Prediction-Based Power-Performance Adaptation of Multithreaded Scientific Codes

Computing has recently reached an inflection point with the introduction of multicore processors. On-chip thread-level parallelism is doubling approximately every other year. Concurrency lends itself naturally to allowing a program to trade performance for power savings by regulating the number of active cores; however, in several domains, users are unwilling to sacrifice performance to save power. We present a prediction model for identifying energy-efficient operating points of concurrency in well-tuned multithreaded scientific applications and a runtime system that uses live program analysis to optimize applications dynamically. We describe a dynamic phase-aware performance prediction model that combines multivariate regression techniques with runtime analysis of data collected from hardware event counters to locate optimal operating points of concurrency. Using our model, we develop a prediction-driven phase-aware runtime optimization scheme that throttles concurrency so that power consumption can be reduced and performance can be set at the knee of the scalability curve of each program phase. The use of prediction reduces the overhead of searching the optimization space while achieving near-optimal performance and power savings. A thorough evaluation of our approach shows a reduction in power consumption of 10.8 percent, simultaneous with an improvement in performance of 17.9 percent, resulting in energy savings of 26.7 percent.

Update on Research Activities in the MaRINET Project

The MaRINET FP7 project aims to build a synergy in the European marine renewable energy development infrastructure network, involving a total of 28 partners across the union. Its scope extends from small to large scale testing, in both tank and field. The main activities of the project are to standardize test procedures, to provide centralized free access for European technology developers, and to innovate for improving test infrastructures and techniques.
Two years to the end of the project, this paper presents an update of the work being carried in this last part. It focuses on research objectives identified to be current challenges for industrial development. They are distributed in 6 topics. On the one hand are issues directly related to one of the 3 types of energy scoped in the project: wave, tidal, and offshore wind. On the other hand, collaborative effort is drawn on aspects that are common to those technologies: electrical components, environmental monitoring, and dedicated moorings.
Theory and validation of new test techniques are presented, for example in the case of non-intrusive wave measurements. This is done in coordination with extensive experimental analysis of the phenomena implying tests, such as nonlinearities in moorings.

Significance Driven Computation on Next-Generation Unreliable Platforms

In this paper, we propose a design paradigm for energy efficient and variation-aware operation of next-generation multicore heterogeneous platforms. The main idea behind the proposed approach lies on the observation that not all operations are equally important in shaping the output quality of various applications and of the overall system. Based on such an observation, we suggest that all levels of the software design stack, including the programming model, compiler, operating system (OS) and run-time system should identify the critical tasks and ensure correct operation of such tasks by assigning them to dynamically adjusted reliable cores/units. Specifically, based on error rates and operating conditions identified by a sense-and-adapt (SeA) unit, the OS selects and sets the right mode of operation of the overall system. The run-time system identifies the critical/less-critical tasks based on special directives and schedules them to the appropriate units that are dynamically adjusted for highly-accurate/approximate operation by tuning their voltage/frequency. Units that execute less significant operations can operate at voltages less than what is required for correct operation and consume less power, if required, since such tasks do not need to be always exact as opposed to the critical ones. Such scheme can lead to energy efficient and reliable operation, while reducing the design cost and overheads of conventional circuit/micro-architecture level techniques.

Iso-Quality of Service: Fairly Ranking Servers for Real-Time Data Analytics

We present a mathematically rigorous Quality-of-Service (QoS) metric which relates the achievable quality of service metric (QoS) for a real-time analytics service to the server energy cost of offering the service. Using a new iso-QoS evaluation methodology, we scale server resources to meet QoS targets and directly rank the servers in terms of their energy-efficiency and by extension cost of ownership. Our metric and method are platform-independent and enable fair comparison of datacenter compute servers with significant architectural diversity, including micro-servers. We deploy our metric and methodology to compare three servers running financial option pricing workloads on real-life market data. We find that server ranking is sensitive to data inputs and desired QoS level and that although scale-out micro-servers can be up to two times more energy-efficient than conventional heavyweight servers for the same target QoS, they are still six times less energy efficient than high-performance computational accelerators.

Methods and Metrics for Fair Server Assessment under Real-Time Financial Workloads

We present a rigorous methodology and new metrics for fair comparison of server and microserver platforms. Deploying our methodology and metrics, we compare a microserver with ARM cores against two servers with ×86 cores running the same real-time financial analytics workload. We define workload-specific but platform-independent performance metrics for platform comparison, targeting both datacenter operators and end users. Our methodology establishes that a server based on the Xeon Phi co-processor delivers the highest performance and energy efficiency. However, by scaling out energy-efficient microservers, we achieve competitive or better energy efficiency than a power-equivalent server with two Sandy Bridge sockets, despite the microserver's slower cores. Using a new iso-QoS metric, we find that the ARM microserver scales enough to meet market throughput demand, that is, a 100% QoS in terms of timely option pricing, with as little as 55% of the energy consumed by the Sandy Bridge server.

