TRAM achieves up to 27% power reduction in multipliers for CNNs and vision transformers by jointly training model weights and approximate multiplier designs.
A survey on approximate multiplier designs for energy efficiency: From algorithms to circuits.ACM Transactions on Design Automation of Electronic Systems (TODAES), 29(1):1–37
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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.