What is model compilation for inference acceleration?

Model compilation converts ML models into optimized execution graphs for faster inference.

Model compilation frameworks like TensorRT, TVM, and TorchScript transform high-level model definitions into optimized low-level execution graphs. They perform operator fusion, constant folding, memory optimization, and hardware-specific kernel selection. This reduces inference latency and improves throughput, especially for GPU and edge deployment scenarios.