Mitigating the Impact of Faults in Unreliable Memories for Error-Resilient Applications

Inherently error-resilient applications in areas such as signal processing, machine learning and data analytics provide opportunities for relaxing reliability requirements, and thereby reducing the overhead incurred by conventional error correction schemes. In this paper, we exploit the tolerable imprecision of such applications by designing an energy-efficient fault-mitigation scheme for unreliable data memories to meet target yield. The proposed approach uses a bit-shuffling mechanism to isolate faults into bit locations with lower significance. This skews the bit-error distribution towards the low order bits, substantially limiting the output error magnitude. By controlling the granularity of the shuffling, the proposed technique enables trading-off quality for power, area, and timing overhead. Compared to error-correction codes, this can reduce the overhead by as much as 83% in read power, 77% in read access time, and 89% in area, when applied to various data mining applications in 28nm process technology.

The VINEYARD Approach: Versatile, Integrated, Accelerator-Based, Heterogeneous Data Centres.

Emerging web applications like cloud computing, Big Data and social networks have created the need for powerful centres hosting hundreds of thousands of servers. Currently, the data centres are based on general purpose processors that provide high flexibility buts lack the energy efficiency of customized accelerators. VINEYARD aims to develop an integrated platform for energy-efficient data centres based on new servers with novel, coarse-grain and fine-grain, programmable hardware accelerators. It will, also, build a high-level programming framework for allowing end-users to seamlessly utilize these accelerators in heterogeneous computing systems by employing typical data-centre programming frameworks (e.g. MapReduce, Storm, Spark, etc.). This programming framework will, further, allow the hardware accelerators to be swapped in and out of the heterogeneous infrastructure so as to offer high flexibility and energy efficiency. VINEYARD will foster the expansion of the soft-IP core industry, currently limited in the embedded systems, to the data-centre market. VINEYARD plans to demonstrate the advantages of its approach in three real use-cases (a) a bio-informatics application for high-accuracy brain modeling, (b) two critical financial applications, and (c) a big-data analysis application.

Case study investigation of indoor air quality in mechanically ventilated and naturally ventilated UK social housing

There is a significant lack of indoor air quality research in low energy homes. This study compared the indoor air quality of eight
newly built case study homes constructed to similar levels of air-tightness and insulation; with two different ventilation strategies (four homes with Mechanical Ventilation with Heat Recovery (MVHR) systems/Code level 4 and four homes naturally ventilated/Code level 3). Indoor air quality measurements were conducted over a 24 h period in the living room and main bedroom of each home during the summer and winter seasons. Simultaneous outside measurements and an occupant diary were also employed during the measurement period. Occupant interviews were conducted to gain information on perceived indoor air quality, occupant behaviour and building related illnesses. Knowledge of the MVHR system including ventilation related behaviour was also studied. Results suggest indoor air quality problems in both the mechanically ventilated and naturally ventilated homes, with significant issues identified regarding occupant use in the social homes

Selective Multi-Carrier Index Keying OFDM: Error Propagation Rate with Moment Generating Function

We propose a new selective multi-carrier index keying in orthogonal frequency division multiplexing (OFDM) systems that opportunistically modulate both a small subset of sub-carriers and their indices. Particularly, we investigate the performance enhancement in two cases of error propagation sensitive and compromised deviceto-device (D2D) communications. For the performance evaluation, we focus on analyzing the error propagation probability (EPP) introducing the exact and upper bound expressions on the detection error probability, in the presence of both imperfect and perfect detection of active multi-carrier indices. The average EPP results in closedform are generalized for various fading distribution using the moment generating function, and our numerical results clearly show that the proposed approach is desirable for reliable and energy-efficient D2D applications.

A Scalable Runtime for the ECOSCALE Heterogeneous Exascale Hardware Platform

Exascale computation is the next target of high performance computing. In the push to create exascale computing platforms, simply increasing the number of hardware devices is not an acceptable option given the limitations of power consumption, heat dissipation, and programming models which are designed for current hardware platforms. Instead, new hardware technologies, coupled with improved programming abstractions and more autonomous runtime systems, are required to achieve this goal. This position paper presents the design of a new runtime for a new heterogeneous hardware platform being developed to explore energy efficient, high performance computing. By combining a number of different technologies, this framework will both simplify the programming of current and future HPC applications, as well as automating the scheduling of data and computation across this new hardware platform. In particular, this work explores the use of FPGAs to achieve both the power and performance goals of exascale, as well as utilising the runtime to automatically effect dynamic configuration and reconfiguration of these platforms. 

