kernel fusion opportunities

**Kernel fusion opportunities** is the **chances to combine multiple operations into fewer kernels to reduce memory traffic and launch overhead** - fusion improves throughput by keeping intermediates on-chip instead of repeatedly writing to global memory. **What Is Kernel fusion opportunities?** - **Definition**: Optimization where adjacent operators are executed in one composite kernel. - **Primary Benefit**: Removes intermediate tensor writes and reads that consume bandwidth. - **Secondary Benefit**: Cuts kernel launch count and related CPU scheduling overhead. - **Fusion Limits**: Complex control flow, shape mismatches, or register pressure can constrain fusion depth. **Why Kernel fusion opportunities Matters** - **Memory Efficiency**: Bandwidth-bound pipelines often gain significantly from fused intermediate reuse. - **Latency Reduction**: Fewer launches lower overhead for small and medium-sized operator chains. - **Throughput**: Composite kernels increase arithmetic intensity and improve hardware utilization. - **Inference Speed**: Fusion is especially impactful in low-latency serving paths with many small ops. - **Energy Savings**: Less memory movement reduces power cost per operation. **How It Is Used in Practice** - **Pattern Mining**: Identify repeated operator sequences with heavy intermediate traffic. - **Compiler Enablement**: Use graph compilers or runtime fusion passes where available. - **Safety Validation**: Check numerical parity and kernel resource usage after fusion changes. Kernel fusion opportunities are **high-value targets for memory-bound optimization** - reducing intermediate traffic often yields immediate and meaningful speed improvements.