Analog Reconfigurable Circuits

The aim of this paper is to present an overview of a new branch of analog electronics represented by analog reconfigurable circuits. The reconfiguration of analog circuits has been known and used since the beginnings of electronics, but the universal reconfigurable circuits called Field Programmable Analog Arrays (FPAA) have been developed over the last two decades. This paper presents the classification of analog circuit reconfiguration, examples of FPAA solutions obtained as academic projects and commercially available ones, as well as some application examples of the dynamic reconfiguration of FPAA.

Electronic Photonic Integrated Circuits and Control Systems

Photonic systems can operate at frequencies several orders of magnitude higher than electronics, whereas electronics offers extremely high density and easily built memories. Integrated photonic-electronic systems promise to combine advantage of both, leading to advantages in accuracy, reconfigurability and energy efficiency. This work concerns of hybrid and monolithic electronic-photonic system design. First, a high resolution voltage supply to control the thermooptic photonic chip for time-bin entanglement is described, in which the electronics system controller can be scaled with more number of power channels and the ability to daisy-chain the devices. Second, a system identification technique embedded with feedback control for wavelength stabilization and control model in silicon nitride photonic integrated circuits is proposed. Using the system, the wavelength in thermooptic device can be stabilized in dynamic environment. Third, the generation of more deterministic photon sources with temporal multiplexing established using field programmable gate arrays (FPGAs) as controller photonic device is demonstrated for the first time. The result shows an enhancement to the single photon output probability without introducing additional multi-photon noise. Fourth, multiple-input and multiple-output (MIMO) control of a silicon nitride thermooptic photonic circuits incorporating Mach Zehnder interferometers (MZIs) is demonstrated for the first time using a dual proportional integral reference tracking technique. The system exhibits improved performance in term of control accuracy by reducing wavelength peak drift due to internal and external disturbances. Finally, a monolithically integrated complementary metal oxide semiconductor (CMOS) nanophotonic segmented transmitter is characterized. With segmented design, the monolithic Mach Zehnder modulator (MZM) shows a low link sensitivity and low insertion loss with driver flexibility

Exploiting All-Programmable System on Chips for Closed-Loop Real-Time Neural Interfaces

High-density microelectrode arrays (HDMEAs) feature thousands of recording electrodes in a single chip with an area of few square millimeters. The obtained electrode density is comparable and even higher than the typical density of neuronal cells in cortical cultures. Commercially available HDMEA-based acquisition systems are able to record the neural activity from the whole array at the same time with submillisecond resolution. These devices are a very promising tool and are increasingly used in neuroscience to tackle fundamental questions regarding the complex dynamics of neural networks. Even if electrical or optical stimulation is generally an available feature of such systems, they lack the capability of creating a closed-loop between the biological neural activity and the artificial system. Stimuli are usually sent in an open-loop manner, thus violating the inherent working basis of neural circuits that in nature are constantly reacting to the external environment. This forbids to unravel the real mechanisms behind the behavior of neural networks. The primary objective of this PhD work is to overcome such limitation by creating a fullyreconfigurable processing system capable of providing real-time feedback to the ongoing neural activity recorded with HDMEA platforms. The potentiality of modern heterogeneous FPGAs has been exploited to realize the system. In particular, the Xilinx Zynq All Programmable System on Chip (APSoC) has been used. The device features reconfigurable logic, specialized hardwired blocks, and a dual-core ARM-based processor; the synergy of these components allows to achieve high elaboration performances while maintaining a high level of flexibility and adaptivity. The developed system has been embedded in an acquisition and stimulation setup featuring the following platforms: \u2022 3\ub7Brain BioCam X, a state-of-the-art HDMEA-based acquisition platform capable of recording in parallel from 4096 electrodes at 18 kHz per electrode. \u2022 PlexStim\u2122 Electrical Stimulator System, able to generate electrical stimuli with custom waveforms to 16 different output channels. \u2022 Texas Instruments DLP\uae LightCrafter\u2122 Evaluation Module, capable of projecting 608x684 pixels images with a refresh rate of 60 Hz; it holds the function of optical stimulation. All the features of the system, such as band-pass filtering and spike detection of all the recorded channels, have been validated by means of ex vivo experiments. Very low-latency has been achieved while processing the whole input data stream in real-time. In the case of electrical stimulation the total latency is below 2 ms; when optical stimuli are needed, instead, the total latency is a little higher, being 21 ms in the worst case. The final setup is ready to be used to infer cellular properties by means of closed-loop experiments. As a proof of this concept, it has been successfully used for the clustering and classification of retinal ganglion cells (RGCs) in mice retina. For this experiment, the light-evoked spikes from thousands of RGCs have been correctly recorded and analyzed in real-time. Around 90% of the total clusters have been classified as ON- or OFF-type cells. In addition to the closed-loop system, a denoising prototype has been developed. The main idea is to exploit oversampling techniques to reduce the thermal noise recorded by HDMEAbased acquisition systems. The prototype is capable of processing in real-time all the input signals from the BioCam X, and it is currently being tested to evaluate the performance in terms of signal-to-noise-ratio improvement

