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Performance Optimization

LoSkroefie edited this page Jan 19, 2025 · 1 revision

Performance Optimization Guide

Overview

This guide provides comprehensive information about optimizing FLEXON's performance in various scenarios.

Memory Management

1. Buffer Pooling

public class BufferManager
{
    private readonly ArrayPool<byte> _arrayPool;
    private readonly ObjectPool<FlexonWriter> _writerPool;
    private readonly ObjectPool<FlexonReader> _readerPool;

    public BufferManager()
    {
        _arrayPool = ArrayPool<byte>.Shared;
        _writerPool = ObjectPool<FlexonWriter>.Create();
        _readerPool = ObjectPool<FlexonReader>.Create();
    }

    public async Task ProcessData<T>(T data)
    {
        var buffer = _arrayPool.Rent(8192);
        try
        {
            var writer = _writerPool.Get();
            try
            {
                writer.Reset(buffer);
                writer.WriteValue(data);
                await ProcessBuffer(buffer);
            }
            finally
            {
                _writerPool.Return(writer);
            }
        }
        finally
        {
            _arrayPool.Return(buffer);
        }
    }
}

2. Zero-Copy Operations

public class ZeroCopyProcessor
{
    private readonly IFlexonSerializer _serializer;

    public void ProcessLargeData(ReadOnlySpan<byte> data)
    {
        var reader = new FlexonReader(data);
        while (!reader.EndOfData)
        {
            var item = reader.ReadValue<DataItem>();
            ProcessItem(item);
        }
    }

    public void WriteData<T>(T data, Span<byte> buffer)
    {
        var writer = new FlexonWriter(buffer);
        writer.WriteValue(data);
    }
}

3. Memory Monitoring

public class MemoryMonitor
{
    private readonly PerformanceCounter _memoryCounter;
    private readonly long _memoryThreshold;

    public async Task<bool> CheckMemoryUsage()
    {
        var currentUsage = _memoryCounter.NextValue();
        if (currentUsage > _memoryThreshold)
        {
            await TriggerGarbageCollection();
            return false;
        }
        return true;
    }

    public async Task MonitorOperation(Func<Task> operation)
    {
        var before = GC.GetTotalMemory(false);
        await operation();
        var after = GC.GetTotalMemory(false);
        
        LogMemoryUsage(after - before);
    }
}

SIMD Optimization

1. Vector Operations

public class VectorProcessor
{
    public void ProcessVectors(Span<Vector3> vectors)
    {
        if (Vector.IsHardwareAccelerated)
        {
            ProcessVectorsSimd(vectors);
        }
        else
        {
            ProcessVectorsScalar(vectors);
        }
    }

    private void ProcessVectorsSimd(Span<Vector3> vectors)
    {
        var vectorCount = vectors.Length / 4;
        for (int i = 0; i < vectorCount; i++)
        {
            ref var v = ref Unsafe.As<Vector3, Vector<float>>(
                ref vectors[i * 4]);
            v = Vector.Multiply(v, new Vector<float>(2.0f));
        }
    }
}

2. Batch Processing

public class BatchProcessor
{
    private readonly int _batchSize;
    private readonly IFlexonSerializer _serializer;

    public async Task ProcessItems<T>(IEnumerable<T> items)
    {
        var options = new FlexonOptions { EnableSimd = true };
        
        foreach (var batch in items.Chunk(_batchSize))
        {
            var binary = _serializer.Serialize(batch, options);
            await ProcessBatch(binary);
        }
    }
}

Threading Optimization

1. Parallel Processing

public class ParallelProcessor
{
    private readonly ParallelOptions _options;
    private readonly IFlexonSerializer _serializer;

    public async Task ProcessDataParallel<T>(IEnumerable<T> items)
    {
        var partitioner = Partitioner.Create(items);
        
        await Parallel.ForEachAsync(
            partitioner,
            _options,
            async (partition, ct) =>
            {
                foreach (var item in partition)
                {
                    await ProcessItem(item, ct);
                }
            });
    }
}

2. Thread Pool Configuration

public class ThreadPoolConfig
{
    public static void OptimizeThreadPool()
    {
        ThreadPool.GetMinThreads(out int workerThreads, out int completionPortThreads);
        
        // Increase minimum threads based on processor count
        int newWorkerThreads = Environment.ProcessorCount * 2;
        int newCompletionPortThreads = Environment.ProcessorCount * 2;
        
        ThreadPool.SetMinThreads(newWorkerThreads, newCompletionPortThreads);
    }

    public static async Task MonitorThreadPool()
    {
        while (true)
        {
            ThreadPool.GetAvailableThreads(out int workerThreads, out int completionPortThreads);
            LogThreadPoolStats(workerThreads, completionPortThreads);
            await Task.Delay(1000);
        }
    }
}

IO Optimization

1. Asynchronous IO

public class AsyncIOManager
{
    private readonly IFlexonSerializer _serializer;

    public async Task ProcessFile(string path)
    {
        using var fileStream = new FileStream(
            path,
            FileMode.Open,
            FileAccess.Read,
            FileShare.Read,
            bufferSize: 4096,
            useAsync: true);

        var reader = new FlexonStreamReader(fileStream);
        await foreach (var item in reader.ReadAsync<DataItem>())
        {
            await ProcessItem(item);
        }
    }
}

