ACME: An energy-efficient approximate bus encoding for I2C

In ultra low power systems with many peripherals, off-chip serial interconnects contribute significantly to the total energy budget. Leveraging the error-resilience characteristics of many embedded applications, the approximate computing paradigm has been applied to serial bus encodings to reduce interconnect consumption. However, the power model considered in previous works was purely capacitive. Accordingly, the objective of these approximate encodings was simply to reduce the transition count. While this works well for most bus standards, one notable exception is represented by I 2 C, whose open-drain physical connection makes the static energy consumed by logic-0 values on the bus extremely relevant. In this work, we propose ACME, the first approximate serial bus encoding targeting specifically I 2 C connections. With a simple encoding/decoding scheme, ACME concurrently reduces both the static and dynamic energy on the bus by maximizing the number of logic-1 values in codewords, while simultaneously reducing transitions. Using an accurate bus model and realistic capacitance and resistance values selected according to the I 2 C standard, we show that our encoding outperforms state-of-the-art solutions and reduces the total energy consumption on the bus by 57% on average, with an error smaller than 0.1%

Value-Deviation-Bounded Serial Data Encoding for Energy-Efficient Approximate Communication

Transferring data between ICs accounts for a growing proportion of system power in wearable and mobile systems. Reducing signal transitions reduces the dynamic power dissipated in this data transfer, but traditional approaches cannot be applied when the transfer interfaces are serial buses. To address this challenge, we present a family of optimal value-deviation-bounded approximate serial encoders (VDBS encoders) that significantly reduce signal transitions (and hence, dynamic power) for bit-serial communication interfaces. When the data in transfer are from sensors, VDBS encoding enables a tradeoff between power efficiency and application fidelity, by exploiting the tolerance of many of the typical algorithms consuming sensor data to deviations in values. We derive analytic formulations for the family of VDBS encoders and introduce an efficient algorithm that performs close to the Pareto-optimal encoders. We evaluate the algorithm in two applications: Encoding data between a camera and processor in a text-recognition system, and between an accelerometer and processor in a pedometer system. For the text recognizer, the algorithm reduces signal transitions by 55% on average, while maintaining OCR accuracy at over 90% for previously-correctly-recognized text. For the pedometer, the algorithm reduces signal transitions by an average of 54% in exchange for step count errors of under 5%

Approximate energy-efficient encoding for serial interfaces

Serial buses are ubiquitous interconnections in embedded computing systems that are used to interface processing elements with peripherals, such as sensors, actuators, and I/O controllers. Despite their limited wiring, as off-chip connections they can account for a significant amount of the total power consumption of a system-on-chip device. Encoding the information sent on these buses is the most intuitive and affordable way to reduce their power contribution; moreover, the encoding can be made even more effective by exploiting the fact that many embedded applications can tolerate intermediate approximations without a significant impact on the final quality of results, thus trading off accuracy for power consumption. We propose a simple yet very effective approximate encoding for reducing dynamic energy in serial buses. Our approach uses differential encoding as a baseline scheme and extends it with bounded approximations to overcome the intrinsic limitations of differential encoding for data with low temporal correlation. We show that the proposed scheme, in addition to yielding extremely compact codecs, is superior to all state-of-the-art approximate serial encodings over a wide set of traces representing data received or sent from/to sensor or actuators

Integrated PV Performance Monitoring System

The main aim of this research work is to design an accurate and reliable monitoring system to be integrated with solar electricity generating system. The amount of solar energy received on the surface of the earth varies due to meteorological conditions and apparent trajectory of the sun. Due to this, the availability of sunlight is an average of 5-6 hours per day throughout the year in Malaysia. The performance monitoring system is required to ensure that the PV based solar electricity generating system is operating at an optimum level. The PV monitoring system is able to measure all the important parameters that determine an optimum performance. The measured values are recorded continuously, as the data acquisition system is connected to a computer, and data is stored at fixed intervals. The hardware is fully supported by software designed to give full flexibility in terms of data retrieval and processing. The data can be locally used and can be transmitted via internet for monitoring purposes. The data that appears directly on the local monitoring system is displayed via graphical user interface that was created by using Visualbasic.net. The Apache software was used to retrieve data from the internet. The transmitted data received by the remote terminal can be viewed by using any internet browser

A novel travelling-wave Zeeman decelerator for production of cold radicals

Recent advances in producing samples of molecules at very low temperatures have been motivated by the prospects of studying collisions and chemical reactions with controllable collision energies, performing high resolution spectroscopy and precision measurements for fundamental physics, quantum information processing and quantum simulation. Methods based on the deceleration of supersonic molecular beams are particularly well suited for collision experiments since the final longitudinal velocity of the sample can be tuned over a wide range with narrow velocity spreads. Zeeman deceleration methods rely on the state-dependent interaction of neutral paramagnetic atoms or molecules with a time-dependent inhomogeneous magnetic fields. For this reason, the Zeeman deceleration technique is especially effective in open-shell systems such as molecular radicals or metastable atoms and molecules. Here, an experimental realization of a novel travelling-wave Zeeman decelerator based on a double-helix wire geometry is presented. The decelerator is capable of decelerating samples of paramagnetic atoms and molecules from 560 m/s forward velocity down to an arbitrary final velocity. Compared to the conventional Zeeman or Stark decelerators, the presented decelerator exhibits full three-dimensional confinement of the molecules at a full range of velocities starting from the initial forward velocity down to the arbitrary final velocity, leading to an improvement of the overall phase-space acceptance compared to the conventional Zeeman and Stark decelerators. Operation of the decelerator is demonstrated by deceleration of a molecular beam of OH radicals from an initial velocity of 445 m/s down to a final velocity of 350 m/s. The experimental results are accompanied by numerical trajectory simulations confirming stable operation and showing phase-space stability of the decelerator. These results pave the way for the future cold-collision experiments. In the future, the traveling-wave Zeeman decelerator will serve as a source of cold paramagnetic molecules for hybrid trapping experiments

