2nbased ferroelectric FET (FeFET) has recently received great interest for its application in '/> A FeFET Based Processing-In-Memory Architecture for Solving Distributed Least-Square Optimizations
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A FeFET Based Processing-In-Memory Architecture for Solving Distributed Least-Square Optimizations

机译:基于FeFET的内存中处理架构,用于解决分布式最小二乘优化问题

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Hf0n2nbased ferroelectric FET (FeFET) has recently received great interest for its application in nonvolatile memory (NVM) [1]. Unlike conventional perovskite based ferroelectric materials, Hf0n2nis CMOS compatible and retains ferroelectricity for thin film with thickness around 10 nm. Therefore, successful integration of ferroelectric Hf0n2ninto advanced CMOS technology makes this technology highly promising for NVM [1]. Moreover, by tuning the portion of switched ferroelectric domain, a FeFET can exhibit multiple intermediate states, which enables its application as an analog conductance in mixed-signal in-memory computing. Currently, such architectures have been applied to neuromorphic computing [2], [3]. In this paper, we present a processing-in-memory (PIM) architecture with FeFETs and demonstrate how this can be used to solve a new class of optimization problems, in particular, distributed least square minimization.
机译:Hf0n 2 nbased铁电FET(FeFET)最近在非易失性存储器(NVM)中的应用引起了极大的兴趣[1]。与传统的基于钙钛矿的铁电材料不同,Hf0n 2 nis CMOS兼容,并为厚度约10 nm的薄膜保留铁电性。因此,铁电Hf0n 的成功集成2 先进的CMOS技术使得该技术对NVM极具前景[1]。此外,通过调整开关铁电畴的一部分,FeFET可以表现出多个中间状态,从而使其可以作为模拟电导在混合信号内存计算中的应用。当前,这样的架构已经被应用于神经形态计算[2],[3]。在本文中,我们介绍了具有FeFET的内存中处理(PIM)架构,并演示了如何将其用于解决一类新的优化问题,尤其是分布式最小二乘最小化。

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