CUDA Kernel Optimization: Advanced GPU Performance Engineering

Advanced CUDA kernel optimization requires a deep understanding of GPU architecture, memory hierarchies, and execution models. The techniques covered in this lesson—from shared memory bank conflict elimination to advanced profiling workflows—form the foundation for extracting peak performance from modern GPU hardware.

Key Takeaways:#

• Memory hierarchy optimization provides the highest performance gains
• Warp-level programming enables fine-grained performance control
• Occupancy optimization balances resources for maximum throughput
• Production monitoring ensures sustained high performance

These optimization strategies enable the development of high-performance GPU applications that scale efficiently across different hardware generations and workload characteristics.