Design Techniques for Energy-Quality Scalable Digital Systems

Energy efficiency is one of the key design goals in modern computing. Increasingly complex tasks are being executed in mobile devices and Internet of Things end-nodes, which are expected to operate for long time intervals, in the orders of months or years, with the limited energy budgets provided by small form-factor batteries. Fortunately, many of such tasks are error resilient, meaning that they can toler- ate some relaxation in the accuracy, precision or reliability of internal operations, without a significant impact on the overall output quality. The error resilience of an application may derive from a number of factors. The processing of analog sensor inputs measuring quantities from the physical world may not always require maximum precision, as the amount of information that can be extracted is limited by the presence of external noise. Outputs destined for human consumption may also contain small or occasional errors, thanks to the limited capabilities of our vision and hearing systems. Finally, some computational patterns commonly found in domains such as statistics, machine learning and operational research, naturally tend to reduce or eliminate errors. Energy-Quality (EQ) scalable digital systems systematically trade off the quality of computations with energy efficiency, by relaxing the precision, the accuracy, or the reliability of internal software and hardware components in exchange for energy reductions. This design paradigm is believed to offer one of the most promising solutions to the impelling need for low-energy computing. Despite these high expectations, the current state-of-the-art in EQ scalable design suffers from important shortcomings. First, the great majority of techniques proposed in literature focus only on processing hardware and software components. Nonetheless, for many real devices, processing contributes only to a small portion of the total energy consumption, which is dominated by other components (e.g. I/O, memory or data transfers). Second, in order to fulfill its promises and become diffused in commercial devices, EQ scalable design needs to achieve industrial level maturity. This involves moving from purely academic research based on high-level models and theoretical assumptions to engineered flows compatible with existing industry standards. Third, the time-varying nature of error tolerance, both among different applications and within a single task, should become more central in the proposed design methods. This involves designing “dynamic” systems in which the precision or reliability of operations (and consequently their energy consumption) can be dynamically tuned at runtime, rather than “static” solutions, in which the output quality is fixed at design-time. This thesis introduces several new EQ scalable design techniques for digital systems that take the previous observations into account. Besides processing, the proposed methods apply the principles of EQ scalable design also to interconnects and peripherals, which are often relevant contributors to the total energy in sensor nodes and mobile systems respectively. Regardless of the target component, the presented techniques pay special attention to the accurate evaluation of benefits and overheads deriving from EQ scalability, using industrial-level models, and on the integration with existing standard tools and protocols. Moreover, all the works presented in this thesis allow the dynamic reconfiguration of output quality and energy consumption. More specifically, the contribution of this thesis is divided in three parts. In a first body of work, the design of EQ scalable modules for processing hardware data paths is considered. Three design flows are presented, targeting different technologies and exploiting different ways to achieve EQ scalability, i.e. timing-induced errors and precision reduction. These works are inspired by previous approaches from the literature, namely Reduced-Precision Redundancy and Dynamic Accuracy Scaling, which are re-thought to make them compatible with standard Electronic Design Automation (EDA) tools and flows, providing solutions to overcome their main limitations. The second part of the thesis investigates the application of EQ scalable design to serial interconnects, which are the de facto standard for data exchanges between processing hardware and sensors. In this context, two novel bus encodings are proposed, called Approximate Differential Encoding and Serial-T0, that exploit the statistical characteristics of data produced by sensors to reduce the energy consumption on the bus at the cost of controlled data approximations. The two techniques achieve different results for data of different origins, but share the common features of allowing runtime reconfiguration of the allowed error and being compatible with standard serial bus protocols. Finally, the last part of the manuscript is devoted to the application of EQ scalable design principles to displays, which are often among the most energy- hungry components in mobile systems. The two proposals in this context leverage the emissive nature of Organic Light-Emitting Diode (OLED) displays to save energy by altering the displayed image, thus inducing an output quality reduction that depends on the amount of such alteration. The first technique implements an image-adaptive form of brightness scaling, whose outputs are optimized in terms of balance between power consumption and similarity with the input. The second approach achieves concurrent power reduction and image enhancement, by means of an adaptive polynomial transformation. Both solutions focus on minimizing the overheads associated with a real-time implementation of the transformations in software or hardware, so that these do not offset the savings in the display. For each of these three topics, results show that the aforementioned goal of building EQ scalable systems compatible with existing best practices and mature for being integrated in commercial devices can be effectively achieved. Moreover, they also show that very simple and similar principles can be applied to design EQ scalable versions of different system components (processing, peripherals and I/O), and to equip these components with knobs for the runtime reconfiguration of the energy versus quality tradeoff