Implementation Aspects of a Transmitted-Reference UWB Receiver

In this paper, we discuss the design issues of an ultra wide band (UWB) receiver targeting a single-chip CMOS implementation for low data-rate applications like ad hoc wireless sensor networks. A non-coherent transmitted reference (TR) receiver is chosen because of its small complexity compared to other architectures. After a brief recapitulation of the UWB fundamentals and a short discussion on the major differences between coherent and non-coherent receivers, we discuss issues, challenges and possible design solutions. Several simulation results obtained by means of a behavioral model are presented, together with an analysis of the trade-off between performance and complexity in an integrated circuit implementation

Fault-Tolerant Thresholds for Encoded Ancillae with Homogeneous Errors

I describe a procedure for calculating thresholds for quantum computation as a function of error model given the availability of ancillae prepared in logical states with independent, identically distributed errors. The thresholds are determined via a simple counting argument performed on a single qubit of an infinitely large CSS code. I give concrete examples of thresholds thus achievable for both Steane and Knill style fault-tolerant implementations and investigate their relation to threshold estimates in the literature.Comment: 14 pages, 5 figures, 3 tables; v2 minor edits, v3 completely revised, submitted to PR

Belief propagation decoding of quantum channels by passing quantum messages

Belief propagation is a powerful tool in statistical physics, machine learning, and modern coding theory. As a decoding method, it is ubiquitous in classical error correction and has also been applied to stabilizer-based quantum error correction. The algorithm works by passing messages between nodes of the factor graph associated with the code and enables efficient decoding, in some cases even up to the Shannon capacity of the channel. Here we construct a belief propagation algorithm which passes quantum messages on the factor graph and is capable of decoding the classical-quantum channel with pure state outputs. This gives explicit decoding circuits whose number of gates is quadratic in the blocklength of the code. We also show that this decoder can be modified to work with polar codes for the pure state channel and as part of a polar decoder for transmitting quantum information over the amplitude damping channel. These represent the first explicit capacity-achieving decoders for non-Pauli channels.Comment: v3: final version for publication; v2: improved discussion of the algorithm; 7 pages & 2 figures. v1: 6 pages, 1 figur

