Memcapacitive Devices in Logic and Crossbar Applications

Over the last decade, memristive devices have been widely adopted in computing for various conventional and unconventional applications. While the integration density, memory property, and nonlinear characteristics have many benefits, reducing the energy consumption is limited by the resistive nature of the devices. Memcapacitors would address that limitation while still having all the benefits of memristors. Recent work has shown that with adjusted parameters during the fabrication process, a metal-oxide device can indeed exhibit a memcapacitive behavior. We introduce novel memcapacitive logic gates and memcapacitive crossbar classifiers as a proof of concept that such applications can outperform memristor-based architectures. The results illustrate that, compared to memristive logic gates, our memcapacitive gates consume about 7x less power. The memcapacitive crossbar classifier achieves similar classification performance but reduces the power consumption by a factor of about 1,500x for the MNIST dataset and a factor of about 1,000x for the CIFAR-10 dataset compared to a memristive crossbar. Our simulation results demonstrate that memcapacitive devices have great potential for both Boolean logic and analog low-power applications

A 2.5MHz 55dB Switched-Current BandPass ΣΔ Modulator for AM Signal Conversion.

We present a Switched-Current (SI) fourth-order bandpass ΣΔ modulator IC prototype. It uses fully-differential circuits in 0.8μm CMOS technology to obtain a Dynamic Range (DR) larger than 55dB at 2.5MHz center frequency with 30kHz bandwidth - in accordance to the requirements of AM digital receivers. The prototype incorporates a single-ended to fully-differential current-mode buffer for testing purposes. The power consumption of the whole prototype (modulator plus buffer) is 60mW from a 5V supply voltage.This work has been supported by the European Union, under ESPRIT Project 8795-AMFIS.Peer reviewe

Homogeneous Spiking Neuromorphic System for Real-World Pattern Recognition

A neuromorphic chip that combines CMOS analog spiking neurons and memristive synapses offers a promising solution to brain-inspired computing, as it can provide massive neural network parallelism and density. Previous hybrid analog CMOS-memristor approaches required extensive CMOS circuitry for training, and thus eliminated most of the density advantages gained by the adoption of memristor synapses. Further, they used different waveforms for pre and post-synaptic spikes that added undesirable circuit overhead. Here we describe a hardware architecture that can feature a large number of memristor synapses to learn real-world patterns. We present a versatile CMOS neuron that combines integrate-and-fire behavior, drives passive memristors and implements competitive learning in a compact circuit module, and enables in-situ plasticity in the memristor synapses. We demonstrate handwritten-digits recognition using the proposed architecture using transistor-level circuit simulations. As the described neuromorphic architecture is homogeneous, it realizes a fundamental building block for large-scale energy-efficient brain-inspired silicon chips that could lead to next-generation cognitive computing.Comment: This is a preprint of an article accepted for publication in IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol 5, no. 2, June 201

Digital Offset Calibration of an OPAMP Towards Improving Static Parameters of 90 nm CMOS DAC

In this paper, an on-chip self-calibrated 8-bit R-2R digital-to-analog converter (DAC) based on digitally compensated input offset of the operational amplifier (OPAMP) is presented. To improve the overall DAC performance, a digital offset cancellation method was used to compensate deviations in the input offset voltage of the OPAMP caused by process variations. The whole DAC as well as offset compensation circuitry were designed in a standard 90 nm CMOS process. The achieved results show that after the self-calibration process, the improvement of 48% in the value of DAC offset error is achieved

Low-power, 10-Gbps 1.5-Vpp differential CMOS driver for a silicon electro-optic ring modulator

We present a novel driver circuit enabling electro-optic modulation with high extinction ratio from a co-designed silicon ring modulator. The driver circuit provides an asymmetric differential output at 10Gbps with a voltage swing up to 1.5V(pp) from a single 1.0V supply, maximizing the resonance-wavelength shift of depletion-type ring modulators while avoiding carrier injection. A test chip containing 4 reconfigurable driver circuits was fabricated in 40nm CMOS technology. The measured energy consumption for driving a 100fF capacitive load at 10Gbps was as low as 125fJ/bit and 220fJ/bit at 1V(pp) and 1.5V(pp) respectively. After flip-chip integration with ring modulators on a silicon-photonics chip, the power consumption was measured to be 210fJ/bit and 350fJ/bit respectively

Realization of a ROIC for 72x4 PV-IR detectors

Silicon Readout Integrated Circuits (ROIC) for HgCdTe Focal Plane Arrays of 1x4 and 72x4 photovoltaic detectors are represented. The analog circuit blocks are completely identical for both, while the digital control circuit is modified to take into account the larger array size. The manufacturing technology is 0.35μm, double poly-Si, three-metal CMOS process. ROIC structure includes four elements TDI functioning with a super sampling rate of 3, bidirectional scanning, dead pixel de-selection, automatic gain adjustment in response to pixel deselection besides programmable four gain setting (up to 2.58pC storage), and programmable integration time. ROIC has four outputs with a dynamic range of 2.8V (from 1.2V to 4V) for an output load of 10pF capacitive in parallel with 1MΩ resistance, and operates at a clock frequency of 5 MHz. The input referred noise is less than 1037 μV with 460 fF integration capacitor, corresponding to 2978 electrons