Subthreshold leakage modeling and reduction techniques
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
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ICCD '00 Proceedings of the 2000 IEEE International Conference on Computer Design: VLSI in Computers & Processors
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CASES '06 Proceedings of the 2006 international conference on Compilers, architecture and synthesis for embedded systems
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A low-power parallel design of discrete wavelet transform using subthreshold voltage technology
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Hybrid Super/Subthreshold Design of a Low Power Scalable-Throughput FFT Architecture
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SAMOS'06 Proceedings of the 6th international conference on Embedded Computer Systems: architectures, Modeling, and Simulation
Hybrid super/subthreshold design of a low power scalable-throughput FFT architecture
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Assessing the performance limits of parallelized near-threshold computing
Proceedings of the 49th Annual Design Automation Conference
Design of energy-efficient, adaptable throughput systems at near/sub-threshold voltage
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Optimization for real-time systems with non-convex power versus speed models
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IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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Sensor network processors and their applications are a growing area of focus in computer system research and design. Inherent to this design space is a reduced processing performance requirement and extremely high energy constraints, such that sensor network processors must execute low-performance tasks for long durations on small energy supplies. In this paper, we demonstrate that subthreshold-voltage circuit design (400 mV and below) lends itself well to the performance and energy demands of sensor network processors. Moreover, we show that the landscape for microarchitectural energy optimization dramatically changes in the subthreshold domain. The dominance of leakage power in the subthreshold regime demands architectures that i) reduce overall area, ii) increase the utility of transistors, while iii) maintaining acceptable CPI efficiency. We confirm these observations by performing SPICE-level analysis of 21 sensor network processors and memory architectures. Our best sensor platform, implemented in 130nm CMOS and operating at 235 mV, only consumes 1.38 pJ/instruction, nearly an order of magnitude less energy than previously published sensor network processor results. This design, accompanied by bulk-silicon solar cells for energy scavenging, has been manufactured by IBM and is currently being tested.