Approcci innovativi per future simulazioni HPC verso l'exascale computing con applicazioni alla fisica dei materiali

In questo lavoro di tesi sono state evidenziate alcune problematiche relative alle macchine exascale (sistemi che sviluppano un exaflops di Potenza di calcolo) e all'evoluzione dei software che saranno eseguiti su questi sistemi, prendendo in esame principalmente la necessità del loro sviluppo, in quanto indispensabili per lo studio di problemi scientifici e tecnologici di più grandi dimensioni, con particolare attenzione alla Material Science, che è uno dei campi che ha avuto maggiori sviluppi grazie all'utilizzo di supercomputer, ed ad uno dei codici HPC più utilizzati in questo contesto: Quantum ESPRESSO. Dal punto di vista del software sono state presentate le prime misure di efficienza energetica su architettura ibrida grazie al prototipo di cluster EURORA sul software Quantum ESPRESSO. Queste misure sono le prime ad essere state pubblicate nel contesto software per la Material Science e serviranno come baseline per future ottimizzazioni basate sull'efficienza energetica. Nelle macchine exascale infatti uno dei requisiti per l'accesso sarà la capacità di essere energeticamente efficiente, così come oggi è un requisito la scalabilità del codice. Un altro aspetto molto importante, riguardante le macchine exascale, è la riduzione del numero di comunicazioni che riduce il costo energetico dell'algoritmo parallelo, poiché in questi nuovi sistemi costerà di più, da un punto di vista energetico, spostare i dati che calcolarli. Per tale motivo in questo lavoro sono state esposte una strategia, e la relativa implementazione, per aumentare la località dei dati in uno degli algoritmi più dispendiosi, dal punto di vista computazionale, in Quantum ESPRESSO: Fast Fourier Transform (FFT). Per portare i software attuali su una macchina exascale bisogna iniziare a testare la robustezza di tali software e i loro workflow su test case che stressino al massimo le macchine attualmente a disposizione. In questa tesi per testare il flusso di lavoro di Quantum ESPRESSO e WanT, un software per calcolo di trasporto, è stato caratterizzato un sistema scientificamente rilevante costituito da un cristallo di PDI - FCN2 che viene utilizzato per la costruzione di transistor organici OFET. Infine è stato simulato un dispositivo ideale costituito da due elettrodi in oro con al centro una singola molecola organica.

Alternatives to linear analysis of energy balance data from lactating dairy cows

The current energy requirements system used in the United Kingdom for lactating dairy cows utilizes key parameters such as metabolizable energy intake (MEI) at maintenance (MEm), the efficiency of utilization of MEI for 1) maintenance, 2) milk production (k(l)), 3) growth (k(g)), and the efficiency of utilization of body stores for milk production (k(t)). Traditionally, these have been determined using linear regression methods to analyze energy balance data from calorimetry experiments. Many studies have highlighted a number of concerns over current energy feeding systems particularly in relation to these key parameters, and the linear models used for analyzing. Therefore, a database containing 652 dairy cow observations was assembled from calorimetry studies in the United Kingdom. Five functions for analyzing energy balance data were considered: straight line, two diminishing returns functions, (the Mitscherlich and the rectangular hyperbola), and two sigmoidal functions (the logistic and the Gompertz). Meta-analysis of the data was conducted to estimate k(g) and k(t). Values of 0.83 to 0.86 and 0.66 to 0.69 were obtained for k(g) and k(t) using all the functions (with standard errors of 0.028 and 0.027), respectively, which were considerably different from previous reports of 0.60 to 0.75 for k(g) and 0.82 to 0.84 for k(t). Using the estimated values of k(g) and k(t), the data were corrected to allow for body tissue changes. Based on the definition of k(l) as the derivative of the ratio of milk energy derived from MEI to MEI directed towards milk production, MEm and k(l) were determined. Meta-analysis of the pooled data showed that the average k(l) ranged from 0.50 to 0.58 and MEm ranged between 0.34 and 0.64 MJ/kg of BW0.75 per day. Although the constrained Mitscherlich fitted the data as good as the straight line, more observations at high energy intakes (above 2.4 MJ/kg of BW0.75 per day) are required to determine conclusively whether milk energy is related to MEI linearly or not.