Controller implementation using analog reconfigurable hardware (FPAA)

This Thesis has the main target to make a research about FPAA/dpASPs devices and technologies applied to control systems. These devices provide easy way to emulate analog circuits that can be reconfigurable by programming tools from manufactures and in case of dpASPs are able to be dynamically reconfigurable on the fly. It is described different kinds of technologies commercially available and also academic projects from researcher groups. These technologies are very recent and are in ramp up development to achieve a level of flexibility and integration to penetrate more easily the market. As occurs with CPLD/FPGAs, the FPAA/dpASPs technologies have the target to increase the productivity, reducing the development time and make easier future hardware reconfigurations reducing the costs. FPAA/dpAsps still have some limitations comparing with the classic analog circuits due to lower working frequencies and emulation of complex circuits that require more components inside the integrated circuit. However, they have great advantages in sensor signal condition, filter circuits and control systems. This thesis focuses practical implementations of these technologies to control system PID controllers. The result of the experiments confirms the efficacy of FPAA/dpASPs on signal condition and control systems.Esta tese tem como principal objectivo fazer uma pesquisa sobre circuitos integrados e tecnologias das FPAA/dpASPs aplicadas a sistemas de controlo. Estes dispositivos possibilitam a emulação de circuitos analógicos que podem ser reconfiguráveis por ferramentas de programação dos próprios fabricantes e no caso dos dpASPs são capazes de ser dinamicamente reconfiguráveis em tempo real. São descritas diferentes tecnologias disponíveis no mercado e também projectos académicos de grupos de investigação. Estas tecnologias são muito recentes e estão em pleno desenvolvimento para alcançar um nível de flexibilidade e integração para penetrar mais facilmente no mercado. Como já ocorre com as CPLD/FPGAs, os FPAA/dpASPs tem o objectivo de aumentar a produtividade, reduzindo o tempo de desenvolvimento e facilitar reconfigurações futuras de hardware, reduzindo os custos. As FPAA/dpASPs ainda tem algumas limitações comparando com os circuitos analógicos clássicos devido a uma menor largura de banda de frequências de trabalho e à dificuldade de emulação de circuitos complexos que requerem mais componentes dentro do circuito integrado e portanto uma maior escala de integração. No entanto, estes circuitos integrados têm grandes vantagens e podem ser utilizados para aplicações de condicionamento do sinal de sensores, circuitos de filtros e sistemas de controlo. Esta tese concentra-se nas implementações práticas destas tecnologias aos sistemas de controlo usando controladores PID. Os resultados das experiências confirmam a eficácia das FPAA/dpASPs no condicionamento de sinal e sistemas de controlo

A Closed-Loop Bidirectional Brain-Machine Interface System For Freely Behaving Animals

A brain-machine interface (BMI) creates an artificial pathway between the brain and the external world. The research and applications of BMI have received enormous attention among the scientific community as well as the public in the past decade. However, most research of BMI relies on experiments with tethered or sedated animals, using rack-mount equipment, which significantly restricts the experimental methods and paradigms. Moreover, most research to date has focused on neural signal recording or decoding in an open-loop method. Although the use of a closed-loop, wireless BMI is critical to the success of an extensive range of neuroscience research, it is an approach yet to be widely used, with the electronics design being one of the major bottlenecks. The key goal of this research is to address the design challenges of a closed-loop, bidirectional BMI by providing innovative solutions from the neuron-electronics interface up to the system level. Circuit design innovations have been proposed in the neural recording front-end, the neural feature extraction module, and the neural stimulator. Practical design issues of the bidirectional neural interface, the closed-loop controller and the overall system integration have been carefully studied and discussed.To the best of our knowledge, this work presents the first reported portable system to provide all required hardware for a closed-loop sensorimotor neural interface, the first wireless sensory encoding experiment conducted in freely swimming animals, and the first bidirectional study of the hippocampal field potentials in freely behaving animals from sedation to sleep. This thesis gives a comprehensive survey of bidirectional BMI designs, reviews the key design trade-offs in neural recorders and stimulators, and summarizes neural features and mechanisms for a successful closed-loop operation. The circuit and system design details are presented with bench testing and animal experimental results. The methods, circuit techniques, system topology, and experimental paradigms proposed in this work can be used in a wide range of relevant neurophysiology research and neuroprosthetic development, especially in experiments using freely behaving animals

