Weiyi Zhang, Chun Zhang, L. Niu, Fasih Ud Din, Farrukh, Hanjun Jiang
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An Efficient FPGA Design for Fixed-point Exponential Calculation
Exponential calculation is widely used in different algorithms, such as the activation functions of artificial neural networks. However, it is hard to implement on FPGA, consuming much time and resources. In this work, a novel exponential calculation module for fixed-point number is proposed based on the theory of Fast InvSqrt. The proposed exponential unit achieves at most 3.7x throughput while the resource utilization is largely reduced compared with previous works. The efficiency and accuracy are suitable for different applications.