Performance of an operating high energy physics data grid: DOSAR-Grid

The DO experiment at Fermilab's Tevatron will record several petabytes of data over the next five years in pursuing the goals of understanding nature and searching for the origin of mass. Computing resources required to analyze these data far exceed capabilities of any one institution. Moreover, the widely scattered geographical distribution of DO collaborators poses further serious difficulties for optimal use of human and computing resources. These difficulties will exacerbate in future high energy physics experiments, like the LHC. The computing grid has long been recognized as a solution to these problems. This technology is being made a more immediate reality to end users in DO by developing a grid in the DO Southern Analysis Region (DOSAR), DOSAR-Grid, using a available resources within it and a home-grown local task manager, McFarm. We will present the architecture in which the DOSAR-Grid is implemented, the use of technology and the functionality of the grid, and the experience from operating the grid in simulation, reprocessing and data analyses for a currently running HEP experiment.

Phenothiazine based polymers for energy and data storage application

Die vorliegende Arbeit befasst sich mit der Synthese und Charakterisierung von Polymeren mit redox-funktionalen Phenothiazin-Seitenketten. Phenothiazin und seine Derivate sind kleine Redoxeinheiten, deren reversibles Redoxverhalten mit electrochromen Eigenschaften verbunden ist. Das besondere an Phenothiazine ist die Bildung von stabilen Radikalkationen im oxidierten Zustand. Daher können Phenothiazine als bistabile Moleküle agieren und zwischen zwei stabilen Redoxzuständen wechseln. Dieser Schaltprozess geht gleichzeitig mit einer Farbveränderung an her.rnrnIm Rahmen dieser Arbeit wird die Synthese neuartiger Phenothiazin-Polymere mittels radikalischer Polymerisation beschrieben. Phenothiazin-Derivate wurden kovalent an aliphatischen und aromatischen Polymerketten gebunden. Dies erfolgte über zwei unterschiedlichen synthetischen Routen. Die erste Route beinhaltet den Einsatz von Vinyl-Monomeren mit Phenothiazin Funktionalität zur direkten Polymerisation. Die zweite Route verwendet Amin modifizierte Phenothiazin-Derivate zur Funktionalisierung von Polymeren mit Aktivester-Seitenketten in einer polymeranalogen Reaktion. rnrnPolymere mit redox-funktionalen Phenothiazin-Seitenketten sind aufgrund ihrer Elektron-Donor-Eigenschaften geeignete Kandidaten für die Verwendung als Kathodenmaterialien. Zur Überprüfung ihrer Eignung wurden Phenothiazin-Polymere als Elektrodenmaterialien in Lithium-Batteriezellen eingesetzt. Die verwendeten Polymere wiesen gute Kapazitätswerte von circa 50-90 Ah/kg sowie schnelle Aufladezeiten in der Batteriezelle auf. Besonders die Aufladezeiten sind 5-10 mal höher als konventionelle Lithium-Batterien. Im Hinblick auf Anzahl der Lade- und Entladezyklen, erzielten die Polymere gute Werte in den Langzeit-Stabilitätstests. Insgesamt überstehen die Polymere 500 Ladezyklen mit geringen Veränderungen der Anfangswerte bezüglich Ladezeiten und -kapazitäten. Die Langzeit-Stabilität hängt unmittelbar mit der Radikalstabilität zusammen. Eine Stabilisierung der Radikalkationen gelang durch die Verlängerung der Seitenkette am Stickstoffatom des Phenothiazins und der Polymerhauptkette. Eine derartige Alkyl-Substitution erhöht die Radikalstabilität durch verstärkte Wechselwirkung mit dem aromatischen Ring und verbessert somit die Batterieleistung hinsichtlich der Stabilität gegenüber Lade- und Entladezyklen. rnrnDes Weiteren wurde die praktische Anwendung von bistabilen Phenothiazin-Polymeren als Speichermedium für hohe Datendichten untersucht. Dazu wurden dünne Filme des Polymers auf leitfähigen Substraten elektrochemisch oxidiert. Die elektrochemische Oxidation erfolgte mittels Rasterkraftmikroskopie in Kombination mit leitfähigen Mikroskopspitzen. Mittels dieser Technik gelang es, die Oberfläche des Polymers im nanoskaligen Bereich zu oxidieren und somit die lokale Leitfähigkeit zu verändern. Damit konnten unterschiedlich große Muster lithographisch beschrieben und aufgrund der Veränderung ihrer Leitfähigkeit detektiert werden. Der Schreibprozess führte nur zu einer Veränderung der lokalen Leitfähigkeit ohne die topographische Beschaffenheit des Polymerfilms zu beeinflussen. Außerdem erwiesen sich die Muster als besonders stabil sowohl mechanisch als auch über die Zeit.rnrnZum Schluss wurden neue Synthesestrategien entwickelt um mechanisch stabile als auch redox-funktionale Oberflächen zu produzieren. Mit Hilfe der oberflächen-initiierten Atomtransfer-Radikalpolymerisation wurden gepfropfte Polymerbürsten mit redox-funktionalen Phenothiazin-Seitenketten hergestellt und mittels Röntgenmethoden und Rasterkraftmikroskopie analysiert. Eine der Synthesestrategien geht von gepfropften Aktivesterbürsten aus, die anschließend in einem nachfolgenden Schritt mit redox-funktionalen Gruppen modifiziert werden können. Diese Vorgehensweise ist besonders vielversprechend und erlaubt es unterschiedliche funktionelle Gruppen an den Aktivesterbürsten zu verankern. Damit können durch Verwendung von vernetzenden Gruppen neben den Redoxeigenschaften, die mechanische Stabilität solcher Polymerfilme optimiert werden. rn rn