The ALICE TPC, a large 3-dimensional tracking device with fast readout for ultra-high multiplicity events

The design, construction, and commissioning of the ALICE Time-Projection Chamber (TPC) is described. It is the main device for pattern recognition, tracking, and identification of charged particles in the ALICE experiment at the CERN LHC. The TPC is cylindrical in shape with a volume close to 90 m^3 and is operated in a 0.5 T solenoidal magnetic field parallel to its axis. In this paper we describe in detail the design considerations for this detector for operation in the extreme multiplicity environment of central Pb--Pb collisions at LHC energy. The implementation of the resulting requirements into hardware (field cage, read-out chambers, electronics), infrastructure (gas and cooling system, laser-calibration system), and software led to many technical innovations which are described along with a presentation of all the major components of the detector, as currently realized. We also report on the performance achieved after completion of the first round of stand-alone calibration runs and demonstrate results close to those specified in the TPC Technical Design Report.Comment: 55 pages, 82 figure

Design and test of digitally-controlled power management IPs in advanced CMOS technologies

Les technologies avancées de semi-conducteur permettent de mettre en œuvre un contrôleur numérique dédié aux convertisseurs à découpage, de faible puissance et de fréquence de découpage élevée sur FPGA et ASIC. Cette thèse vise à proposer des contrôleurs numériques des performances élevées, de faible consommation énergétique et qui peuvent être implémentés facilement. En plus des contrôleurs numériques existants comme PID, RST, tri-mode et par mode de glissement, un nouveau contrôleur numérique (DDP) pour le convertisseur abaisseur de tension est proposé sur le principe de la commande prédictive: il introduit une nouvelle variable de contrôle qui est la position de la largeur d'impulsion permettant de contrôler de façon simultanée le courant dans l'inductance et la tension de sortie. La solution permet une dynamique très rapide en transitoire, aussi bien pour la variation de la charge que pour les changements de tension de référence. Les résultats expérimentaux sur FPGA vérifient les performances de ce contrôleur jusqu'à la fréquence de découpage de 4MHz. Un contrôleur numérique nécessite une modulation numérique de largeur d'impulsion (DPWM). L'approche Sigma-Delta de la DPWM est un bon candidat en ce qui concerne le compromis entre la complexité et les performances. Un guide de conception d'étage Sigma-Delta pour le DPWM est présenté. Une architecture améliorée de traditionnelles 1-1 MASH Sigma-Delta DPWM est synthétisée sans détérioration de la stabilité en boucle fermée ainsi qu'en préservant un coût raisonnable en ressources matérielles. Les résultats expérimentaux sur FPGA vérifient les performances des DPWM proposées en régimes stationnaire et transitoire. Deux ASICs sont portés en CMOS 0,35 m: le contrôleur en tri-mode pour le convertisseur abaisseur de tension et la commande par mode de glissement pour les convertisseurs abaisseur et élévateur de tension. Les bancs de test sont conçus pour conduire à un modèle d'évaluation de consommation énergétique. Pour le contrôleur en tri-mode, la consommation de puissance mesurée est seulement de 24,56mW/MHz lorsque le ratio de temps en régime de repos (stand-by) est 0,7. Les consommations de puissance de command par mode de glissement pour les convertisseurs abaisseur et élévateur de tension sont respectivement de 4,46mW/MHz et 4,79mW/MHz. En utilisant le modèle de puissance, une consommation de la puissance estimée inférieure à 1mW/MHz est envisageable dans des technologies CMOS plus avancées. Comparé aux contrôlés homologues analogiques de l'état de l'art, les prototypes ASICs illustrent la possibilité d'atteindre un rendement comparable pour les applications de faible et de moyen puissance mais avec l'avantage d'une meilleure précision et une meilleure flexibilité.Owing to the development of modern semiconductor technology, it is possible to implement a digital controller for low-power high switching frequency DC-DC power converter in FPGA and ASIC. This thesis is intended to propose digital controllers with high performance, low power consumption and simple implementation architecture. Besides existing digital control-laws, such as PID, RST, tri-mode and sliding-mode (SM), a novel digital control-law, direct control with dual-state-variable prediction (DDP control), for the buck converter is proposed based on the principle of predictive control. Compared to traditional current-mode predictive control, the predictions of the inductor current and the output voltage are performed at the same time by adding a control variable to the DPWM signal. DDP control exhibits very high dynamic transient performances under both load variations and reference changes. Experimental results in FPGA verify the performances at switching frequency up to 4MHz. For the boost converter exhibiting more serious nonlinearity, linear PID and nonlinear SM controllers are designed and implemented in FPGA to verify the performances. A digital control requires a DPWM. Sigma-Delta DPWM is therefore a good candidate regarding the implementation complexity and performances. An idle-tone free condition for Sigma-Delta DPWM is considered to reduce the inherent tone-noise under DC-excitation compared to the classic approach. A guideline for Sigma-Delta DPWM helps to satisfy proposed condition. In addition, an 1-1 MASH Sigma-Delta DPWM with a feasible dither generation module is proposed to further restrain the idle-tone effect without deteriorating the closed-loop stability as well as to preserve a reasonable cost in hardware resources. The FPGA-based experimental results verify the performances of proposed DPWM in steady-state and transient-state. Two ASICs in 0.35 m CMOS process are implemented including the tri-mode controller for buck converter and the PID and SM controllers for the buck and boost converters respectively. The lab-scale tests are designed to lead to a power assessment model suggesting feasible applications. For the tri-mode controller, the measured power consumption is only 24.56mW/MHz when the time ratio of stand-by operation mode is 0.7. As specific power optimization strategies in RTL and system-level are applied to the latter chip, the measured power consumptions of the SM controllers for buck converter and boost converter are 4.46mW/MHz and 4.79mW/MHz respectively. The power consumption is foreseen as less than 1mW/MHz when the process scales down to nanometer technologies based on the power-scaling model. Compared to the state-of-the-art analog counterpart, the prototype ICs are proven to achieve comparable or even higher power efficiency for low-to-medium power applications with the benefit of better accuracy and better flexibility.VILLEURBANNE-DOC'INSA-Bib. elec. (692669901) / SudocSudocFranceF

