A Survey of Techniques For Improving Energy Efficiency in Embedded Computing Systems

Recent technological advances have greatly improved the performance and features of embedded systems. With the number of just mobile devices now reaching nearly equal to the population of earth, embedded systems have truly become ubiquitous. These trends, however, have also made the task of managing their power consumption extremely challenging. In recent years, several techniques have been proposed to address this issue. In this paper, we survey the techniques for managing power consumption of embedded systems. We discuss the need of power management and provide a classification of the techniques on several important parameters to highlight their similarities and differences. This paper is intended to help the researchers and application-developers in gaining insights into the working of power management techniques and designing even more efficient high-performance embedded systems of tomorrow

A Dual Dielectric Approach for Performance Aware Reduction of Gate Leakage in Combinational Circuits

Design of systems in the low-end nanometer domain has introduced new dimensions in power consumption and dissipation in CMOS devices. With continued and aggressive scaling, using low thickness SiO2 for the transistor gates, gate leakage due to gate oxide direct tunneling current has emerged as the major component of leakage in the CMOS circuits. Therefore, providing a solution to the issue of gate oxide leakage has become one of the key concerns in achieving low power and high performance CMOS VLSI circuits. In this thesis, a new approach is proposed involving dual dielectric of dual thicknesses (DKDT) for the reducing both ON and OFF state gate leakage. It is claimed that the simultaneous utilization of SiON and SiO2 each with multiple thicknesses is a better approach for gate leakage reduction than the conventional usage of a single gate dielectric (SiO2), possibly with multiple thicknesses. An algorithm is developed for DKDT assignment that minimizes the overall leakage for a circuit without compromising with the performance. Extensive experiments were carried out on ISCAS'85 benchmarks using 45nm technology which showed that the proposed approach can reduce the leakage, as much as 98% (in an average 89.5%), without degrading the performance

LOW-VOLTAGE LOW-POWER ANALOG-TO-DIGITAL CONVERTERS

Ph.DDOCTOR OF PHILOSOPH

Multiple voltage scheme with frequency variation for power minimization of pipelined circuits at high-level synthesis

High-Level Synthesis (HLS) is defined as a translation process from a behavioral description into structural description. The high-level synthesis process consists of three interdependent phases: scheduling, allocation and binDing The order of the three phases varies depending on the design flow. There are three important quality measures used to support design decision, namely size, performance and power consumption. Recently, with the increase in portability, the power consumption has become a very dominant factor in the design of circuits. The aim of low-power high-level synthesis is to schedule operations to minimize switching activity and select low power modules while satisfying timing constraints. This thesis presents a heuristic that helps minimize power consumption by operating the functional units at multiple voltages and varied clock frequencies. The algorithm presented here deals with pipelined operations where multiple instance of the same operation are carried out. The algorithm was implemented using C++, on LINUX platform

Towards Optimal Application Mapping for Energy-Efficient Many-Core Platforms

Siirretty Doriast

A review of advances in pixel detectors for experiments with high rate and radiation

The Large Hadron Collider (LHC) experiments ATLAS and CMS have established hybrid pixel detectors as the instrument of choice for particle tracking and vertexing in high rate and radiation environments, as they operate close to the LHC interaction points. With the High Luminosity-LHC upgrade now in sight, for which the tracking detectors will be completely replaced, new generations of pixel detectors are being devised. They have to address enormous challenges in terms of data throughput and radiation levels, ionizing and non-ionizing, that harm the sensing and readout parts of pixel detectors alike. Advances in microelectronics and microprocessing technologies now enable large scale detector designs with unprecedented performance in measurement precision (space and time), radiation hard sensors and readout chips, hybridization techniques, lightweight supports, and fully monolithic approaches to meet these challenges. This paper reviews the world-wide effort on these developments.Comment: 84 pages with 46 figures. Review article.For submission to Rep. Prog. Phy

On thermal sensor calibration and software techniques for many-core thermal management

