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A quantitative approach to testing in Quantum dot Cellular Automata: NanoMagnet Logic case

机译:量子点细胞自动机中定量测试方法:NanoMagnet Logic案例

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摘要

With the approaching of CMOS scaling limits the interest on emerging technologies is rapidly growing. Among emerging technologies, Quantum dot Cellular Automata (QCA) is one of the most studied. Particularly the magnetic implementation, NanoMagnet Logic (NML), offers very low power consumption and it combines logic and memory on a unique device. Despite the advantages of these technologies, QCA and NML working principle relies on the electric or magnetic interaction among neighbor cells, so it is very sensitive to process variations. The behavior of circuits is therefore largely affected by defects and fabrication variations. To effectively design circuits with these technologies, proper tools for testing circuits are necessary. In this work we present an innovative test environment for NML technology. The test algorithm is integrated in ToPoliNano, our design and simulation tool for emerging technologies, and it is specifically tailored to support the analysis of faults in large complexity circuits. Thanks to this tool it is possible to design and test complex NML circuits considering the effect of process variations in terms of Yield and Output Error Rate. The approach gives then feedback to the technologists, remarkably helping the future development of this technology. Moreover, notwithstanding the methodology is applied here to NML circuits only, it can also be successfully applied to QCA technology in general, greatly enhancing the value of the work we proposed here
机译:随着CMOS缩放限制的临近,对新兴技术的兴趣正在迅速增长。在新兴技术中,量子点元胞自动机(QCA)是研究最多的技术之一。尤其是磁性实现,NanoMagnet Logic(NML),功耗极低,并且在独特的设备上结合了逻辑和存储器。尽管这些技术具有优势,但QCA和NML的工作原理仍依赖于相邻单元之间的电或磁相互作用,因此它对工艺变化非常敏感。因此,电路的行为在很大程度上受到缺陷和制造偏差的影响。为了使用这些技术有效地设计电路,需要适当的工具来测试电路。在这项工作中,我们为NML技术提供了创新的测试环境。该测试算法已集成到我们的新兴技术设计和仿真工具ToPoliNano中,并且专门针对支持大型复杂电路中的故障分析而量身定制。得益于此工具,可以考虑良率和输出错误率等工艺变化的影响来设计和测试复杂的NML电路。然后,该方法将反馈给技术人员,极大地帮助了该技术的未来发展。此外,尽管该方法仅适用于NML电路,但总体上也可以成功地应用于QCA技术,从而大大提高了我们在此处提出的工作的价值。

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