Design of Special Function Units in Modern Microprocessors

Today’s computing systems demand high performance for applications such as cloud computing, web-based search engines, network applications, and social media tasks. Such software applications involve an extensive use of hashing and arithmetic operations in their computation. In this thesis, we explore the use of new special function units (SFUs) for modern microprocessors, to accelerate such workloads. First, we design an SFU for hashing. Hashing can reduce the complexity of search and lookup from O(p) to O(p/n), where n bins are used and p items are being processed. In modern microprocessors, hashing is done in software. In our work, we propose a novel hardware hash unit design for use in modern microprocessors. Since the hash unit is designed at the hardware level, several advantages are obtained by our approach. First, a hardware-based hash unit executes a single hash instruction to perform a hash operation. In a software-based hashing in modern microprocessors, a hash operation is compiled into multiple instructions, thereby degrading performance. Second, software-based hashing stores hash data in a DRAM (also, hash operation entries can be stored in one of the cache levels). In a hardware-based hash unit, hash data is stored in a dedicated memory module (a hardware hash table), which improves performance. Third, today’s operating systems execute multiple applications (processes) in parallel, which entail high memory utilization. Hence the operating systems require many context switching between different processes, which results in many cache misses. In a hardware-based hash unit, the cache misses is reduced significantly using the dedicated memory module (hash table). These advantages all reduce the power consumption and increase the overall system performance significantly with a minimal increase in the microprocessor’s die area. We evaluate our hardware-based hash unit and compare its performance with software-based hashing. We start by evaluating our design approach at the micro-architecture level in terms of system performance. After that, we design our approach at the circuit level design to obtain the area overhead. Also, we analyze our design’s power and delay for each hash operation. These results are compared with a traditional hashing implementation. Then, we present an FPGA-based coprocessor for hash unit acceleration, applied to a virus checking application. Second, we present an SFU to speed up arithmetic operations. We call this arithmetic SFU a programmable arithmetic unit (PAU). In modern microprocessors, applications that require heavy arithmetic computations are done in software. To improve the performance for such computations, we present a programmable arithmetic unit (PAU), a partially reconfigurable methodology for arithmetic applications. The PAU consists of a set of IP blocks connected to a reconfigurable FPGA controller via a fast mesh-based interconnect. The IP blocks in the PAU can be any IP block such as adders, subtractors, multipliers, comparators and sign extension units. The PAU can have one or more copies of the same IP block (for example, 5 adders and 7 multipliers). The FPGA controller is an on-chip FPGA-based reconfigurable control fabric. The FPGA controller enables different arithmetic applications to be embedded on the PAU. The FPGA controller is programmed for different applications. The reconfigurable logic is based on a LUT-based design like a traditional FPGA. The FPGA controller and the IP blocks in the PAU communicate via a high speed ring data fabric. In our work, we use the PAU as an SFU in modern microprocessors. We compare the performance of different hardware-based arithmetic applications in the PAU with software-based implementations in modern microprocessors