Block level voltage

Over the past years, state-of-art power optimization methods move towards higher abstraction levels that result in more efficient power savings. Among existing power optimization approaches, dynamic power management (DPM) is considered to be one of the most effective strategies. Depending on abstraction levels, DPM can be implemented in different formats but here we focus on scheduling that is more suitable for real-time system design use. This differs from the concurrent scheduling approaches that start from either the HLS (High-Level Synthesis) or RTS (Real-Time System) point of view, we propose a synergy solution of both approaches, namely block-level voltage/frequency scheduling (BLVFS). The presented block-level voltage/ frequency scheduling approach shows a generic solution for low power SoC (System on Chip) system design while the approaches which belong to the HLS and RTS categories have a strong dependency on the system functionalities. Consider a SoC as a combination of heterogeneous functional blocks, our approach provides efficient power savings by dynamically scheduling the scaling of voltage and frequency at the same time. Simulation results indicate that by using heuristic based strategies significant power savings can be achieved

Chapter One – An Overview of Architecture-Level Power- and Energy-Efficient Design Techniques

Power dissipation and energy consumption became the primary design constraint for almost all computer systems in the last 15 years. Both computer architects and circuit designers intent to reduce power and energy (without a performance degradation) at all design levels, as it is currently the main obstacle to continue with further scaling according to Moore's law. The aim of this survey is to provide a comprehensive overview of power- and energy-efficient “state-of-the-art” techniques. We classify techniques by component where they apply to, which is the most natural way from a designer point of view. We further divide the techniques by the component of power/energy they optimize (static or dynamic), covering in that way complete low-power design flow at the architectural level. At the end, we conclude that only a holistic approach that assumes optimizations at all design levels can lead to significant savings.Peer ReviewedPostprint (published version

Approximate Inference for Constructing Astronomical Catalogs from Images

We present a new, fully generative model for constructing astronomical catalogs from optical telescope image sets. Each pixel intensity is treated as a random variable with parameters that depend on the latent properties of stars and galaxies. These latent properties are themselves modeled as random. We compare two procedures for posterior inference. One procedure is based on Markov chain Monte Carlo (MCMC) while the other is based on variational inference (VI). The MCMC procedure excels at quantifying uncertainty, while the VI procedure is 1000 times faster. On a supercomputer, the VI procedure efficiently uses 665,000 CPU cores to construct an astronomical catalog from 50 terabytes of images in 14.6 minutes, demonstrating the scaling characteristics necessary to construct catalogs for upcoming astronomical surveys.Comment: accepted to the Annals of Applied Statistic

Duty-cycled Wake-up Schemes for Ultra-low Power Wireless Communications

In sensor network applications with low traffic intensity, idle channel listening is one of the main sources of energy waste.The use of a dedicated low-power wake-up receiver (WRx) which utilizes duty-cycled channel listening can significantlyreduce idle listening energy cost. In this thesis such a scheme is introduced and it is called DCW-MAC, an acronym forduty-cycled wake-up receiver based medium access control.We develop the concept in several steps, starting with an investigation into the properties of these schemes under idealizedconditions. This analysis show that DCW-MAC has the potential to significantly reduce energy costs, compared to twoestablished reference schemes based only on low-power wake up receivers or duty-cycled listening. Findings motivatefurther investigations and more detailed analysis of energy consumption. We do this in two separate steps, first concentratingon the energy required to transmit wake-up beacons and later include all energy costs in the analysis. The more completeanalysis makes it possible to optimize wake-up beacons and other DCW-MAC parameters, such as sleep and listen intervals,for minimal energy consumption. This shows how characteristics of the wake-up receiver influence how much, and if, energycan be saved and what the resulting average communication delays are. Being an analysis based on closed form expressions,rather than simulations, we can derive and verify good approximations of optimal energy consumption and resulting averagedelays, making it possible to quickly evaluate how a different wake-up receiver characteristic influences what is possible toachieve in different scenarios.In addition to the direct optimizations of the DCW-MAC scheme, we also provide a proof-of-concept in 65 nm CMOS,showing that the digital base-band needed to implement DCW-MAC has negligible energy consumption compared to manylow-power analog front-ends in literature. We also propose a a simple frame-work for comparing the relative merits ofanalog front-ends for wake-up receivers, where we use the experiences gained about DCW-MAC energy consumption toprovide a simple relation between wake-up receiver/analog front-end properties and energy consumption for wide ranges ofscenario parameters. Using this tool it is possible to compare analog front-ends used in duty-cycled wake-up schemes, evenif they are originally designed for different scenarios.In all, the thesis presents a new wake-up receiver scheme for low-power wireless sensor networks and provide a comprehensiveanalysis of many of its important properties