Global macrozoobenthos production and energy budget data base V150731, with link to database

I developed a new model for estimating annual production-to-biomass ratio P/B and production P of macrobenthic populations in marine and freshwater habitats. Self-learning artificial neural networks (ANN) were used to model the relationships between P/B and twenty easy-to-measure abiotic and biotic parameters in 1252 data sets of population production. Based on log-transformed data, the final predictive model estimates log(P/B) with reasonable accuracy and precision (r2 = 0.801; residual mean square RMS = 0.083). Body mass and water temperature contributed most to the explanatory power of the model. However, as with all least squares models using nonlinearly transformed data, back-transformation to natural scale introduces a bias in the model predictions, i.e., an underestimation of P/B (and P). When estimating production of assemblages of populations by adding up population estimates, accuracy decreases but precision increases with the number of populations in the assemblage.

A guide to commercial-scale ethanol production and financing : a product of the Solar Energy Information Data Bank /

"SERI/SP-751-877, UC-61."

Energy aware data gathering based on adaptive modulation scaling in wireless sensor networks

Energy consumption has been a key concern of data gathering in wireless sensor networks. Previous research works show that modulation scaling is an efficient technique to reduce energy consumption. However, such technique will also impact on both packet delivery latency and packet loss, therefore, may result in adverse effects on the qualities of applications. In this paper, we study the problem of modulation scaling and energy-optimization. A mathematical model is proposed to analyze the impact of modulation scaling on the overall energy consumption, end-to-end mean delivery latency and mean packet loss rate. A centralized optimal management mechanism is developed based on the model, which adaptively adjusts the modulation levels to minimize energy consumption while ensuring the QoS for data gathering. Experimental results show that the management mechanism saves significant energy in all the investigated scenarios. Some valuable results are also observed in the experiments. © 2004 IEEE.

Analyzing interrelated stochastic trend and seasonality on the example of energy trading data

The correct modelling of long- and short-term seasonality is a very interesting issue. The choice between the deterministic and stochastic modelling of trend and seasonality and their implications are as relevant as the case of deterministic and stochastic trends itself. The study considers the special case when the stochastic trend and seasonality do not evolve independently and the usual differencing filters do not apply. The results are applied to the day-ahead (spot) trading data of some main European energy exchanges (power and natural gas).

Analyzing interrelated stochastic trend and seasonality on the example of energy trading data

The correct modelling of long- and short-term seasonality is a very interesting issue. The choice between the deterministic and stochastic modelling of trend and seasonality and their implications are as relevant as the case of deterministic and stochastic trends itself. The study considers the special case when the stochastic trend and seasonality do not evolve independently and the usual differencing filters do not apply. The results are applied to the day-ahead (spot) trading data of some main European energy exchanges (power and natural gas).

