What is inference graph optimization in production ML systems?

Inference graph optimization reduces computation by simplifying and fusing model operations.

Inference graph optimization transforms computational graphs to improve latency and throughput. Techniques include operator fusion, constant folding, pruning unused nodes, and hardware-specific optimizations (e.g., TensorRT graph compilation). This reduces memory access overhead and improves execution efficiency.