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Statistical Simulations on Perceptron-Based Adders

Statistical Simulations on Perceptron-Based Adders
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Author(s): Snorre Aunet (University of Oslo, Norway & Centers for Neural Inspired Nano Architectures, Norway)and Hans Kristian Otnes Berge (University of Oslo, Norway)
Copyright: 2009
Pages: 8
Source title: Encyclopedia of Artificial Intelligence
Source Author(s)/Editor(s): Juan Ramón Rabuñal Dopico (University of A Coruña, Spain), Julian Dorado (University of A Coruña, Spain)and Alejandro Pazos (University of A Coruña, Spain)
DOI: 10.4018/978-1-59904-849-9.ch216

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Abstract

In this article we compare a number of full-adder (1- bit addition) cells regarding minimum supply voltage and yield, when taking statistical simulations into account. According to the ITRS Roadmap two of the most important challenges for future nanoelectronics design are reducing power consumption and increasing manufacturability (ITRS, 2005). We use subthreshold CMOS, which is regarded by many as the most promising ultra low power circuit technique. It is also shown that a minimum redundancyfactor as low as 2 is sufficient to make circuits maintain full functionality under the presence of defects. This is, to our knowledge, the lowest redundancy reported for comparable circuits, and builds on a method suggested a few years ago (Aunet & Hartmann, 2003). A standard Full-Adder (FA) and an FA based on perceptrons exploiting the “mirrored gate”, implemented in a standard 90 nm CMOS technology, are shown not to withstand statistical mismatch and process variations for supply voltages below 150 mV. Exploiting a redundancy scheme tolerating “open” faults, with gate-level redundancy and shorted outputs, shows that the same two FAs might produce adequate Sum and Carry outputs at the presence of a defect PMOS for supply voltages above 150 mV, for a redundancy factor of 2 (Aunet & Otnes Berge, 2007). Two additional perceptrons do not tolerate the process variations, according to simulations. Simulations suggest that the standard FA has the lowest power consumption. Power consumption varies more than an order of magnitude for all subthreshold FAs, due to the statistical variations

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