Performance Optimization
Achieving microsecond-level latency requires meticulous attention to every layer of your system. This guide covers proven techniques for maximizing VectorAlpha's performance in production environments.
Hardware Optimization
CPU Selection and Configuration
Modern trading systems benefit from CPUs with high single-thread performance and large L3 caches. Intel Ice Lake and AMD EPYC processors offer excellent performance for quantitative workloads.
Recommended CPU Features
- ✓ AVX-512: Enables processing 8 double-precision values per instruction
- ✓ Large L3 Cache: 32MB+ reduces memory access latency
- ✓ High Clock Speed: 3.5GHz+ base frequency for consistent performance
- ✓ NUMA Support: Multi-socket systems for parallel workloads
Network Optimization
Network latency often dominates total system latency. Optimize your network stack for minimal overhead:
# Disable interrupt coalescing
ethtool -C eth0 rx-usecs 0 tx-usecs 0
# Enable receive packet steering
echo f > /sys/class/net/eth0/queues/rx-0/rps_cpus
# Increase network buffer sizes
sysctl -w net.core.rmem_max=134217728
sysctl -w net.core.wmem_max=134217728Software Optimization Techniques
Compiler Flags
Rust's compiler offers powerful optimization flags that can significantly improve performance:
Learn more: Cargo Build Profiles Documentation
Configuration Example Coming Soon
Configuration examples will be available in the next update.
Profile-Guided Optimization
Use PGO to optimize for your specific workload. First, build with profiling enabled, run representative workloads, then rebuild with the profile data. This can yield 10-20% performance improvements.
Memory Access Patterns
Optimize data structures for sequential access to maximize cache efficiency:
Code Example Coming Soon
Full code examples with syntax highlighting will be available in the next update.
Latency Measurement and Analysis
Instrumentation Strategy
Accurate latency measurement requires careful instrumentation without affecting performance:
Code Example Coming Soon
Full code examples with syntax highlighting will be available in the next update.
Thread Management
CPU Affinity
Pin critical threads to dedicated CPU cores to eliminate context switching:
Code Example Coming Soon
Full code examples with syntax highlighting will be available in the next update.
Lock-Free Communication
Use lock-free queues for inter-thread communication to avoid contention:
Learn more: Introduction to Lock-Free Algorithms
Performance Comparison
| Communication Method | Latency (ns) | Throughput (msg/sec) |
|---|---|---|
| Mutex-protected queue | 250-500 | 2M |
| Lock-free SPSC queue | 15-30 | 33M |
| Lock-free MPMC queue | 40-80 | 12M |
GPU Acceleration Best Practices
Kernel Optimization
Maximize GPU throughput with these optimization techniques:
- Coalesced Memory Access: Ensure adjacent threads access adjacent memory locations
- Occupancy Tuning: Balance register usage with thread count
- Shared Memory: Use for frequently accessed data within thread blocks
- Stream Processing: Overlap computation with data transfer
CUDA Example Coming Soon
GPU programming examples will be available in the next update.
Production Deployment Checklist
Pre-Production Optimization Steps
- Profile application with production-like data
- Configure CPU governor to "performance" mode
- Disable CPU frequency scaling and turbo boost for consistency
- Enable huge pages for large memory allocations
- Verify NUMA node assignment for memory and threads
- Test failover scenarios without performance degradation
- Implement comprehensive latency monitoring
- Set up alerting for performance anomalies
Continuous Optimization
Performance optimization is an ongoing process. Establish these practices:
- Automated Benchmarking: Run performance tests on every commit
- Regression Detection: Alert on performance degradations
- A/B Testing: Compare optimization strategies in production
- Capacity Planning: Monitor resource usage trends