412 research outputs found
Low-power spatial computing using dynamic threshold devices
Asynchronous spatial computing systems exhibit only localized communication, their overall data-flow being controlled by handshaking. It is therefore straightforward to determine when a particular part of such a system is active. We show that using thin-body double-gate fully depleted SOI transistors, the shift in threshold voltage that can be produced by modulating the back-gate bias is sufficient to reduce subthreshold leakage power by a factor of more than 104 in typical circuits. Using TBFDSOI devices in spatial computing architectures will allow overall power to be greatly reduced while maintaining high performance
Optimization and Characterization of CMOS for Ultra Low Power Applications
Aggressive voltage scaling into the subthreshold operating region holds great promise for applications with strict energy budget. However, it has been established that higher speed superthreshold device is not suitable for moderate performance subthreshold circuits. The design constraint for selecting Vth and TOX is much more flexible for subthreshold circuits at low voltage level than superthreshold circuits. In order to obtain better performance from a device under subthreshold conditions, it is necessary to investigate and optimize the process and geometry parameters of a Si MOSFET at nanometer technology node. This paper calibrates the fabrication process parameters and electrical characteristics for n- and p-MOSFETs with 35 nm physical gate length. Thereafter, the calibrated device for superthreshold application is optimized for better performance under subthreshold conditions using TCAD simulation. The device simulated in this work shows 9.89% improvement in subthreshold slope and 34% advantage in ION/IOFF ratio for the same drive current
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Variability-aware low-power techniques for nanoscale mixed-signal circuits.
New circuit design techniques that accommodate lower supply voltages necessary for portable systems need to be integrated into the semiconductor intellectual property (IP) core. Systems that once worked at 3.3 V or 2.5 V now need to work at 1.8 V or lower, without causing any performance degradation. Also, the fluctuation of device characteristics caused by process variation in nanometer technologies is seen as design yield loss. The numerous parasitic effects induced by layouts, especially for high-performance and high-speed circuits, pose a problem for IC design. Lack of exact layout information during circuit sizing leads to long design iterations involving time-consuming runs of complex tools. There is a strong need for low-power, high-performance, parasitic-aware and process-variation-tolerant circuit design. This dissertation proposes methodologies and techniques to achieve variability, power, performance, and parasitic-aware circuit designs. Three approaches are proposed: the single iteration automatic approach, the hybrid Monte Carlo and design of experiments (DOE) approach, and the corner-based approach. Widely used mixed-signal circuits such as analog-to-digital converter (ADC), voltage controlled oscillator (VCO), voltage level converter and active pixel sensor (APS) have been designed at nanoscale complementary metal oxide semiconductor (CMOS) and subjected to the proposed methodologies. The effectiveness of the proposed methodologies has been demonstrated through exhaustive simulations. Apart from these methodologies, the application of dual-oxide and dual-threshold techniques at circuit level in order to minimize power and leakage is also explored
Particle Swarm Optimization Algorithm for Leakage Power Reduction in VLSI Circuits
 Leakage power is the dominant source of power dissipation innanometer technology. As per the International Technology Roadmap forSemiconductors (ITRS) static power dominates dynamic power with theadvancement in technology. One of the well-known techniques used forleakage reduction is Input Vector Control (IVC). Due to stacking effect inIVC, it gives less leakage for the Minimum Leakage Vector (MLV) appliedat inputs of test circuit. This paper introduces Particle Swarm Optimization(PSO) algorithm to the field of VLSI to find minimum leakage vector.Another optimization algorithm called Genetic algorithm (GA) is alsoimplemented to search MLV and compared with PSO in terms of number ofiterations. The proposed approach is validated by simulating few testcircuits. Both GA and PSO algorithms are implemented in Verilog HDLand the simulations are carried out using Xilinx 9.2i. From the simulationresults it is found that PSO based approach is best in finding MLVcompared to Genetic based implementation as PSO technique uses lessruntime compared to GA. To the best of the author’s knowledge PSOalgorithm is used in IVC technique to optimize power for the first time andit is quite successful in searching MLV
Experimental and simulation study of 1D silicon nanowire transistors using heavily doped channels
The experimental results from 8 nm diameter silicon nanowire junctionless field effect transistors with gate lengths of 150 nm are presented that demonstrate on-currents up to 1.15 mA/m for 1.0 V and 2.52 mA/m for 1.8 V gate overdrive with an off-current set at 100 nA/m. On- to off-current ratios above 108 with a subthreshold slope of 66 mV/dec are demonstrated at 25 oC. Simulations using drift-diffusion which include densitygradient quantum corrections provide excellent agreement with the experimental results. The simulations demonstrate that the present silicon-dioxide gate dielectric only allows the gate to be scaled to 25 nm length before short-channel effects significantly reduce the performance. If high-K dielectrics replace some parts of the silicon dioxide then the technology can be scaled to at least 10 nm gatelength
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