Transient error mitigation by means of approximate logic circuits

Mención Internacional en el título de doctorThe technological advances in the manufacturing of electronic circuits have allowed to greatly improve their performance, but they have also increased the sensitivity of electronic devices to radiation-induced errors. Among them, the most common effects are the SEEs, i.e., electrical perturbations provoked by the strike of high-energy particles, which may modify the internal state of a memory element (SEU) or generate erroneous transient pulses (SET), among other effects. These events pose a threat for the reliability of electronic circuits, and therefore fault-tolerance techniques must be applied to deal with them. The most common fault-tolerance techniques are based in full replication (DWC or TMR). These techniques are able to cover a wide range of failure mechanisms present in electronic circuits. However, they suffer from high overheads in terms of area and power consumption. For this reason, lighter alternatives are often sought at the expense of slightly reducing reliability for the least critical circuit sections. In this context a new paradigm of electronic design is emerging, known as approximate computing, which is based on improving the circuit performance in change of slight modifications of the intended functionality. This is an interesting approach for the design of lightweight fault-tolerant solutions, which has not been yet studied in depth. The main goal of this thesis consists in developing new lightweight fault-tolerant techniques with partial replication, by means of approximate logic circuits. These circuits can be designed with great flexibility. This way, the level of protection as well as the overheads can be adjusted at will depending on the necessities of each application. However, finding optimal approximate circuits for a given application is still a challenge. In this thesis a method for approximate circuit generation is proposed, denoted as fault approximation, which consists in assigning constant logic values to specific circuit lines. On the other hand, several criteria are developed to generate the most suitable approximate circuits for each application, by using this fault approximation mechanism. These criteria are based on the idea of approximating the least testable sections of circuits, which allows reducing overheads while minimising the loss of reliability. Therefore, in this thesis the selection of approximations is linked to testability measures. The first criterion for fault selection developed in this thesis uses static testability measures. The approximations are generated from the results of a fault simulation of the target circuit, and from a user-specified testability threshold. The amount of approximated faults depends on the chosen threshold, which allows to generate approximate circuits with different performances. Although this approach was initially intended for combinational circuits, an extension to sequential circuits has been performed as well, by considering the flip-flops as both inputs and outputs of the combinational part of the circuit. The experimental results show that this technique achieves a wide scalability, and an acceptable trade-off between reliability versus overheads. In addition, its computational complexity is very low. However, the selection criterion based in static testability measures has some drawbacks. Adjusting the performance of the generated approximate circuits by means of the approximation threshold is not intuitive, and the static testability measures do not take into account the changes as long as faults are approximated. Therefore, an alternative criterion is proposed, which is based on dynamic testability measures. With this criterion, the testability of each fault is computed by means of an implication-based probability analysis. The probabilities are updated with each new approximated fault, in such a way that on each iteration the most beneficial approximation is chosen, that is, the fault with the lowest probability. In addition, the computed probabilities allow to estimate the level of protection against faults that the generated approximate circuits provide. Therefore, it is possible to generate circuits which stick to a target error rate. By modifying this target, circuits with different performances can be obtained. The experimental results show that this new approach is able to stick to the target error rate with reasonably good precision. In addition, the approximate circuits generated with this technique show better performance than with the approach based in static testability measures. In addition, the fault implications have been reused too in order to implement a new type of logic transformation, which consists in substituting functionally similar nodes. Once the fault selection criteria have been developed, they are applied to different scenarios. First, an extension of the proposed techniques to FPGAs is performed, taking into account the particularities of this kind of circuits. This approach has been validated by means of radiation experiments, which show that a partial replication with approximate circuits can be even more robust than a full replication approach, because a smaller area reduces the probability of SEE occurrence. Besides, the proposed techniques have been applied to a real application circuit as well, in particular to the microprocessor ARM Cortex M0. A set of software benchmarks is used to generate the required testability measures. Finally, a comparative study of the proposed approaches with approximate circuit generation by means of evolutive techniques have been performed. These approaches make use of a high computational capacity to generate multiple circuits by trial-and-error, thus reducing the possibility of falling into local minima. The experimental results demonstrate that the circuits generated with evolutive approaches are slightly better in performance than the circuits generated with the techniques here proposed, although with a much higher computational effort. In summary, several original fault mitigation techniques with approximate logic circuits are proposed. These approaches are demonstrated in various scenarios, showing that the scalability and adaptability to the requirements of each application are their main virtuesLos avances tecnológicos en la fabricación de