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PENDA: An Efficient Processing Element via Norm-of-Difference for Deep Learning Accelerators
Inner product computation dominates the computational cost of deep learning models; thus, accelerating this primitive is key to improving hardware efficiency. However, most existing techniques rely on approximations, which can degrade model accuracy. To preserve exactness while optimizing hardware,
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