.SetDebugVisualization(true)
dc.SetDebugShowBounds(true)
dc.SetDebugShowPaths(true)
dc.SetDebugShowTextMetrics(true)

// Debug output
advancegg.SetDebugOutput(os.Stdout)
advancegg.DebugPrint("Custom debug message")

// Performance warnings
advancegg.EnablePerformanceWarnings(true)
advancegg.SetPerformanceWarningThreshold(advancegg.WarningTypeSlowOperation, 100*time.Millisecond)

// Memory leak detection
advancegg.EnableMemoryLeakDetection(true)
leaks := advancegg.DetectMemoryLeaks()
if len(leaks) > 0 {
    fmt.Printf("Memory leaks detected: %d\n", len(leaks))
}

Benchmarking

Built-in Benchmarks

// Run standard benchmarks
results := advancegg.RunBenchmarks()
fmt.Printf("Drawing performance: %.2f ops/sec\n", results.DrawingOpsPerSecond)
fmt.Printf("Image processing: %.2f MP/sec\n", results.ImageProcessingMPPerSecond)
fmt.Printf("Text rendering: %.2f chars/sec\n", results.TextRenderingCharsPerSecond)

// Custom benchmarks
benchmark := advancegg.NewBenchmark("custom_operation")
benchmark.Run(1000, func() {
    // Operation to benchmark
    dc.DrawCircle(rand.Float64()*800, rand.Float64()*600, 50)
    dc.Fill()
})
fmt.Printf("Custom operation: %.2f ops/sec\n", benchmark.GetOpsPerSecond())

// Comparative benchmarks
comparison := advancegg.CompareBenchmarks(
    "SIMD vs Non-SIMD",
    func() { advancegg.ApplyGaussianBlurSIMD(img, 5.0) },
    func() { advancegg.ApplyGaussianBlur(img, 5.0) },
)
fmt.Printf("SIMD is %.2fx faster\n", comparison.SpeedupFactor)

Performance Testing

// Stress testing
stressTest := advancegg.NewStressTest()
stressTest.SetDuration(60 * time.Second)
stressTest.SetConcurrency(10)

stressTest.AddTest("drawing", func() {
    dc := advancegg.NewContext(800, 600)
    for i := 0; i < 1000; i++ {
        dc.DrawCircle(rand.Float64()*800, rand.Float64()*600, 10)
        dc.Fill()
    }
})

results := stressTest.Run()
fmt.Printf("Stress test results: %.2f ops/sec\n", results.OpsPerSecond)

// Load testing
loadTest := advancegg.NewLoadTest()
loadTest.SetRampUpTime(10 * time.Second)
loadTest.SetSustainTime(30 * time.Second)
loadTest.SetMaxConcurrency(100)

loadResults := loadTest.Run(func() {
    img := advancegg.LoadImage("test.jpg")
    processed := advancegg.ApplyGaussianBlur(img, 3.0)
    advancegg.SaveJPEG(processed, "output.jpg", 90)
})

fmt.Printf("Load test peak throughput: %.2f ops/sec\n", loadResults.PeakThroughput)

Optimization Best Practices

General Guidelines

Performance Tips

Enable SIMD: Use SIMD optimizations for image processing
Memory Pooling: Enable memory pooling for frequent allocations
Batch Operations: Group similar operations together
Cache Resources: Cache fonts, images, and gradients
Reuse Contexts: Avoid creating new contexts frequently
Optimize Image Sizes: Use appropriate resolutions
Profile Regularly: Identify bottlenecks early

Code Examples

// Efficient drawing loop
func efficientDrawing() {
    // Reuse context
    dc := advancegg.NewContext(800, 600)
    defer dc.Dispose()
    
    // Batch similar operations
    dc.SetRGB(1, 0, 0)
    for _, circle := range redCircles {
        dc.DrawCircle(circle.X, circle.Y, circle.Radius)
    }
    dc.Fill() // Single fill operation
    
    dc.SetRGB(0, 1, 0)
    for _, circle := range greenCircles {
        dc.DrawCircle(circle.X, circle.Y, circle.Radius)
    }
    dc.Fill()
}

// Efficient image processing
func efficientImageProcessing(images []image.Image) []image.Image {
    // Enable optimizations
    advancegg.EnableSIMD(true)
    advancegg.EnableMemoryPooling(true)
    
