Differential temperature sensors: Review of applications in the test and characterization of circuits, usage and design methodology

Differential temperature sensors can be placed in integrated circuits to extract a signature ofthe power dissipated by the adjacent circuit blocks built in the same silicon die. This review paper firstdiscusses the singularity that differential temperature sensors provide with respect to other sensortopologies, with circuit monitoring being their main application. The paper focuses on the monitoringof radio-frequency analog circuits. The strategies to extract the power signature of the monitoredcircuit are reviewed, and a list of application examples in the domain of test and characterizationis provided. As a practical example, we elaborate the design methodology to conceive, step bystep, a differential temperature sensor to monitor the aging degradation in a class-A linear poweramplifier working in the 2.4 GHz Industrial Scientific Medical—ISM—band. It is discussed how,for this particular application, a sensor with a temperature resolution of 0.02 K and a high dynamicrange is required. A circuit solution for this objective is proposed, as well as recommendations for thedimensions and location of the devices that form the temperature sensor. The paper concludes with adescription of a simple procedure to monitor time variability.Postprint (published version

Neuro-memristive Circuits for Edge Computing: A review

The volume, veracity, variability, and velocity of data produced from the ever-increasing network of sensors connected to Internet pose challenges for power management, scalability, and sustainability of cloud computing infrastructure. Increasing the data processing capability of edge computing devices at lower power requirements can reduce several overheads for cloud computing solutions. This paper provides the review of neuromorphic CMOS-memristive architectures that can be integrated into edge computing devices. We discuss why the neuromorphic architectures are useful for edge devices and show the advantages, drawbacks and open problems in the field of neuro-memristive circuits for edge computing

Ring oscillator clocks and margins

How much margin do we have to add to the delay lines of a bundled-data circuit? This paper is an attempt to give a methodical answer to this question, taking into account all sources of variability and the existing EDA machinery for timing analysis and sign-off. The paper is based on the study of the margins of a ring oscillator that substitutes a PLL as clock generator. A timing model is proposed that shows that a 12% margin for delay lines can be sufficient to cover variability in a 65nm technology. In a typical scenario, performance and energy improvements between 15% and 35% can be obtained by using a ring oscillator instead of a PLL. The paper concludes that a synchronous circuit with a ring oscillator clock shows similar benefits in performance and energy as those of bundled-data asynchronous circuits.Peer ReviewedPostprint (author's final draft

Experimental phase-error extraction and modelling in silicon photonic arrayed waveguide gratings

We present a detailed study of parameter sweeps of silicon photonic arrayed waveguide gratings (AWG), looking into the effects of phase errors in the delay lines, which are induced by fabrication variation. We fabricated AWGs with 8 wavelength channels spaced 200 GHz and 400 GHz apart. We swept the waveguide width of the delay lines, and also performed a sweep where we introduced increments of length to the waveguides to emulate different AWG layouts and look into the effect of the phase errors. With this more detailed study we could quantitatively confirm the results of earlier studies, showing the wider waveguides reduce the effect of phase errors and dramatically improve the performance of the AWGs in terms of insertion loss and crosstalk. We also looked into the effect of rotating the layout of the circuit on the mask, and here we could show that, contrary to results with older technologies, this no longer has an effect on the current generation of devices

A differential memristive synapse circuit for on-line learning in neuromorphic computing systems

Spike-based learning with memristive devices in neuromorphic computing architectures typically uses learning circuits that require overlapping pulses from pre- and post-synaptic nodes. This imposes severe constraints on the length of the pulses transmitted in the network, and on the network's throughput. Furthermore, most of these circuits do not decouple the currents flowing through memristive devices from the one stimulating the target neuron. This can be a problem when using devices with high conductance values, because of the resulting large currents. In this paper we propose a novel circuit that decouples the current produced by the memristive device from the one used to stimulate the post-synaptic neuron, by using a novel differential scheme based on the Gilbert normalizer circuit. We show how this circuit is useful for reducing the effect of variability in the memristive devices, and how it is ideally suited for spike-based learning mechanisms that do not require overlapping pre- and post-synaptic pulses. We demonstrate the features of the proposed synapse circuit with SPICE simulations, and validate its learning properties with high-level behavioral network simulations which use a stochastic gradient descent learning rule in two classification tasks.Comment: 18 Pages main text, 9 pages of supplementary text, 19 figures. Patente

Global design of analog cells using statistical optimization techniques

We present a methodology for automated sizing of analog cells using statistical optimization in a simulation based approach. This methodology enables us to design complex analog cells from scratch within reasonable CPU time. Three different specification types are covered: strong constraints on the electrical performance of the cells, weak constraints on this performance, and design objectives. A mathematical cost function is proposed and a bunch of heuristics is given to increase accuracy and reduce CPU time to minimize the cost function. A technique is also presented to yield designs with reduced variability in the performance parameters, under random variations of the transistor technological parameters. Several CMOS analog cells with complexity levels up to 48 transistors are designed for illustration. Measurements from fabricated prototypes demonstrate the suitability of the proposed methodology

Models wagging the dog: are circuits constructed with disparate parameters?

In a recent article, Prinz, Bucher, and Marder (2004) addressed the fundamental question of whether neural systems are built with a fixed blueprint of tightly controlled parameters or in a way in which properties can vary largely from one individual to another, using a database modeling approach. Here, we examine the main conclusion that neural circuits indeed are built with largely varying parameters in the light of our own experimental and modeling observations. We critically discuss the experimental and theoretical evidence, including the general adequacy of database approaches for questions of this kind, and come to the conclusion that the last word for this fundamental question has not yet been spoken