Automation and Control Architecture for Hybrid Pipeline Robots

The aim of this research project, towards the automation of the Hybrid Pipeline Robot (HPR), is the development of a control architecture and strategy, based on reconfiguration of the control strategy for speed-controlled pipeline operations and self-recovering action, while performing energy and time management. The HPR is a turbine powered pipeline device where the flow energy is converted to mechanical energy for traction of the crawler vehicle. Thus, the device is flow dependent, compromising the autonomy, and the range of tasks it can perform. The control strategy proposes pipeline operations supervised by a speed control, while optimizing the energy, solved as a multi-objective optimization problem. The states of robot cruising and self recovering, are controlled by solving a neuro-dynamic programming algorithm for energy and time optimization, The robust operation of the robot includes a self-recovering state either after completion of the mission, or as a result of failures leading to the loss of the robot inside the pipeline, and to guaranteeing the HPR autonomy and operations even under adverse pipeline conditions Two of the proposed models, system identification and tracking system, based on Artificial Neural Networks, have been simulated with trial data. Despite the satisfactory results, it is necessary to measure a full set of robot’s parameters for simulating the complete control strategy. To solve the problem, an instrumentation system, consisting on a set of probes and a signal conditioning board, was designed and developed, customized for the HPR’s mechanical and environmental constraints. As a result, the contribution of this research project to the Hybrid Pipeline Robot is to add the capabilities of energy management, for improving the vehicle autonomy, increasing the distances the device can travel inside the pipelines; the speed control for broadening the range of operations; and the self-recovery capability for improving the reliability of the device in pipeline operations, lowering the risk of potential loss of the robot inside the pipeline, causing the degradation of pipeline performance. All that means the pipeline robot can target new market sectors that before were prohibitive

Performance evaluation of wake-up radio based wireless body area network

Abstract. The last decade has been really ambitious in new research and development techniques to reduce energy consumption especially in wireless sensor networks (WSNs). Sensor nodes are usually battery-powered and thus have very limited lifetime. Energy efficiency has been the most important aspect to discuss when talking about wireless body area network (WBAN) in particular, since it is the bottleneck of these networks. Medium access control (MAC) protocols hold the vital position to determine the energy efficiency of a WBAN, which is a key design issue for battery operated sensor nodes. The wake-up radio (WUR) based MAC and physical layer (PHY) have been evaluated in this research work in order to contribute to the energy efficient solutions development. WUR is an on-demand approach in which the node is woken up by the wake-up signal (WUS). A WUS switches a node from sleep mode to wake up mode to start signal transmission and reception. The WUS is transmitted or received by a secondary radio transceiver, which operates on very low power. The energy benefit of using WUR is compared with conventional duty-cycling approach. As the protocol defines the nodes in WUR based network do not waste energy on idle listening and are only awakened when there is a request for communication, therefore, energy consumption is extremely low. The performance of WUR based MAC protocol has been evaluated for both physical layer (PHY) and MAC for transmission of WUS and data. The probabilities of miss detection, false alarm and detection error rates are calculated for PHY and the probabilities of collision and successful data transmission for channel access method Aloha is evaluated. The results are obtained to compute and compare the total energy consumption of WUR based network with duty cycling. The results prove that the WUR based networks have significant potential to improve energy efficiency, in comparison to conventional duty cycling approach especially, in the case of low data-reporting rate applications. The duty cycle approach is better than WUR approach when sufficiently low duty cycle is combined with highly frequent communication between the network nodes

Algorithms for Scheduling Problems

This edited book presents new results in the area of algorithm development for different types of scheduling problems. In eleven chapters, algorithms for single machine problems, flow-shop and job-shop scheduling problems (including their hybrid (flexible) variants), the resource-constrained project scheduling problem, scheduling problems in complex manufacturing systems and supply chains, and workflow scheduling problems are given. The chapters address such subjects as insertion heuristics for energy-efficient scheduling, the re-scheduling of train traffic in real time, control algorithms for short-term scheduling in manufacturing systems, bi-objective optimization of tortilla production, scheduling problems with uncertain (interval) processing times, workflow scheduling for digital signal processor (DSP) clusters, and many more

IST Austria Thesis

In the thesis we focus on the interplay of the biophysics and evolution of gene regulation. We start by addressing how the type of prokaryotic gene regulation – activation and repression – affects spurious binding to DNA, also known as transcriptional crosstalk. We propose that regulatory interference caused by excess regulatory proteins in the dense cellular medium – global crosstalk – could be a factor in determining which type of gene regulatory network is evolutionarily preferred. Next,we use a normative approach in eukaryotic gene regulation to describe minimal non-equilibrium enhancer models that optimize so-called regulatory phenotypes. We find a class of models that differ from standard thermodynamic equilibrium models by a single parameter that notably increases the regulatory performance. Next chapter addresses the question of genotype-phenotype-fitness maps of higher dimensional phenotypes. We show that our biophysically realistic approach allows us to understand how the mechanisms of promoter function constrain genotypephenotype maps, and how they affect the evolutionary trajectories of promoters. In the last chapter we ask whether the intrinsic instability of gene duplication and amplification provides a generic alternative to canonical gene regulation. Using mathematical modeling, we show that amplifications can tune gene expression in many environments, including those where transcription factor-based schemes are hard to evolve or maintain