A ultra-low latency trading engine built with modern C++23, featuring GPU acceleration, coroutines, and sub-microsecond performance.
- Ultra-Low Latency: Sub-microsecond order matching with lock-free data structures
- Memory Optimized: Custom allocators and memory pools for zero-allocation trading
- SIMD Optimizations: Vectorized price calculations using AVX2/AVX-512
- Lock-Free Architecture: Atomic operations and memory ordering for maximum throughput
- High-Throughput UDP: Multicast market data feed handling
- Coroutine-Based: Async processing with C++20 coroutines
- Binary Protocol Support: FIX/FAST protocol parsing
- Hardware Timestamping: Nanosecond precision timing
- CUDA Integration: GPU-based price calculations and risk analytics
- Parallel Processing: Vectorized operations for portfolio calculations
- Real-time VaR: GPU-accelerated Value-at-Risk calculations
- Option Pricing: Black-Scholes and Monte Carlo simulations
- Real-time Monitoring: Position tracking and exposure limits
- Circuit Breakers: Automatic trading halts on risk thresholds
- Multi-threaded: Parallel risk calculations
- Hot Configuration: Runtime parameter updates without restart
- gRPC API: High-performance order entry and market data
- REST Endpoints: Management and monitoring interfaces
- WebSocket Streams: Real-time market data distribution
- Prometheus Metrics: Comprehensive performance monitoring
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ Market Data │ │ Order Entry │ │ Risk Manager │
│ Feed Handler │ │ (gRPC API) │ │ │
└─────────┬───────┘ └─────────┬───────┘ └─────────┬───────┘
│ │ │
▼ ▼ ▼
┌─────────────────────────────────────────────────────────────────┐
│ Matching Engine Core │
│ ┌─────────────┐ ┌─────────────┐ ┌─────────────────────────┐ │
│ │ Order Book │ │ Trade Exec │ │ GPU Price Calc │ │
│ │ (Lock-Free) │ │ Engine │ │ (CUDA Kernels) │ │
│ └─────────────┘ └─────────────┘ └─────────────────────────┘ │
└─────────────────────────────────────────────────────────────────┘
│ │ │
▼ ▼ ▼
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ Trade Store │ │ Monitoring │ │ Simulation │
│ & Analytics │ │ & Metrics │ │ & Backtesting │
└─────────────────┘ └─────────────────┘ └─────────────────┘
- Language: C++23 with concepts, coroutines, and ranges
- Concurrency: std::jthread, atomic operations, lock-free containers
- GPU Computing: CUDA 12.0+ with cuBLAS
- Networking: Custom UDP/TCP with epoll (Linux) / IOCP (Windows)
- Serialization: Protocol Buffers with gRPC
- Build System: CMake with Conan/vcpkg dependencies
- Containerization: Docker with NVIDIA runtime
- Monitoring: Prometheus + Grafana dashboards
- Testing: Google Test + Google Benchmark
- C++23 compatible compiler (GCC 12+, Clang 15+)
- CUDA Toolkit 12.0+
- CMake 3.20+
- Docker & Docker Compose (optional)
# Clone repository
git clone https://github.com/Brijes987/ChronoTrade.git
cd trading-engine
# Install dependencies (Ubuntu/Debian)
sudo apt-get update
sudo apt-get install -y build-essential cmake libprotobuf-dev protobuf-compiler \
libgrpc++-dev libgrpc-dev libbenchmark-dev libgtest-dev
# Build
mkdir build && cd build
cmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_CXX_STANDARD=23 ..
make -j$(nproc)
# Run
./trading_engine# Start full stack with monitoring
docker-compose up -d
# View logs
docker-compose logs -f trading-engine
# Access Grafana dashboard
open http://localhost:3000 (admin/admin)- Order Processing: < 500 nanoseconds (median)
- Market Data Processing: < 100 nanoseconds per message
- Trade Execution: < 1 microsecond end-to-end
- Risk Calculations: < 50 microseconds for 10K positions
- Orders per Second: 1M+ sustained
- Market Data Messages: 10M+ per second
- Concurrent Connections: 10K+ simultaneous clients
- Memory Usage: < 1GB for 100K active orders
- CPU: Intel Xeon or AMD EPYC (16+ cores recommended)
- Memory: 32GB+ DDR4-3200
- GPU: NVIDIA RTX 3080+ or Tesla V100+ (optional)
- Network: 10Gbps+ low-latency network interface
- Storage: NVMe SSD for logging and analytics
cd build
ctest --output-on-failure./benchmarks/matching_engine_benchmark
./benchmarks/market_data_benchmark
./benchmarks/gpu_calculations_benchmark# Start market data simulator
./tools/market_simulator --symbols AAPL,GOOGL,MSFT --rate 10000
# Run backtesting
./tools/backtest --strategy momentum --data historical_data.csv- Latency Percentiles: P50, P95, P99, P99.9
- Throughput: Messages/trades per second
- Resource Usage: CPU, memory, GPU utilization
- Error Rates: Failed orders, network errors
- Business Metrics: PnL, positions, risk exposure
- Real-time latency heatmaps
- Order flow visualization
- Risk exposure monitoring
- System performance metrics
- Trade execution analytics
# config/engine.yaml
matching_engine:
max_orders_per_symbol: 100000
price_precision: 4
enable_gpu_acceleration: true
market_data:
udp_buffer_size: 65536
processing_threads: 4
enable_hardware_timestamps: true
risk_management:
max_position_size: 1000000
max_daily_loss: 100000
enable_circuit_breakers: true# CPU isolation
echo 2-15 > /sys/fs/cgroup/cpuset/trading/cpuset.cpus
# Network optimization
echo 'net.core.rmem_max = 134217728' >> /etc/sysctl.conf
echo 'net.core.wmem_max = 134217728' >> /etc/sysctl.conf
# Disable CPU frequency scaling
echo performance > /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
- Follow C++ Core Guidelines
- Maintain sub-microsecond latency requirements
- Add comprehensive tests for new features
- Update benchmarks for performance-critical changes
- Document API changes
This project is licensed under the MIT License - see the LICENSE file for details.
⚡ Built for Speed. Engineered for Scale. Optimized for Performance.