    // Process in parallel
    return advancegg.ProcessImagesParallel(images, func(img image.Image) image.Image {
        // Chain operations efficiently
        return advancegg.ApplyFilterChain(img, []advancegg.Filter{
            advancegg.NewGaussianBlurFilter(2.0),
            advancegg.NewBrightnessFilter(1.1),
            advancegg.NewContrastFilter(1.2),
        })
    })
}

Complete Examples

High-Performance Rendering

package main

import (
    "fmt"
    "runtime"
    "time"
    "github.com/GrandpaEJ/advancegg"
)

func main() {
    // Initialize performance optimizations
    setupPerformanceOptimizations()
    
    // Create profiler
    profiler := advancegg.NewProfiler()
    profiler.Start()
    
    // Perform high-performance rendering
    profiler.BeginSection("setup")
    dc := setupHighPerformanceContext()
    profiler.EndSection("setup")
    
    profiler.BeginSection("rendering")
    renderComplexScene(dc)
    profiler.EndSection("rendering")
    
    profiler.BeginSection("save")
    dc.SavePNG("high_performance_render.png")
    profiler.EndSection("save")
    
    // Print performance results
    results := profiler.GetResults()
    fmt.Printf("Total time: %v\n", results.TotalTime)
    for _, section := range results.Sections {
        fmt.Printf("%s: %v (%.1f%%)\n", 
            section.Name, section.Duration, section.Percentage)
    }
}

func setupPerformanceOptimizations() {
    // Enable all optimizations
    advancegg.EnableSIMD(true)
    advancegg.EnableMemoryPooling(true)
    advancegg.EnableAutomaticCaching(true)
    advancegg.SetWorkerThreads(runtime.NumCPU())
    
    // Configure memory pools
    advancegg.SetMemoryPoolSize(advancegg.PoolTypeImage, 200*1024*1024)
    advancegg.SetMemoryPoolSize(advancegg.PoolTypeContext, 100*1024*1024)
    
    // Configure caches
    advancegg.SetCacheSize(advancegg.CacheTypeFont, 50*1024*1024)
    advancegg.SetCacheSize(advancegg.CacheTypeGradient, 25*1024*1024)
    
    // Enable GPU if available
    if advancegg.GPUSupported() {
        advancegg.EnableGPUAcceleration(true)
    }
}

func setupHighPerformanceContext() *advancegg.Context {
    dc := advancegg.NewContext(1920, 1080)
    
    // Enable context-specific optimizations
    dc.SetSIMDEnabled(true)
    dc.SetMemoryPoolingEnabled(true)
    dc.SetCachingEnabled(true)
    
    return dc
}

func renderComplexScene(dc *advancegg.Context) {
    // Background gradient
    bg := advancegg.NewLinearGradient(0, 0, 1920, 1080)
    bg.AddColorStop(0, advancegg.RGB(0.1, 0.1, 0.2))
    bg.AddColorStop(1, advancegg.RGB(0.2, 0.1, 0.3))
    dc.SetFillStyle(bg)
    dc.DrawRectangle(0, 0, 1920, 1080)
    dc.Fill()
    
    // Render thousands of objects efficiently
    renderParticleSystem(dc, 10000)
    renderGeometry(dc, 1000)
    renderText(dc)
}

func renderParticleSystem(dc *advancegg.Context, count int) {
    // Batch particles by color for efficiency
    colors := []advancegg.Color{
        advancegg.RGB(1, 0.5, 0),
        advancegg.RGB(0.5, 1, 0),
        advancegg.RGB(0, 0.5, 1),
    }
    
    for _, color := range colors {
        dc.SetColor(color)
        for i := 0; i < count/len(colors); i++ {
            x := rand.Float64() * 1920
            y := rand.Float64() * 1080
            size := 1 + rand.Float64()*3
            dc.DrawCircle(x, y, size)
        }
        dc.Fill() // Single fill for all particles of this color
    }
}

API Reference

SIMD Optimizations

Enabling SIMD

SIMD-Optimized Operations

Memory Management

Memory Pooling

Resource Management

Garbage Collection Optimization

Caching System

Automatic Caching

Manual Caching

Parallel Processing

Multi-threading

GPU Acceleration

Profiling and Debugging

Performance Profiling

Performance Monitoring

Debug Mode

Benchmarking

Built-in Benchmarks

Performance Testing

Optimization Best Practices

General Guidelines

Performance Tips

Code Examples

Complete Examples

High-Performance Rendering