What is GPU inference optimization in classification systems?

GPU inference optimization improves classification speed and throughput using hardware acceleration techniques.

GPU optimization includes batching requests, using tensor cores, model quantization, and graph optimizations via frameworks like TensorRT or ONNX Runtime. Efficient memory management and kernel fusion reduce overhead. This is critical for deep learning classification systems handling high throughput.