Subthreshold circuit design is a compelling method for ultra-low power applications. However, subthreshold designs show dramatically increased sensitivity to process variations due to the exponential relationship of subthreshold drive current with V th variation. In this paper, we present an analysis of subthreshold energy efficiency considering process variation, and propose methods to mitigate its impact. We show that, unlike superthreshold circuits, random dopant fluctuation is the dominant component of variation in subthreshold operation. We investigate how this variability can be ameliorated with proper circuit sizing and choice of circuit logic depth. We then present a statistical analysis of the energy efficiency of subthreshold circuits considering process variations. We show that the energy optimal supply voltage increases due to process variations and study its dependence on circuit parameters. We verify our analytical models against Monte Carlo SPICE simulations and show that they accurately predict the minimum energy and energy optimal supply voltage. Finally, we use the developed statistical energy model to determine the optimal pipelining depth in subthreshold designs.

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Energy efficiency has become a ubiquitous design requirement for digital circuits. Aggressive supply-voltage scaling has emerged as the most effective way to reduce energy use. In this work, we review circuit behavior at low voltages, specifically in the subthreshold (V dd , V th ) regime, and suggest new strategies for energy-efficient design. We begin with a study at the device level, and we show that extreme sensitivity to the supply and threshold voltages complicates subthreshold design. The effects of this sensitivity can be minimized through simple device modifications and new device geometries. At the circuit level, we review the energy characteristics of subthreshold logic and SRAM circuits, and demonstrate that energy efficiency relies on the balance between dynamic and leakage energies, with process variability playing a key role in both energy efficiency and robustness. We continue the study of energy-efficient design by broadening our scope to the architectural level. We discuss the energy benefits of techniques such as multiple-threshold CMOS (MTCMOS) and adaptive body biasing (ABB), and we also consider the performance benefits of multiprocessor design at ultralow supply voltages.

Abstract-Subthreshold circuits have drawn a strong interest in recent ultralow power research. In this paper, we present a highly efficient subthreshold microprocessor targeting sensor application. It is optimized across different design stages including ISA definition, microarchitecture evaluation and circuit and implementation optimization. Our investigation concludes that microarchitectural decisions in the subthreshold regime differ significantly from that in conventional superthreshold mode. We propose a new general-purpose sensor processor architecture, which we call the Subliminal Processor. On the circuit side, subthreshold operation is known to exhibit an optimal energy point ( min ). However, propagation delay also becomes more sensitive to process variation and can reduce the energy scaling gain. We conduct thorough analysis on how supply voltage and operating frequency impact energy efficiency in a statistical context. With careful library cell selection and robust static RAM design, the Subliminal Processor operates correctly down to 200 mV in a 0.13-m technology, which is sufficiently low to operate at min .Silicon measurements of the Subliminal Processor show a maximum energy efficiency of 2.6 pJ/instruction at 360 mV supply voltage and 833 kHz operating frequency. Finally, we examine the variation in frequency and min across die to verify our analysis of adaptive tuning of the clock frequency and min for optimal energy efficiency.Index Terms-Sensor networks, subthreshold design, min , ultra low power design.

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