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FQA: A Full-Space Quantization-Driven Architecture for Hardware-Efficient Piecewise Approximation of Nonlinear Activation Functions
arXiv:2606.05627v1 Announce Type: new Abstract: In this paper, we propose a full-space quantization-driven architecture (FQA) for the hardware-efficient piecewise polynomial approximations (PPAs) of nonlinear activation functions. FQA comprehensively considers both fractional-bit truncation error and quantization error that cause the deviation of the optimal approximation coefficients. Crucially, FQA can precisely determine and search the complete range of optimal coefficients.