TRAM achieves up to 27% power reduction in multipliers for CNNs and vision transformers by jointly training model weights and approximate multiplier designs.
Approximate computing survey, part II: Application-specific & architectural approximation techniques and applications.ACM Computing Surveys, 57(7):1–36
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TRAM: Training Approximate Multiplier Structures for Low-Power AI Accelerators
TRAM achieves up to 27% power reduction in multipliers for CNNs and vision transformers by jointly training model weights and approximate multiplier designs.