NeuADC: Neural Network-Inspired RRAM-Based Synthesizable Analog-to-Digital Conversion with Reconfigurable Quantization Support
NeuADC: Neural Network-Inspired RRAM-Based Synthesizable Analog-to-Digital Conversion with Reconfigurable Quantization Support
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DOI：
10.23919/date.2019.8714933
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发表时间：
2019-03
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通讯作者：
Weidong Cao;Xin He;Ayan Chakrabarti;Xuan Zhang
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作者：
Weidong Cao;Xin He;Ayan Chakrabarti;Xuan Zhang
传统的模数转换器（ADC）采用专用的模拟和混合信号（AMS）电路，需要耗时的手工设计过程。它们还表现出有限的可重构性，并且无法使用相同的电路来支持不同的量化方案。在本文中，我们提出了NeuADC -一种自动化的设计方法来合成一个模拟到数字（A/D）接口，可以近似所需的量化功能，使用神经网络（NN）与一个单一的隐藏层。我们的设计利用混合信号电阻式随机存取存储器（RRAM）交叉结构在一个新的双路径配置，以实现基本的NN操作在电路级，并利用平滑位编码方案，以提高训练精度。基于130 nm工艺的SPICE仿真结果表明，与最先进的ADC设计相比，NeuADC不仅在综合设计指标上具有良好的性能，而且它可以使用相同的硬件基板本质上支持多种可重新配置的量化方案，为未来适应性应用驱动的信号转换铺平了道路。在中等RRAM电阻精度下，NeuADC的量化质量的鲁棒性也使用SPICE仿真进行了评估。
Traditional analog-to-digital converters (ADCs) employ dedicated analog and mixed-signal (AMS) circuits and require time-consuming manual design process. They also exhibit limited reconfigurability and are unable to support diverse quantization schemes using the same circuitry. In this paper, we propose NeuADC — an automated design approach to synthesizing an analog-to-digital (A/D) interface that can approximate the desired quantization function using a neural network (NN) with a single hidden layer. Our design leverages the mixed-signal resistive random-access memory (RRAM) crossbar architecture in a novel dual-path configuration to realize basic NN operations at the circuit level and exploits smooth bit-encoding scheme to improve the training accuracy. Results obtained from SPICE simulations based on 130nm technology suggest that not only can NeuADC deliver promising performance compared to the state-of-art ADC designs across comprehensive design metrics, but also it can intrinsically support multiple reconfigurable quantization schemes using the same hardware substrate, paving the ways for future adaptable application-driven signal conversion. The robustness of NeuADC’s quantization quality under moderate RRAM resistance precision is also evaluated using SPICE simulations.