Energy-aware Software

Luca Ardito has focused his PhD on studying how to identify and to reduce the energy consumption caused by software. The project concentrates on the application level, with an experimental approach to discover and modify characteristics that waste energy. We can define five research goals: RG1. Is it possible to measure the energy consumption of an application? Measuring the energy consumption of an electronic device (PC, mobile phone, etc.) is straightforward, but several applications coexist on it, possibly with very different energy needs. Usage profiles for applications are certainly important too. We will consider the most common platforms (Windows, Linux, Mac Osx). RG2. Could Energy Efficiency be considered as a software non- functional requirement? Research has increasingly focused on improving the Energy Efficiency of hardware, but the literature still lacks in quantifying accurately the energy impact of software. This research goal is strictly related to the following one. RG3. Is it possible to profile the energy consumption of a software application? An empirical experiment could assess quantitatively the energetic impact of software usage by building up common application usage scenarios and executing them independently to collect power consumption data. RG4. Is there a relationship between the way a program is written and its energy consumption? The same application, at the code level, can be written in different ways. Here the question is if the different ways have impact on energy consumption. The code should be considered at two levels: source code (programmer) and object code/byte code (compiler). RG5. Is it possible to use the energy consumption information to trigger self-adaptation? A software application could automatically modify its behaviour in order to reduce its energy consumption

Iso-energy-efficiency: An approach to power-constrained parallel computation

Future large scale high performance supercomputer systems require high energy efficiency to achieve exaflops computational power and beyond. Despite the need to understand energy efficiency in high-performance systems, there are few techniques to evaluate energy efficiency at scale. In this paper, we propose a system-level iso-energy-efficiency model to analyze, evaluate and predict energy-performance of data intensive parallel applications with various execution patterns running on large scale power-aware clusters. Our analytical model can help users explore the effects of machine and application dependent characteristics on system energy efficiency and isolate efficient ways to scale system parameters (e.g. processor count, CPU power/frequency, workload size and network bandwidth) to balance energy use and performance. We derive our iso-energy-efficiency model and apply it to the NAS Parallel Benchmarks on two power-aware clusters. Our results indicate that the model accurately predicts total system energy consumption within 5% error on average for parallel applications with various execution and communication patterns. We demonstrate effective use of the model for various application contexts and in scalability decision-making

Design and control approaches for energy harvesting wireless sensor networks

Wireless Networks are monitoring infrastructures composed of sensing (measuring), computing, and communication devices used to observe, supervise and monitor environmental phenomena. Energy Harvesting Wireless Sensor Networks (EH-WSN) have the additional feature to save energy from the environment in order to ensure long life autonomy of the entire network, without ideally the human intervention over long periods of time. The present work is aimed to address some of the most significant limitations of the actual EH-WSN, making a step forward the perpetual operation of EH-WSN. In this dissertation, design methodology and management policies are proposed to improve EH-WSN in terms of application performances, traffic congestion and energy efficiency. The study explicitly targets to energy-efficient affordable ways to develop more reliable and trustworthy EH-WSN, capable to ensure long life and desired performances. The presentation is organized into two macro sections, or Parts: the first one is dedicated to design the main EH-WSN hardware and software parameters that affect the energy efficiency of a sensor node, while in the second part three dynamic control strategies are proposed to outperform the EH-WSN in terms of energy efficiency, traffic congestion and application requirements

PowerPack: Energy Profiling and Analysis of High-Performance Systems and Applications

Energy efficiency is a major concern in modern high-performance computing system design. In the past few years, there has been mounting evidence that power usage limits system scale and computing density, and thus, ultimately system performance. However, despite the impact of power and energy on the computer systems community, few studies provide insight to where and how power is consumed on high-performance systems and applications. In previous work, we designed a framework called PowerPack that was the first tool to isolate the power consumption of devices including disks, memory, NICs, and processors in a high-performance cluster and correlate these measurements to application functions. In this work, we extend our framework to support systems with multicore, multiprocessor-based nodes, and then provide in-depth analyses of the energy consumption of parallel applications on clusters of these systems. These analyses include the impacts of chip multiprocessing on power and energy efficiency, and its interaction with application executions. In addition, we use PowerPack to study the power dynamics and energy efficiencies of dynamic voltage and frequency scaling (DVFS) techniques on clusters. Our experiments reveal conclusively how intelligent DVFS scheduling can enhance system energy efficiency while maintaining performance

A low cost shading analyzer and site evaluator design to determine solar power system installation area

Shading analyzer systems are necessary for selecting the most suitable installation site to sustain enough solar power. Afterwards, changes in solar data throughout the year must be evaluated along with the identification of obstructions surrounding the installation site in order to analyze shading effects on productivity of the solar power system. In this study, the shading analysis tools are introduced briefly, and a new and different device is developed and explained to analyze shading effect of the environmental obstruction on the site on which the solar power system will be established. Thus, exposure duration of the PV panels to the sunlight can be measured effectively. The device is explained with an application on the installation area selected as a pilot site, Denizli, in Turkey. © 2015 Selami Kesler et al

Quantitative Imaging of Protein-Protein Interactions by Multiphoton Fluorescence Lifetime Imaging Microscopy using a Streak camera

Fluorescence Lifetime Imaging Microscopy (FLIM) using multiphoton excitation techniques is now finding an important place in quantitative imaging of protein-protein interactions and intracellular physiology. We review here the recent developments in multiphoton FLIM methods and also present a description of a novel multiphoton FLIM system using a streak camera that was developed in our laboratory. We provide an example of a typical application of the system in which we measure the fluorescence resonance energy transfer between a donor/acceptor pair of fluorescent proteins within a cellular specimen.Comment: Overview of FLIM techniques, StreakFLIM instrument, FRET application