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Biosequences analysis on NanoMagnet Logic

机译:NanoMagnet Logic的生物序列分析

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In the last decade Quantum dot Cellular Automata technology has been one of the most studied among the emerging technologies. The magnetic implementation, NanoMagnet Logic (NML), is particularly interesting as an alternative solutions to CMOS technology. The main advantages of NML circuits resides in the possibility to mix logic and memory in the same device, the expected low power consumption and the remarkable tolerance to heat and radiations. NML and QCA circuits behavior is different w.r.t. their CMOS counterparts. Consequently architecture organization must be tailored to their characteristics, and it is important to identify which applications are best suited for this technology. Our contribution reported in this paper represents a considerable step-forward in this direction. We present an optimized implementation on NML technology of an hardware accelerator for biosequences analysis. The architecture leverages the systolic array structure, which is the best organization for this technology due to the regularity of the layout. The circuit is described using a VHDL model, simulated to verify the correct functionality from the application point of view, and performance are evaluated, both in terms of speed and power consumption. Results pinpoints that NML technology with the appropriate clock solution can reach a considerable reduction in power consumption over CMOS. This analysis highlights quantitatively, and not only qualitatively, that NML logic is perfectly suited for Massively Parallel Data Analysis applications.
机译:在过去的十年中,量子点元胞自动机技术一直是新兴技术中研究最多的技术之一。磁性实施方案NanoMagnet Logic(NML)作为CMOS技术的替代解决方案特别有趣。 NML电路的主要优点在于可以在同一设备中混合逻辑和存储器,预期的低功耗以及对热量和辐射的显着耐受性。 NML和QCA电路的行为有所不同他们的CMOS对应产品。因此,必须根据其特征量身定制体系结构组织,并且确定最适合该技术的应用程序很重要。本文报道的我们的贡献代表了朝着这个方向迈出的一大步。我们提出了一种用于生物序列分析的硬件加速器的NML技术的优化实现。该体系结构利用了脉动阵列结构,由于布局的规律性,脉动阵列结构是该技术的最佳组织。使用VHDL模型描述了该电路,并从应用的角度对其进行了仿真,以验证其功能是否正确,并在速度和功耗方面评估了性能。结果表明,采用适当的时钟解决方案的NML技术可以大大降低CMOS上的功耗。该分析从数量上(不仅在质量上)突出表明NML逻辑非常适合大规模并行数据分析应用程序。

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