The high power density of a many-core processor results in increased temperature which negatively impacts system reliability and performance. Dynamic thermal management applies thermal-aware techniques at run time to avoid overheating using temperature information collected from on-chip thermal sensors. Temperature sensing and thermal control schemes are two critical technologies for successfully maintaining thermal safety. In this dissertation, on-line thermal sensor calibration schemes are developed to provide accurate temperature information. Software-based dynamic thermal management techniques are proposed using calibrated thermal sensors. Due to process variation and silicon aging, on-chip thermal sensors require periodic calibration before use in DTM. However, the calibration cost for thermal sensors can be prohibitively high as the number of on-chip sensors increases. Linear models which are suitable for on-line calculation are employed to estimate temperatures at multiple sensor locations using performance counters. The estimated temperature and the actual sensor thermal profile show a very high similarity with correlation coefficient ~0.9 for SPLASH2 and SPEC2000 benchmarks. A calibration approach is proposed to combine potentially inaccurate temperature values obtained from two sources: thermal sensor readings and temperature estimations. A data fusion strategy based on Bayesian inference, which combines information from these two sources, is demonstrated. The result shows the strategy can effectively recalibrate sensor readings in response to inaccuracies caused by process variation and environmental noise. The average absolute error of the corrected sensor temperature readings is A dynamic task allocation strategy is proposed to address localized overheating in many-core systems. Our approach employs reinforcement learning, a dynamic machine learning algorithm that performs task allocation based on current temperatures and a prediction regarding which assignment will minimize the peak temperature. Our results show that the proposed technique is fast (scheduling performed in \u3c1 \u3ems) and can efficiently reduce peak temperature by up to 8 degree C in a 49-core processor (6% on average) versus a leading competing task allocation approach for a series of SPLASH-2 benchmarks. Reinforcement learning has also been applied to 3D integrated circuits to allocate tasks with thermal awareness

Design methodologies for variation-aware integrated circuits

The scaling of VLSI technology has spurred a rapid growth in the semiconductor industry. With the CMOS device dimension scaling to and beyond 90nm technology, it is possible to achieve higher performance and to pack more complex functionalities on a single chip. However, the scaling trend has introduced drastic variation of process and design parameters, leading to severe variability of chip performance in nanometer regime. Also, the manufacturing community projects CMOS will scale for three to four more generations. Since the uncertainties due to variations are expected to increase in each generation, it will significantly impact the performance of design and consequently the yield. Another challenging issue in the nanometer IC design is the high power consumption due to the greater packing density, higher frequency of operation and excessive leakage power. Moreover, the circuits are usually over-designed to compensate for uncertainties due to variations. The over-designed circuits not only make timing closure difficult but also cause excessive power consumption. For portable electronics, excessive power consumption may reduce battery life; for non-portable systems it may impose great difficulties in cooling and packaging. The objective of my research has been to develop design methodologies to address variations and power dissipation for reliable circuit operation. The proposed work has been divided into three parts: the first part addresses the issues related with power/ground noise induced by clock distribution network and proposes techniques to reduce power/ground noise considering the effects of process variations. The second part proposes an elastic pipeline scheme for random circuits with feedback loops. The proposed scheme provides a low-power solution that has the same variation tolerance as the conventional approaches. The third section deals with discrete buffer and wire sizing for link-based non-tree clock network, which is an energy efficient structure for skew tolerance to variations. For the power/ground noise problem, our approach could reduce the peak current and the delay variations by 50% and 51% respectively. Compared to conventional approach, the elastic timing scheme reduces power dissipation by 20% − 27%. The sizing method achieves clock skew reduction of 45% with a small increase in power dissipation

EFFICIENT HARDWARE PRIMITIVES FOR SECURING LIGHTWEIGHT SYSTEMS

In the era of IoT and ubiquitous computing, the collection and communication of sensitive data is increasingly being handled by lightweight Integrated Circuits. Efficient hardware implementations of crytographic primitives for resource constrained applications have become critical, especially block ciphers which perform fundamental operations such as encryption, decryption, and even hashing. We study the efficiency of block ciphers under different implementation styles. For low latency applications that use unrolled block cipher implementations, we design a glitch filter to reduce energy consumption. For lightweight applications, we design a novel architecture for the widely used AES cipher. The design eliminates inefficiencies in data movement and clock activity, thereby significantly improving energy efficiency over state-of-the-art architectures. Apart from efficiency, vulnerability to implementation attacks are a concern, which we mitigate by our randomization capable lightweight AES architecture. We fabricate our designs in a commercial 16nm FinFET technology and present measured testchip data on energy consumption and side channel resistance. Finally, we address the problem of supply chain security by using image processing techniques to extract fingerprints from surface texture of plastic IC packages for IC authentication and counterfeit prevention. Collectively these works present efficient and cost effective solutions to secure lightweight systems