Rafael Serrano-Gotarredona

CAVIAR: A 45k Neuron, 5M Synapse, 12G Connects/s AER Hardware Sensory–Processing– Learning–Actuating System for High-Speed Visual Object Recognition and Tracking

This paper describes CAVIAR, a massively parallel hardware implementation of a spike-based sensing-processing-learning-actuating system inspired by the physiology of the nervous system. CAVIAR uses the asynchronous address-event representation (AER) communication framework and was developed in the context of a European Union funded project. It has four custom mixed-signal AER chips, five custom digital AER interface components, 45 k neurons (spiking cells), up to 5 M synapses, performs 12 G synaptic operations per second, and achieves millisecond object recognition and tracking latencies.

A Spatial Contrast Retina With On-Chip Calibration for Neuromorphic Spike-Based AER Vision Systems

We present a 32 times 32 pixels contrast retina microchip that provides its output as an address event representation (AER) stream. Spatial contrast is computed as the ratio between pixel photocurrent and a local average between neighboring pixels obtained with a diffuser network. This current-based computation produces an important amount of mismatch between neighboring pixels, because the currents can be as low as a few pico-amperes. Consequently, a compact calibration circuitry has been included to trimm each pixel. Measurements show a reduction in mismatch standard deviation from 57% to 6.6% (indoor light). The paper describes the design of the pixel with its spatial contrast computation and calibration sections. About one third of pixel area is used for a 5-bit calibration circuit. Area of pixel is 58 mum times 56 mum , while its current consumption is about 20 nA at 1-kHz event rate. Extensive experimental results are provided for a prototype fabricated in a standard 0.35-mum CMOS process.

A Neuromorphic Cortical-Layer Microchip for Spike-Based Event Processing Vision Systems

We present a neuromorphic cortical-layer processing microchip for address event representation (AER) spike-based processing systems. The microchip computes 2-D convolutions of video information represented in AER format in real time. AER, as opposed to conventional frame-based video representation, describes visual information as a sequence of events or spikes in a way similar to biological brains. This format allows for fast information identification and processing, without waiting to process complete image frames. The neuromorphic cortical-layer processing microchip presented in this paper computes convolutions of programmable kernels over the AER visual input information flow. It not only computes convolutions but also allows for a programmable forgetting rate, which in turn allows for a bio-inspired coincidence detection processing. Kernels are programmable and can be of arbitrary shape and arbitrary size of up to 32 times 32 pixels. The convolution processor operates on a pixel array of size 32 times 32, but can process an input space of up to 128 times 128 pixels. Larger pixel arrays can be directly processed by tiling arrays of chips. The chip receives and generates data in AER format, which is asynchronous and digital. However, its internal operation is based on analog low-current circuit techniques. The paper describes the architecture of the chip and circuits used for the pixels, including calibration techniques to overcome mismatch. Extensive experimental results are provided, describing pixel operation and calibration, convolution processing with and without forgetting, and high-speed recognition experiments like discriminating rotating propellers of different shape rotating at speeds of up to 5000 revolutions per second

On Real-Time AER 2-D Convolutions Hardware for Neuromorphic Spike-Based Cortical Processing

In this paper, a chip that performs real-time image convolutions with programmable kernels of arbitrary shape is presented. The chip is a first experimental prototype of reduced size to validate the implemented circuits and system level techniques. The convolution processing is based on the address-event-representation (AER) technique, which is a spike-based biologically inspired image and video representation technique that favors communication bandwidth for pixels with more information. As a first test prototype, a pixel array of 16times16 has been implemented with programmable kernel size of up to 16times16. The chip has been fabricated in a standard 0.35 mum complimentary metal-oxide-semiconductor (CMOS) process. The technique also allows to process larger size images by assembling 2D arrays of such chips. Pixel operation exploits low-power mixed analog-digital circuit techniques. Because of the low currents involved (down to nanoamperes or even picoamperes), an important amount of pixel area is devoted to mismatch calibration. The rest of the chip uses digital circuit techniques, both synchronous and asynchronous. The fabricated chip has been thoroughly tested, both at the pixel level and at the system level. Specific computer interfaces have been developed for generating AER streams from conventional computers and feeding them as inputs to the convolution chip, and for grabbing AER streams coming out of the convolution chip and storing and analyzing them on computers. Extensive experimental results are provided. At the end of this paper, we provide discussions and results on scaling up the approach for larger pixel arrays and multilayer cortical AER systems.