Deployment of a Hybrid Multicast Switch in Energy-Aware Data Center Network: A Case of Fat-Tree Topology

Recently, energy efficiency or green IT has become a hot issue for many IT infrastructures as they attempt to utilize energy-efficient strategies in their enterprise IT systems in order to minimize operational costs. Networking devices are shared resources connecting important IT infrastructures, especially in a data center network they are always operated 24/7 which consume a huge amount of energy, and it has been obviously shown that this energy consumption is largely independent of the traffic through the devices. As a result, power consumption in networking devices is becoming more and more a critical problem, which is of interest for both research community and general public. Multicast benefits group communications in saving link bandwidth and improving application throughput, both of which are important for green data center. In this paper, we study the deployment strategy of multicast switches in hybrid mode in energy-aware data center network: a case of famous fat-tree topology. The objective is to find the best location to deploy multicast switch not only to achieve optimal bandwidth utilization but also to minimize power consumption. We show that it is possible to easily achieve nearly 50% of energy consumption after applying our proposed algorithm.

A data framework for measuring the energy consumption of the non-domestic building stock

The transition to a low-carbon economy urgently demands better information on the drivers of energy consumption. UK government policy has prioritized energy efficiency in the built stock as a means of carbon reduction, but the sector is historically information poor, particularly the non-domestic building stock. This paper presents the results of a pilot study that investigated whether and how property and energy consumption data might be combined for non-domestic energy analysis. These data were combined in a ‘Non-Domestic Energy Efficiency Database’ to describe the location and physical attributes of each property and its energy consumption. The aim was to support the generation of a range of energy-efficiency statistics for the industrial, commercial and institutional sectors of the non-domestic building stock, and to provide robust evidence for national energy-efficiency and carbon-reduction policy development and monitoring. The work has brought together non-domestic energy data, property data and mapping in a ‘data framework’ for the first time. The results show what is possible when these data are integrated and the associated difficulties. A data framework offers the potential to inform energy-efficiency policy formation and to support its monitoring at a level of detail not previously possible.

Properties of individual YBCO layers in a two-layered design for energy-efficient digital data cables

We are developing two-layered Yttrium Barium Copper Oxide (YBCO) thin film structures for energy efficient data links for superconducting electronics and present the results of their property measurements. High temperature superconductors (HTS) are advantageous for the implementation of energy-efficient cables interconnecting low temperature superconductor-based circuits and other cryogenic electronics circuits at higher temperature stages. The advantages of the HTS cables come from their low loss and low dispersion properties, allowing ballistic transfer of low power signals with very high bandwidth, low heat conduction and negligible inter-line crosstalk. The microstrip line cable geometry for typical materials is a two-layered film, in which the two superconducting layers are separated by an insulation layer with a minimized permittivity. We have made a proof of concept design of two YBCO films grown by pulsed laser deposition and then assembled into a sandwich with uniform insulating interlayer of tens of micrometers thick. We report on results obtained from such systems assembled in different ways. Structural and electromagnetic properties have been examined on individual films and on the corresponding sandwich composite. © 2013 IEEE.

Guidelines for Linked Data generation and publication: an example in building energy consumption

Linked Data is the key paradigm of the Semantic Web, a new generation of the World Wide Web that promises to bring meaning (semantics) to data. A large number of both public and private organizations have published their data following the Linked Data principles, or have done so with data from other organizations. To this extent, since the generation and publication of Linked Data are intensive engineering processes that require high attention in order to achieve high quality, and since experience has shown that existing general guidelines are not always sufficient to be applied to every domain, this paper presents a set of guidelines for generating and publishing Linked Data in the context of energy consumption in buildings (one aspect of Building Information Models). These guidelines offer a comprehensive description of the tasks to perform, including a list of steps, tools that help in achieving the task, various alternatives for performing the task, and best practices and recommendations. Furthermore, this paper presents a complete example on the generation and publication of Linked Data about energy consumption in buildings, following the presented guidelines, in which the energy consumption data of council sites (e.g., buildings and lights) belonging to the Leeds City Council jurisdiction have been generated and published as Linked Data.