Quantization
Activation-aware weight quantization uses activation statistics to identify weight channels that need extra protection. It applies calibrated scaling so salient channels incur less quantization error.
Activation evidence can preserve important weight contributions better than magnitude-only choices. The result still depends on calibration coverage, packing, kernels, and the target workload.
A quantizer gathers representative activations, searches channel scales, and packs the resulting low-precision weights. Serving kernels must implement the same grouping and scaling layout.
Activation-aware weight quantization uses activation statistics to identify weight channels that need extra protection. It applies calibrated scaling so salient channels incur less quantization error. A quantizer gathers representative activations, searches channel scales, and packs the resulting low-precision weights. Serving kernels must implement the same grouping and scaling layout.
Activation evidence can preserve important weight contributions better than magnitude-only choices. The result still depends on calibration coverage, packing, kernels, and the target workload.
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