CUDA Kernel Optimization: Advanced GPU Performance Engineering

Cooperative Groups for Advanced Synchronization#

🤝 Cooperative Groups Architecture:

Thread Block (1024 threads)
├── Warp 0 (32 threads) ──┐
├── Warp 1 (32 threads) ──┤
├── ...                   ├─ Synchronized Operations
└── Warp 31 (32 threads) ─┘

🎯 Advanced Synchronization Patterns:

Pattern Type	Scope	Use Case	Performance
Thread Block	1024 threads	Global sync	High overhead
Warp-level	32 threads	SIMD operations	Low overhead
Sub-warp	Custom size	Flexible sync	Medium overhead
Thread clusters	Multi-block	Distributed compute	Variable

Warp Shuffle Operations#

Shuffle Communication Patterns:#

🔄 Shuffle Operation Types:

__shfl_sync(): Direct thread-to-thread communication
__shfl_up_sync(): Data flows up in warp
__shfl_down_sync(): Data flows down in warp
__shfl_xor_sync(): Butterfly exchange patterns

📊 Performance Comparison:

Communication Method    │ Latency │ Bandwidth │ Power
───────────────────────┼─────────┼───────────┼──────
Shared Memory          │ ~20 cycles │ 1TB/s   │ High
Warp Shuffle           │ ~1 cycle   │ 2TB/s   │ Low
Register Spilling      │ ~400 cycles │ 200GB/s │ Very High

CUDA Kernel Optimization: Advanced GPU Performance Engineering

⚙️ Warp-Level Optimization Techniques

Cooperative Groups for Advanced Synchronization#

Warp Shuffle Operations#

Shuffle Communication Patterns:#