2. Memory-Mapped Files

public class MemoryMappedManager
{
    public async Task ProcessLargeFile(string path)
    {
        using var mmf = MemoryMappedFile.CreateFromFile(path);
        using var accessor = mmf.CreateViewAccessor();
        
        unsafe
        {
            byte* ptr = null;
            accessor.SafeMemoryMappedViewHandle.AcquirePointer(ref ptr);
            try
            {
                var span = new Span<byte>(ptr, (int)accessor.Capacity);
                ProcessData(span);
            }
            finally
            {
                accessor.SafeMemoryMappedViewHandle.ReleasePointer();
            }
        }
    }
}

Network Optimization

1. Connection Pooling

public class ConnectionPool
{
    private readonly ConcurrentQueue<NetworkConnection> _pool;
    private readonly SemaphoreSlim _poolSemaphore;

    public async Task<NetworkConnection> GetConnection()
    {
        await _poolSemaphore.WaitAsync();
        try
        {
            if (_pool.TryDequeue(out var connection))
            {
                return connection;
            }
            return CreateNewConnection();
        }
        finally
        {
            _poolSemaphore.Release();
        }
    }

    public void ReturnConnection(NetworkConnection connection)
    {
        if (connection.IsHealthy)
        {
            _pool.Enqueue(connection);
        }
        else
        {
            connection.Dispose();
        }
    }
}

2. Compression Strategies

public class NetworkCompression
{
    private readonly IFlexonSerializer _serializer;

    public byte[] CompressForNetwork<T>(T data, NetworkQuality quality)
    {
        var options = new FlexonOptions
        {
            EnableCompression = true,
            CompressionLevel = quality switch
            {
                NetworkQuality.Low => CompressionLevel.Optimal,
                NetworkQuality.Medium => CompressionLevel.Balanced,
                NetworkQuality.High => CompressionLevel.Fastest,
                _ => CompressionLevel.NoCompression
            }
        };

        return _serializer.Serialize(data, options);
    }
}

Caching Strategies

1. Type Cache

public class TypeCache
{
    private readonly ConcurrentDictionary<Type, TypeInfo> _cache;
    private readonly ConcurrentDictionary<int, Type> _typeCodeCache;

    public TypeInfo GetTypeInfo(Type type)
    {
        return _cache.GetOrAdd(type, CreateTypeInfo);
    }

    public Type GetTypeFromCode(int typeCode)
    {
        return _typeCodeCache.GetOrAdd(typeCode, LoadType);
    }
}

2. Object Cache

public class ObjectCache
{
    private readonly MemoryCache _cache;
    private readonly IFlexonSerializer _serializer;

    public async Task<T> GetOrCreate<T>(string key, Func<Task<T>> factory)
    {
        if (_cache.TryGetValue(key, out byte[] cached))
        {
            return _serializer.Deserialize<T>(cached);
        }

        var value = await factory();
        var binary = _serializer.Serialize(value);
        
        _cache.Set(key, binary, TimeSpan.FromMinutes(30));
        return value;
    }
}

Profiling and Monitoring

1. Performance Monitoring

public class PerformanceMonitor
{
    private readonly Metrics _metrics;
    private readonly DiagnosticSource _diagnostics;

    public async Task<T> TrackOperation<T>(
        string operation,
        Func<Task<T>> action)
    {
        using var activity = _diagnostics.StartActivity(operation);
        var sw = Stopwatch.StartNew();
        
        try
        {
            var result = await action();
            _metrics.RecordSuccess(operation, sw.ElapsedMilliseconds);
            return result;
        }
        catch (Exception ex)
        {
            _metrics.RecordError(operation, ex);
            throw;
        }
    }
}

2. Memory Profiling

public class MemoryProfiler
{
    private readonly ILogger _logger;

    public async Task ProfileOperation(Func<Task> operation)
    {
        var before = GC.GetTotalMemory(true);
        using var session = StartMemorySession();
        
        await operation();
        
        var after = GC.GetTotalMemory(true);
        var diff = after - before;
        
        _logger.LogInformation(
            "Memory usage: {Diff} bytes, Gen0: {Gen0}, Gen1: {Gen1}, Gen2: {Gen2}",
            diff,
            GC.CollectionCount(0),
            GC.CollectionCount(1),
            GC.CollectionCount(2));
    }
}

Best Practices

  1. Memory Management

    • Use buffer pooling for frequent allocations
    • Implement proper disposal patterns
    • Monitor memory usage
    • Use appropriate buffer sizes
  2. Threading

    • Configure thread pool appropriately
    • Use parallel processing when beneficial
    • Implement proper synchronization
    • Monitor thread usage
  3. IO Operations

    • Use async IO
    • Implement proper buffering
    • Use memory-mapped files for large files
    • Monitor IO performance
  4. Network Operations

    • Use connection pooling
    • Implement proper compression
    • Monitor network performance
    • Handle network errors
  5. Caching

    • Cache frequently used data
    • Implement proper cache invalidation
    • Monitor cache hit rates
    • Use appropriate cache sizes
  6. Monitoring

    • Implement proper logging
    • Monitor performance metrics
    • Track memory usage
    • Profile critical operations

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