Characterization of High-Performance Organic Dyes for Dye-Sensitized Solar Cell: A DFT/TDDFT Study

Dye-sensitized solar cell (DSSC) is currently a promising technology that makes solar energy efficient and cost-effective to harness. In DSSC, metal free dyes, such indoline-containing D149 and D205, are proved to be potential alternatives for traditional metal organic dyes. In this work, a DFT/TDDFT characterization for D149 and D205 were carried out using different functionals, including B3LYP, MPW1K, CAM-B3LYP and PBE0. Three different conformers for D149 and four different conformers for D205 were identified and calculated in vacuum. The performance of different functionals on calculating the maximum absorbance of the dyes in vacuum and five common solvents (acetonitrile, chloroform, ethanol, methanol, and THF) were examined and compared to determine the suitable computational setting for predicting properties of these two dyes. Furthermore, deprotonated D149 and D205 in solvents were also considered, and the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) were calculated, which elucidates the substitution effect on the rhodanine ring of D149 and D205 dyes on their efficiency. Finally, D149 and D205 molecules were confirmed to be firmly anchored on ZnO surface by periodic DFT calculations. These results would shed light on the design of new highly efficiency metal-free dyes.

Flash-Sintering and Characterization of La0.8Sr0.2Ga0.8Mg0.2O3-δ Electrolytes for Solid Oxide Fuel Cells

La_0.8Sr_0.2Ga_0.8Mg_0.2O_3-δ (LSGM), a promising electrolyte material for intermediate temperature solid oxide fuel cells, can be sintered to a fully dense state by a flash-sintering technique. In this work, LSGM is sintered by the current-limiting flash-sintering process at 690°C under an electric field of 100 V cm^-1, in comparison with up to 1400°C or even higher temperature in conventional furnace sintering. The resultant LSGM samples are investigated by scanning electron microscopy, X-ray diffraction, and electrochemical impedance spectroscopy. The SEM images exhibit well-densified microstructures while XRD results show that the perovskite structure after flash-sintering does not changed. EIS results show that the conductivity of LSGM sintered by the current-limiting flash-sintering process increases with sintering current density value. The conductivity of samples sintered at 120 mA mm^-2 reaches 0.049 σ cm^-1 at 800°C, which is approximate to the value of conventional sintered LSGM samples at 1400°C. Additionally, the flash-sintering process is interpreted by Joule heating theory. Therefore, the current-limiting flash-sintering technique is proved to be an energy-efficient and eligible approach for the densification of LSGM and other materials requiring high sintering temperature.

Novel ketone diet enhances physical and cognitive performance

Ketone bodies are the most energy-efficient fuel and yield more ATP per mole of substrate than pyruvate and increase the free energy released from ATP hydrolysis. Elevation of circulating ketones via high-fat, low-carbohydrate diets has been used for the treatment of drug-refractory epilepsy and for neurodegenerative diseases, such as Parkinson's disease. Ketones may also be beneficial for muscle and brain in times of stress, such as endurance exercise. The challenge has been to raise circulating ketone levels by using a palatable diet without altering lipid levels. We found that blood ketone levels can be increased and cholesterol and triglycerides decreased by feeding rats a novel ketone ester diet: chow that is supplemented with (R)-3-hydroxybutyl (R)-3-hydroxybutyrate as 30% of calories. For 5 d, rats on the ketone diet ran 32% further on a treadmill than did control rats that ate an isocaloric diet that was supplemented with either corn starch or palm oil (P < 0.05). Ketone-fed rats completed an 8-arm radial maze test 38% faster than did those on the other diets, making more correct decisions before making a mistake (P < 0.05). Isolated, perfused hearts from rats that were fed the ketone diet had greater free energy available from ATP hydrolysis during increased work than did hearts from rats on the other diets as shown by using [(31)P]-NMR spectroscopy. The novel ketone diet, therefore, improved physical performance and cognitive function in rats, and its energy-sparing properties suggest that it may help to treat a range of human conditions with metabolic abnormalities.

Energy-Aware Rate and Description Allocation Optimized Video Streaming for Mobile D2D Communications

The proliferation problem of video streaming applications and mobile devices has prompted wireless network operators to put more efforts into improving quality of experience (QoE) while saving resources that are needed for high transmission rate and large size of video streaming. To deal with this problem, we propose an energy-aware rate and description allocation optimization method for video streaming in cellular network assisted device-to-device (D2D) communications. In particular, we allocate the optimal bit rate to each layer of video segments and packetize the segments into multiple descriptions with embedded forward error correction (FEC) for realtime streaming without retransmission. Simultaneously, the optimal number of descriptions is allocated to each D2D helper for transmission. The two allocation processes are done according to the access rate of segments, channel state information (CSI) of D2D requester, and remaining energy of helpers, to gain the highest optimization performance. Simulation results demonstrate that our proposed method (named OPT) significantly enhances the performance of video streaming in terms of high QoE and energy saving.

Cooperative Proxying: An Approach to Reduce Network Energy Waste

A network connected host is expected to generate/respond to applications and protocols specific messages. Billions of Euro of electricity is wasted to keep idle hosts powered up 24/7 just to maintain network presence. This short paper describes the design of our cooperative Network Connectivity Proxy (NCP) that can impersonate sleeping hosts and responds to packets on their behalf as they were connected and fully operational. Thus, NCP is in fact an efficient approach to reduce network energy waste.