circuitos electrónicos han permitido mejorar en gran medida sus prestaciones, pero también han incrementado la sensibilidad de los mismos a los errores provocados por la radiación. Entre ellos, los más comunes son los SEEs, perturbaciones eléctricas causadas por el impacto de partículas de alta energía, que entre otros efectos pueden modificar el estado de los elementos de memoria (SEU) o generar pulsos transitorios de valor erróneo (SET). Estos eventos suponen un riesgo para la fiabilidad de los circuitos electrónicos, por lo que deben ser tratados mediante técnicas de tolerancia a fallos. Las técnicas de tolerancia a fallos más comunes se basan en la replicación completa del circuito (DWC o TMR). Estas técnicas son capaces de cubrir una amplia variedad de modos de fallo presentes en los circuitos electrónicos. Sin embargo, presentan un elevado sobrecoste en área y consumo. Por ello, a menudo se buscan alternativas más ligeras, aunque no tan efectivas, basadas en una replicación parcial. En este contexto surge una nueva filosofía de diseño electrónico, conocida como computación aproximada, basada en mejorar las prestaciones de un diseño a cambio de ligeras modificaciones de la funcionalidad prevista. Es un enfoque atractivo y poco explorado para el diseño de soluciones ligeras de tolerancia a fallos. El objetivo de esta tesis consiste en desarrollar nuevas técnicas ligeras de tolerancia a fallos por replicación parcial, mediante el uso de circuitos lógicos aproximados. Estos circuitos se pueden diseñar con una gran flexibilidad. De este forma, tanto el nivel de protección como el sobrecoste se pueden regular libremente en función de los requisitos de cada aplicación. Sin embargo, encontrar los circuitos aproximados óptimos para cada aplicación es actualmente un reto. En la presente tesis se propone un método para generar circuitos aproximados, denominado aproximación de fallos, consistente en asignar constantes lógicas a ciertas líneas del circuito. Por otro lado, se desarrollan varios criterios de selección para, mediante este mecanismo, generar los circuitos aproximados más adecuados para cada aplicación. Estos criterios se basan en la idea de aproximar las secciones menos testables del circuito, lo que permite reducir los sobrecostes minimizando la perdida de fiabilidad. Por tanto, en esta tesis la selección de aproximaciones se realiza a partir de medidas de testabilidad. El primer criterio de selección de fallos desarrollado en la presente tesis hace uso de medidas de testabilidad estáticas. Las aproximaciones se generan a partir de los resultados de una simulación de fallos del circuito objetivo, y de un umbral de testabilidad especificado por el usuario. La cantidad de fallos aproximados depende del umbral escogido, lo que permite generar circuitos aproximados con diferentes prestaciones. Aunque inicialmente este método ha sido concebido para circuitos combinacionales, también se ha realizado una extensión a circuitos secuenciales, considerando los biestables como entradas y salidas de la parte combinacional del circuito. Los resultados experimentales demuestran que esta técnica consigue una buena escalabilidad, y unas prestaciones de coste frente a fiabilidad aceptables. Además, tiene un coste computacional muy bajo. Sin embargo, el criterio de selección basado en medidas estáticas presenta algunos inconvenientes. No resulta intuitivo ajustar las prestaciones de los circuitos aproximados a partir de un umbral de testabilidad, y las medidas estáticas no tienen en cuenta los cambios producidos a medida que se van aproximando fallos. Por ello, se propone un criterio alternativo de selección de fallos, basado en medidas de testabilidad dinámicas. Con este criterio, la testabilidad de cada fallo se calcula mediante un análisis de probabilidades basado en implicaciones. Las probabilidades se actualizan con cada nuevo fallo aproximado, de forma que en cada iteración se elige la aproximación más favorable, es decir, el fallo con menor probabilidad. Además, las probabilidades calculadas permiten estimar la protección frente a fallos que ofrecen los circuitos aproximados generados, por lo que es posible generar circuitos que se ajusten a una tasa de fallos objetivo. Modificando esta tasa se obtienen circuitos aproximados con diferentes prestaciones. Los resultados experimentales muestran que este método es capaz de ajustarse razonablemente bien a la tasa de fallos objetivo. Además, los circuitos generados con esta técnica muestran mejores prestaciones que con el método basado en medidas estáticas. También se han aprovechado las implicaciones de fallos para implementar un nuevo tipo de transformación lógica, consistente en sustituir nodos funcionalmente similares. Una vez desarrollados los criterios de selección de fallos, se aplican a distintos campos. En primer lugar, se hace una extensión de las técnicas propuestas para FPGAs, teniendo en cuenta las particularidades de este tipo de circuitos. Esta técnica se ha validado mediante experimentos de radiación, los cuales demuestran que una replicación parcial con circuitos aproximados puede ser incluso más robusta que una replicación completa, ya que un área más pequeña reduce la probabilidad de SEEs. Por otro lado, también se han aplicado las técnicas propuestas en esta tesis a un circuito de aplicación real, el microprocesador ARM Cortex M0, utilizando un conjunto de benchmarks software para generar las medidas de testabilidad necesarias. Por ´último, se realiza un estudio comparativo de las técnicas desarrolladas con la generación de circuitos aproximados mediante técnicas evolutivas. Estas técnicas hacen uso de una gran capacidad de cálculo para generar múltiples circuitos mediante ensayo y error, reduciendo la posibilidad de caer en algún mínimo local. Los resultados confirman que, en efecto, los circuitos generados mediante técnicas evolutivas son ligeramente mejores en prestaciones que con las técnicas aquí propuestas, pero con un coste computacional mucho mayor. En definitiva, se proponen varias técnicas originales de mitigación de fallos mediante circuitos aproximados. Se demuestra que estas técnicas tienen diversas aplicaciones, haciendo de la flexibilidad y adaptabilidad a los requisitos de cada aplicación sus principales virtudes.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Raoul Velazco.- Secretario: Almudena Lindoso Muñoz.- Vocal: Jaume Segura Fuste

