Hardware realization of a medical diagnostic system based on Probabilistic CMOS (PCMOS) technology

Z. Kong, Jun-Jie Tan, Bilge E. S. Akgul, K. Yeo, K. Palem, W. Goh
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引用次数: 1

Abstract

The continuous miniaturization of CMOS feature sizes into the nanometer regime has increasingly caused problems due to noise vulnerability, process variations, and energy consumption. Noise vulnerability and process variations have been recognized to cause statistical or probabilistic device behaviors. In this paper, by capitalizing on what most people termed as nuisance, we demonstrate how noise can be put to good use in CMOS devices. We present the first hardware implementation of a Bayesian medical diagnostic system for real-world patient monitoring using probabilistic CMOS (PCMOS). We explore ways to adapt Bayesian structure under realistic hardware constraints without compromising prediction accuracy. As compared to conventional CMOS, PCMOS implementation of the network offers noteworthy merits: ultra low-power consumption, high-speed performance and cost-effectiveness.
基于概率CMOS (PCMOS)技术的医疗诊断系统的硬件实现
随着CMOS特征尺寸不断小型化到纳米级,噪声脆弱性、工艺变化和能耗等问题日益突出。噪声脆弱性和工艺变化已被认为是导致统计或概率设备行为的原因。在本文中,通过利用大多数人称之为滋扰的东西,我们展示了如何在CMOS器件中很好地利用噪声。我们提出了贝叶斯医疗诊断系统的第一个硬件实现,用于使用概率CMOS (PCMOS)进行现实世界的患者监测。我们探索了在不影响预测精度的情况下在现实硬件约束下调整贝叶斯结构的方法。与传统CMOS相比,PCMOS实现网络具有显著的优点:超低功耗,高速性能和成本效益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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