Playing with number representations and operator-level approximations

International audienceEnergy consumption is one of the major issues in computing today shared by all domains in computer science, from high-performance computing to embedded systems. The two main factors that influence energy consumption is the execution time and data volume. In the recent years, approximation is receiving renewed interests to improve both speed and energy consumption in embedded systems. Many applications in embedded systems do not require high precision/accuracy, and both software designers and hardware designers often seek for a golden point of the compromise between accuracy, speed, energy, and area cost in several layers with a broad range from application, software levels to architecture, circuit levels. Various techniques for approximate computing (AC) augment the design space by providing another set of design knobs for performance-accuracy trade-off. Stochastic computing (SC) is also seen as an alternative to conventional computing, since requiring less hardware and being more tolerant to soft errors at the expense of higher latency. SC uses a probabilistic model of computation and requires less hardware to implement complex operations. This talk will review the main techniques for operator-level approximations using various number representations and by playing with data word-length and types of operators, to show their benefit and drawbacks in terms of energy efficiency. We will also introduce the basic concepts of stochastic computing as well as its advantages in terms of robustness to errors and fair limitations

A Block-Parallel Architecture for Initial and Fine Synchronization in OFDM Systems

International audienceA novel low complexity parallel algorithm and its associated architecture are proposed for initial synchronization in orthogonal frequency division multiplexing (OFDM) systems. The method is hierarchical and uses auto-correlation for the first step and cross-correlation for the second step. The main advantage of the proposed approach is that it reduces the computational complexity by a factor of five (80%), while achieving similar mean square error (MSE) as cross-correlation based methods. The method uses block-level parallelism for auto-correlation step, which speeds up the computation significantly. After fixed-point analysis, a parallel architecture is proposed to accelerate both coarse and fine synchronization steps. This parallel architecture is scalable and provides speed-up proportional to number of parallel blocks

A Novel Approach for Ultra Low-Power WSN Node Generation

International audienceWireless Sensor Network (WSN) technology is now emerging with appli- cations in various domains of human life e.g. medicine, environmental monitoring and military surveillance etc. WSN systems consist of low-cost and low-power sensor nodes that communicate efficiently over short distances. It has been shown that power con- sumption is the biggest design constraint for such systems. Currently, WSN nodes are being designed using low-power microcontrollers. However, their power dissipation is still orders of magnitude too high and limits the wide-spreading of WSN technology. In this paper, we propose an alternative approach that uses hardware specialization and power-gating to generate distributed hardware micro-tasks. We target control-oriented tasks running on WSN nodes and present, as a case study, a lamp-switching applica- tion. Our approach is validated experimentally and shows prominent power gains over software implementation on a low-power microcontroller such as the MSP430

Power gain estimation of an event-driven wake-up controller dedicated to WSN's microcontroller

International audienceTo deal with Wireless Sensor Node's energy constraints , new architectural solutions have to be found. This paper proposes to analyze a WSN microcontroller subsystem power consumption to extract the main power contributors according to different applicative execution phases. The objective is to come out with the energy reduction potentiality offered by an additional module called Wake-Up Controller. This block is able to substitute to the main CPU for current tasks like data transfers between sensors, memories or radio and fine grain power/frequency management of the entire node's sub-modules. Power simulations of a microcontroller subsystem based on FDSOI28 technology, with and without the Wake-Up Controller use, are proposed. Results are presented for applicative scenarios ranging from very low to high activity rates. This study exhibits power gains from 14.5% to 76% in the full range attesting the future design of this new module

Power reconfigurable receiver model for energy-aware applications

International audienceThis paper presents a reconfigurable receiver model whose purpose is to enable the study of reconfiguration strategies for future energy-aware and adaptive transceivers. This model is based on Figure of Merits of measured circuits. To account for real-life RF interference mechanisms, a link quality estimator is also provided.We show that adapting the receiver performance to the channel conditions can lead to considerable power saving. The models proposed can easily be implemented in a wireless network simulation in order to validate the value of a reconfigurable architecture in real-world deployment scenarios

