Date: Tuesday 15 March 2016
Time: 17:00 - 18:30
Location / Room: Konferenz 2

Chair:
William Fornaciari, Politecnico di Milano - DEIB, IT

Co-Chair:
Soontae Kim, KAIST, KR

The goal of this session is to provide a comprehensive perspective on the design and management of power and energy, tacking the problem from several standpoints. The first paper proposes a methodology to reduce the energy consumed by OLED displays exploiting image-specific pixel-by-pixel transformations, aimed at preserving the contrast of the image as much as possible while reducing the overall power. The second paper presents an efficient Energy Management Unit (EMU) to supply generic loads when the average harvested power is much smaller than required for sustained system operation. A dynamic energy burst scaling (DEBS) technique is proposed to dynamically configure the EMU. The third paper aims at optimizing acousting monitoring by exploiting a two-stage architecture with a low power pattern recognition for feature extraction, combined with an optimized wakeup stage.

Time	Label	Presentation Title Authors
17:00	4.4.1	LOW-OVERHEAD ADAPTIVE CONSTRAST ENHANCEMENT AND POWER REDUCTION FOR OLEDS Speaker: Massimo Poncino, Politecnico di Torino, IT Authors: Daniele Jahier Pagliari, Massimo Poncino and Enrico Macii, Politecnico di Torino, IT Abstract Organic Light Emitting Diode (OLED) display panels are becoming increasingly popular especially in mobile devices; one of the key characteristics of these panels is that their power consumption strongly depends on the displayed image. In this paper, we propose a new methodology to reduce the energy consumed by OLED displays that relies on image-specific pixel-by-pixel transformations, aimed at preserving the contrast of the image as much as possible while reducing the overall power. Unlike previous approaches, our method focuses specifically on the minimization of time and power overheads to implement the image transformation at runtime. To this end, we propose a transformation that can be executed online in real time, either in software, with low time overhead, or in a hardware accelerator with a small silicon footprint. Despite the great reduction in complexity, our results are comparable to those achieved with more complex approaches in terms of image quality. Moreover, our method allows to easily explore the full quality-versus-power tradeoff by acting on a few basic parameters; thus, it enables the runtime selection among multiple display quality settings, according to the status of the system. Download Paper (PDF; Only available from the DATE venue WiFi)
17:30	4.4.2	DYNAMIC ENERGY BURST SCALING FOR TRANSIENTLY POWERED SYSTEMS Speaker: Andres Gomez, ETH Zurich, US Authors: Andres Gomez, Lukas Sigrist, Michele Magno, Luca Benini and Lothar Thiele, ETH Zurich, CH Abstract Energy harvesting is generally seen to be the key to power cyber-physical systems in a low-cost, long term, efficient manner. However, harvesting has traditionally been coupled with large energy storage devices to mitigate the effects of the source's variability. The emerging class of transiently powered systems avoids this issue by performing computation only as a function of the harvested energy, minimizing the obtrusive and expensive storage element. In this work, we present an efficient Energy Management Unit (EMU) to supply generic loads when the average harvested power is much smaller than required for sustained system operation. By building up charge to a pre-defined energy level, the EMU can generate short energy bursts predictably, even under variable harvesting conditions. Furthermore, we propose a dynamic energy burst scaling (DEBS) technique to adjust these bursts to the load's requirements. Using a simple interface, the load can dynamically configure the EMU to supply small bursts of energy at its optimal power point, independent from the harvester's operating point. Extensive theoretical and experimental data demonstrate the high energy efficiency of our approach, reaching up to 73.6% even when harvesting only 110 uW to supply a load of 3.89 mW. Download Paper (PDF; Only available from the DATE venue WiFi)
18:00	4.4.3	LOW-POWER MULTICHANNEL SPECTRO-TEMPORAL FEATURE EXTRACTION CIRCUIT FOR AUDIO PATTERN WAKE-UP Speaker: Dinko Oletic, University of Zagreb, HR Authors: Dinko Oletic1, Vedran Bilas1, Michele Magno2, Norbert Felber2 and Luca Benini2 1University of Zagreb, HR; 2ETH Zurich, CH Abstract In many distributed sensing applications, continuous sensor monitoring requires processing with a significant energy footprint, which hinders autonomous operation and battery lifetime of sensor nodes. In our research we explore the power savings gained by splitting the hardware architecture for continuous monitoring into two stages: an always-on ultra-low-power mixed-signal wake-up circuit placed near the sensor, performing coarse recognition (e.g. wake-up circuit) and waking up the main digital processing unit only on event detection. This enables for activation of energy-hungry digital processing only at the rate of event occurrence without penalising responsiveness and monitoring continuity. We focus on the wake-up circuit performing recognition of spectro-temporal audio patterns, consisting of spectro-temporal feature extraction, and the classification sub-circuits. We propose a novel design of the feature extraction circuit. It consists of a spectral decomposition multi-channel analog band-pass filter bank, implemented in generalized impedance converter topology (GIC), and the bank of passive channel detectors for measuring the intervals of in-band signals. Experimental filter characterization demonstrated the benefits of proposed filtering topology for low-power applications in the audio frequency range even with operational amplifiers of very limited bandwidth. Detector's response was verified in multi-channel environment. Preliminary analysis showed power consumption ranging from 10.5 to 13.5 µW per channel using off-the-shelf components. Download Paper (PDF; Only available from the DATE venue WiFi)
18:30		End of session