IEEE Transactions on Very Large Scale Integration (VLSI) Systems · 2009 · 155 citations · 32 references
EngineeringComputer EngineeringComputer ScienceComputer ArchitectureLow-power DesignMicroelectronicsPower OptimizationPower-aware DesignProcessor Core DesignProcessor MicroarchitectureSubthreshold Circuit DesignVoltage ScalingEnergy-optimal Operating PointLow-power MicroarchitectureMicroarchitectural OptimizationMicroarchitectureMicroarchitecture Performance EvaluationProcessor ArchitectureSubthreshold OperationUltra-low-voltage Circuit Design
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 (Knin)- 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-mum technology, which is sufficiently low to operate at V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">min</sub> . 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 V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">min</sub> across die to verify our analysis of adaptive tuning of the clock frequency and V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">min</sub> for optimal energy efficiency.
32
Wireless sensor networks for habitat monitoring
Alan Mainwaring, David Culler, Joseph Polastre et al. · 2002 · 4.2K citations
Computing, Computer Systems, Ecology +17
Sensor networks: Evolution, opportunities, and challenges
Chee-Yee Chong, Sanjeev Kumar · Proceedings of the IEEE · 2003 · 3.1K citations
A wireless sensor network For structural monitoring
Ning Xu, Sumit Rangwala, Krishna Chintalapudi et al. · 2004 · 1.1K citations
Energy efficient routing in wireless sensor networks
Curt Schurgers, Mani Srivastava · 2002 · 791 citations