HarvWSNet: A co-simulation framework for energy harvesting wireless sensor networks

International audienceRecent advances in energy harvesting (EH) technologies now allow wireless sensor networks (WSNs) to extend their lifetime by scavenging the energy available in their environment. While simulation is the most widely used method to design and evaluate network protocols for WSNs, existing network simulators are not adapted to the simulation of EH-WSNs and most of them provide only a simple linear battery model. Therefore, there is a need for a framework suited to EH-WSN simulation and to lifetime prediction. We propose a co-simulation framework, HarvWSNet, based on WSNet and Matlab, that provides adequate tools for the simulation of the network protocols and the lifetime of EH-WSN. Indeed, the framework allows for the simulation of multi-node network scenarios while including a detailed description of each node's energy harvesting, management subsystem and its time-varying environmental parameters. A simulation case study based on a temperature monitoring application demonstrates HarvWSNet's ability to predict network lifetime while minimally penalizing simulation time

Back to Results Prototyping an Energy Harvesting Wireless Sensor Network Application Using HarvWSNet

International audienceIn this article, the HarvWSNet simulation framework is used to explore the feasibility of a structural health monitoring application based on a wireless sensor network. The aim is to show the value of a simulation-based approach for the architecture exploration and prototyping of severely energy constrained applications. In the target application, each network node performs a reading of temperature and/or acceleration and transmits the data to a base station every given period. A second objective of this work is to test the relevance of a power management algorithm whose role is to adapt the application quality of service to the instantaneous state of the energy harvesting module. The final goal is to propose a perpetually powered node architecture compatible with the user application requirements

Customizing Fixed-Point and Floating-Point Arithmetic - A Case Study in K-Means Clustering

International audienceThis paper presents a comparison between custom fixed-point (FxP) and floating-point (FlP) arithmetic, applied to bidimensional K-means clustering algorithm. After a discussion on the K-means clustering algorithm and arithmetic characteristics, hardware implementations of FxP and FlP arithmetic operators are compared in terms of area, delay and energy, for different bitwidth, using the ApxPerf2.0 framework. Finally, both are compared in the context of K-means clustering. The direct comparison shows the large difference between 8-to-16-bit FxP and FlP operators, FlP adders consuming 5-12× more energy than FxP adders, and multipliers 2-10× more. However, when applied to K-means clustering algorithm, the gap between FxP and FlP tightens. Indeed, the accuracy improvements brought by FlP make the computation more accurate and lead to an accuracy equivalent to FxP with less iterations of the algorithm, proportionally reducing the global energy spent. The 8-bit version of the algorithm becomes more profitable using FlP, which is 80% more accurate with only 1.6× more energy. This paper finally discusses the stake of custom FlP for low-energy general-purpose computation, thanks to its ease of use, supported by an energy overhead lower than what could have been expected

Architectures de contrôleurs ultra-faible consommation pour noeuds de réseau de capteurs sans fil

National audienceCet article traite de la conception d'architectures de contrôle pour les noeuds d'un réseau de capteurs. En utilisant conjointement la spécialisation du matériel pour réduire la consommation dynamique et la coupure d'alimentation pour les phases de veille, nous proposons un paradigme d'architecture original ainsi que son flot de conception fonctionnel depuis des spécifications de haut-niveau (langage C associé à un langage spécifiquement conçu). Nous illustrons les gains apportés par un flot complet de génération de micro-tâches matérielles par rapport à des implantations logicielles classiques ciblant des micro-contrôleurs. En combinant la spécialisation matérielle avec des techniques de réduction de puissance statique (power gating), nous réduisons de façon très significative la puissance globale (et l'énergie) dissipée par le système. Les résultats sur des benchmarks issus du domaine des réseaux de capteurs montrent des gains en énergie allant jusqu'à deux ordres de grandeur par rapport aux meilleurs micro-contrôleurs faible consommation du domaine