Bit-Vector Model Counting using Statistical Estimation

Approximate model counting for bit-vector SMT formulas (generalizing \#SAT) has many applications such as probabilistic inference and quantitative information-flow security, but it is computationally difficult. Adding random parity constraints (XOR streamlining) and then checking satisfiability is an effective approximation technique, but it requires a prior hypothesis about the model count to produce useful results. We propose an approach inspired by statistical estimation to continually refine a probabilistic estimate of the model count for a formula, so that each XOR-streamlined query yields as much information as possible. We implement this approach, with an approximate probability model, as a wrapper around an off-the-shelf SMT solver or SAT solver. Experimental results show that the implementation is faster than the most similar previous approaches which used simpler refinement strategies. The technique also lets us model count formulas over floating-point constraints, which we demonstrate with an application to a vulnerability in differential privacy mechanisms

Fast and accurate SER estimation for large combinational blocks in early stages of the design

Soft Error Rate (SER) estimation is an important challenge for integrated circuits because of the increased vulnerability brought by technology scaling. This paper presents a methodology to estimate in early stages of the design the susceptibility of combinational circuits to particle strikes. In the core of the framework lies MASkIt , a novel approach that combines signal probabilities with technology characterization to swiftly compute the logical, electrical, and timing masking effects of the circuit under study taking into account all input combinations and pulse widths at once. Signal probabilities are estimated applying a new hybrid approach that integrates heuristics along with selective simulation of reconvergent subnetworks. The experimental results validate our proposed technique, showing a speedup of two orders of magnitude in comparison with traditional fault injection estimation with an average estimation error of 5 percent. Finally, we analyze the vulnerability of the Decoder, Scheduler, ALU, and FPU of an out-of-order, superscalar processor design.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness and Feder Funds under grant TIN2013-44375-R, by the Generalitat de Catalunya under grant FI-DGR 2016, and by the FP7 program of the EU under contract FP7-611404 (CLERECO).Peer ReviewedPostprint (author's final draft

A Bayesian approach for inferring neuronal connectivity from calcium fluorescent imaging data

Deducing the structure of neural circuits is one of the central problems of modern neuroscience. Recently-introduced calcium fluorescent imaging methods permit experimentalists to observe network activity in large populations of neurons, but these techniques provide only indirect observations of neural spike trains, with limited time resolution and signal quality. In this work we present a Bayesian approach for inferring neural circuitry given this type of imaging data. We model the network activity in terms of a collection of coupled hidden Markov chains, with each chain corresponding to a single neuron in the network and the coupling between the chains reflecting the network's connectivity matrix. We derive a Monte Carlo Expectation--Maximization algorithm for fitting the model parameters; to obtain the sufficient statistics in a computationally-efficient manner, we introduce a specialized blockwise-Gibbs algorithm for sampling from the joint activity of all observed neurons given the observed fluorescence data. We perform large-scale simulations of randomly connected neuronal networks with biophysically realistic parameters and find that the proposed methods can accurately infer the connectivity in these networks given reasonable experimental and computational constraints. In addition, the estimation accuracy may be improved significantly by incorporating prior knowledge about the sparseness of connectivity in the network, via standard L$_1$ penalization methods.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS303 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org