The deceleration of Moore's Law has led to increasing difficulties in advancing the computational speed and power efficiency of Complementary -Metal-Oxide-Semiconductor (CMOS) chips. As a solution to this challeng...
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ISBN:
(纸本)9798350330991;9798350331004
The deceleration of Moore's Law has led to increasing difficulties in advancing the computational speed and power efficiency of Complementary -Metal-Oxide-Semiconductor (CMOS) chips. As a solution to this challenge, optical computing emerges as a promising technology, boasting low energy consumption, high processing speed, and extensive bandwidth. Yet, a critical obstacle remains: the absence of a co simulation platform that incorporates both photonic chips and peripheral electrical circuits. This paper addresses this gap by introducing a hybrid optoelectronic computing evaluation and deployment platform utilizing Simulink tools. Based on the measured data from the silicon optical computing chip, we have deployed an imagefilteringalgorithm and a convolutional neural network onto this platform. The optical computing chip achieves an accuracy of 86.4% on the imageNet image dataset. Through evaluation, we have identified the most substantial impacts on calculation results. To achieve an image classification accuracy of 80%, the signal-to-noise ratio (SNR) of the low -speed DAC must be a minimum of 52 dB. These findings provide crucial insights into the optimization of optical computing systems.
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