2023/05/29 · In this article, we proposed QPA, an integration of error-flattened quantization-aware PPA methods, to generate the optimized coefficients for efficient ...

In this paper, we proposed QPA, a quantization-aware piecewise polynomial approximation methodology, to generate the optimized coefficients for hardware ...

1) The QPA methodology is used for designing quantization-. aware piecewise polynomial approximation methods. These · 2) Benefiting from the advantages of ...

2023/07/01 · In this article, we proposed QPA, an integration of error-flattened quantization-aware PPA methods, to generate the optimized coefficients for ...

In this article, we proposed QPA, an integration of error-flattened quantization-aware PPA methods, to generate the optimized coefficients for efficient ...

2023/10/30 · Piecewise polynomial approximation on non-linear functions plays an important role in neural network accelerators and digital.

QPA incorporated four key features to minimize the fitting error and the hardware cost, including using the Remez algorithm to compute the minimax fitting.

QPA, an integration of error-flattened quantization-aware PPA methods, to generate the optimized coefficients for efficient hardware implementations ...

This article reviews some of the classical methods used for quickly obtaining low-precision approximations to the elementary functions.

[1.18] H. Geng, X. Chen, N. Zhao, Y. Du and L. Du, QPA: A Quantization-Aware Piecewise Polynomial Approximation Methodology for Hardware-Efficient ...