Compact low-power calibration mini-DACs for neural arrays with programmable weights

This paper considers the viability of compact low-resolution low-power mini digital-to-analog converters (mini-DACs) for use in large arrays of neural type cells, where programmable weights are required. Transistors are biased in weak inversion in order to yield small currents and low power consumptions, a necessity when building large size arrays. One important drawback of weak inversion operation is poor matching between transistors. The resulting effective precision of a fabricated array of 50 DACs turned out to be 47% (1.1 bits), due to transistor mismatch. However, it is possible to combine them two by two in order to build calibrated DACs, thus compensating for inter-DAC mismatch. It is shown experimentally that the precision can be improved easily by a factor of 10 (4.8% or 4.4 bits), which makes these DACs viable for low-resolution applications such as massive arrays of neural processing circuits. A design methodology is provided, and illustrated through examples, to obtain calibrated mini-DACs of a given target precision. As an example application, we show simulation results of using this technique to calibrate an array of digitally controlled integrate-and-fire neurons.

Current Mode Techniques for Sub-pico-Ampere Circuit Design

In this paper we explore the low current limit that standard CMOS technologies offer for current mode based VLSI designs. We show and validate a reliable circuit design technique for current mode signal processing down to fempto-amperes. We will take advantage of specific-current extractors and logarithmic current splitters to obtain on-chip sub-pA currents. Then we will use a special on-chip saw-tooth oscillator to monitor and measure currents down to a few fempto-amps. This way, sub-pA currents are characterized without driving them off-chip, nor requiring expensive instrumentation with complicated low leakage setups. A special current mirror is also introduced for reliably replicating such low currents. As an example, a simple log-domain first-order low-pass filter is implemented that uses a 100 fF capacitor and a 3.5 fA bias current to achieve a cut-off frequency of 0.5 Hz and using an area of 12 × 24.35 μm2 in a standard 0.35 μm CMOS process. A technique for characterizing noise at these currents is described and verified. Also, temperature dependence of leakage currents is measured as well.

A new charge-packet driven mismatch-calibrated integrate-and-fire neuron for processing positive and negative signals in AER based systems

We present the design and experimental measurements of an integrate-and-fire pixel for address-event-representation (AER) transceiver chips such that (a) input events can be weighted according to a digital word, (b) this weight includes a sign bit, (c) the incoming event is accompanied by a sign bit, and (d) the pixel can be calibrated to compensate for mismatch in large arrays of these pixels. A prototype has been fabricated in the AMS 0.35 /spl mu/m CMOS process, whose experimental measurement results are provided.

LVDS interface for AER links with burst mode operation capability

This paper presents the design and simulation of a serial AER LVDS communication link. It converts data from classical AER parallel bus with a 4-phase handshaking protocol into a bit stream which is transmitted serially into a single LVDS wire. At the receiver side data from the LVDS cable are transformed back to a parallel AER bus and handshaking signals are also properly managed. The link has been designed in a 90 nms technology. Extensive simulations have been performed demonstrating that the link can operate at a speed of 1 Gbps for all the technology corners, exhibiting a power consumption of 27.8 mW for the transmitter and 12.3 mW for the receiver. In the simulation the transmission channel was modelled as a 50 cm cat5E UTP cable, connected to the AER chip through 5 cm PCB traces modelled as a coupled microstrip transmission line. The design has been completed up to the layout level and has been submitted for fabrication. The transmitter and the receiver take up an area of 311times148 mum2 and 300x148 mum2 respectively.

High-speed image processing with AER-based components

A high speed sample image processing application using AER-based components is presented. The setup objective is to distinguish between two propellers of different shape rotating at high speed (around 1000 revolutions/sec) to show event-based systems capabilities in high speed applications. Event-based schemes allow the most relevant information to propagate faster through the system layers. So image processing is sped up because a rough result may be available when only a little part of the input has arrived. This setup is much faster than the conventional frame-based image processing systems because they would need to process more than 10kFrames/s to do the same task proposed here, whereas only few events are required with the event based technique

On mismatch properties of MOS and resistors calibrated ladder structures

The mismatch behaviour of MOS and resistor based calibrated ladder structures, used in arrays of DACs, is studied theoretically and experimentally. It is found that the calibrated DAC worst case output current standard deviation is approximately 1/3 that of its individual components. MOS experimental measurements illustrate the discussed mismatch behaviour. Directions on how to design ladder DACs for a target precision are provided.