6.6. Chapter Summary

1. The compiler backend performs three primary tasks: graph optimization, operator selection, and memory allocation.

2. Graph optimization reduces resource overhead, adapts the graph to hardware capabilities, and enhances execution performance while maintaining the model’s numerical properties.

3. Graph optimization techniques can be hardware-agnostic (e.g., memory I/O optimization) or hardware-specific (e.g., subgraph transformation to adapt to hardware instruction restrictions).

4. Operator selection involves mapping the compute nodes in an IR to suitable operators for hardware execution.

5. When selecting an optimized operator, factors such as data format and type must be considered, as they impact operator performance on the target hardware.

6. An IR is generated after graph optimization and operator selection. Based on the IR, memory is allocated for input and output tensors of each operator before launching them to hardware for execution.

7. Memory reuse is designed to improve memory utilization and accommodate larger models within limited device memory.

8. Fusion of communication operators enhances communication efficiency. Properly allocating memory for in-place operators reduces memory footprint and improves computing efficiency.

9. Operator compilers play a vital role in optimizing hardware performance. Critical optimization techniques include scheduling strategies and the polyhedral model algorithm.