Inference Acceleration
Techniques for improving model inference speed through methods such as graph optimization and hardware adaptation. Commonly used tools include TensorRT, ONNX Runtime, and OpenVINO.
Timeline (last 90 days)
Inference acceleration techniques are moving from general-purpose optimization toward workload awareness, and redesigning the decoding pipeline for specific workload characteristics may be more effective than making incremental improvements on a general-purpose framework.
Model acceleration typically refers to reducing the number of steps, time, or computational resources required for generation while keeping output quality acceptable.
All Facts (2)
Inference acceleration techniques are moving from general-purpose optimization toward workload awareness, and redesigning the decoding pipeline for specific workload characteristics may be more effective than making incremental improvements on a general-purpose framework.
50%UnverifiedModel acceleration typically refers to reducing the number of steps, time, or computational resources required for generation while keeping output quality acceptable.
50%