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.

An energy-efficient data delivery scheme for delay-sensitive traffic in wireless sensor networks

We propose a novel data-delivery method for delay-sensitive traffic that significantly reduces the energy consumption in wireless sensor networks without reducing the number of packets that meet end-to-end real-time deadlines. The proposed method, referred to as SensiQoS, leverages the spatial and temporal correlation between the data generated by events in a sensor network and realizes energy savings through application-specific in-network aggregation of the data. SensiQoS maximizes energy savings by adaptively waiting for packets from upstream nodes to perform in-network processing without missing the real-time deadline for the data packets. SensiQoS is a distributed packet scheduling scheme, where nodes make localized decisions on when to schedule a packet for transmission to meet its end-to-end real-time deadline and to which neighbor they should forward the packet to save energy. We also present a localized algorithm for nodes to adapt to network traffic to maximize energy savings in the network. Simulation results show that SensiQoS improves the energy savings in sensor networks where events are sensed by multiple nodes, and spatial and/or temporal correlation exists among the data packets. Energy savings due to SensiQoS increase with increase in the density of the sensor nodes and the size of the sensed events. © 2010 Harshavardhan Sabbineni and Krishnendu Chakrabarty.

Low power field programmable gate array implementation of fast digital signal processing algorithms: characterisation and manipulation of data locality

Dynamic power consumption is very dependent on interconnect, so clever mapping of digital signal processing algorithms to parallelised realisations with data locality is vital. This is a particular problem for fast algorithm implementations where typically, designers will have sacrificed circuit structure for efficiency in software implementation. This study outlines an approach for reducing the dynamic power consumption of a class of fast algorithms by minimising the index space separation; this allows the generation of field programmable gate array (FPGA) implementations with reduced power consumption. It is shown how a 50% reduction in relative index space separation results in a measured power gain of 36 and 37% over a Cooley-Tukey Fast Fourier Transform (FFT)-based solution for both actual power measurements for a Xilinx Virtex-II FPGA implementation and circuit measurements for a Xilinx Virtex-5 implementation. The authors show the generality of the approach by applying it to a number of other fast algorithms namely the discrete cosine, the discrete Hartley and the Walsh-Hadamard transforms.

Energy versus data integrity trade-offs in embedded high-density logic compatible dynamic memories

Current variation aware design methodologies, tuned for worst-case scenarios, are becoming increasingly pessimistic from the perspective of power and performance. A good example of such pessimism is setting the refresh rate of DRAMs according to the worst-case access statistics, thereby resulting in very frequent refresh cycles, which are responsible for the majority of the standby power consumption of these memories. However, such a high refresh rate may not be required, either due to extremely low probability of the actual occurrence of such a worst-case, or due to the inherent error resilient nature of many applications that can tolerate a certain number of potential failures. In this paper, we exploit and quantify the possibilities that exist in dynamic memory design by shifting to the so-called approximate computing paradigm in order to save power and enhance yield at no cost. The statistical characteristics of the retention time in dynamic memories were revealed by studying a fabricated 2kb CMOS compatible embedded DRAM (eDRAM) memory array based on gain-cells. Measurements show that up to 73% of the retention power can be saved by altering the refresh time and setting it such that a small number of failures is allowed. We show that these savings can be further increased by utilizing known circuit techniques, such as body biasing, which can help, not only in extending, but also in preferably shaping the retention time distribution. Our approach is one of the first attempts to access the data integrity and energy tradeoffs achieved in eDRAMs for utilizing them in error resilient applications and can prove helpful in the anticipated shift to approximate computing.

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.

A study and a directory of energy consumption data sets of buildings

Energy consumption data are required to perform analysis, modelling, evaluation, and optimisation of energy usage in buildings. While a variety of energy consumption data sets have been examined and reported in the literature, there is a lack of a comprehensive categorisation and analysis of the available data sets. In this study, an overview of energy consumption data of buildings is provided. Three common strategies for generating energy consumption data, i.e., measurement, survey, and simulation, are described. A number of important characteristics pertaining to each strategy and the resulting data sets are discussed. In addition, a directory of energy consumption data sets of buildings is developed. The data sets are collected from either published papers or energy related organisations. The main contributions of this study include establishing a resource pertaining to energy consumption data sets and providing information related to the characteristics and availability of the respective data sets; therefore facilitating and promoting research activities in energy consumption data analysis.

Fast and energy efficient data storage for information discovery in multi-dimensional WSNs

Multidimensional WSNs are deployed in complex environments to sense and collect data relating to multiple attributes (multi-dimensional data). An efficient information dis-covery for multi-dimensional WSNs deployed in mission–critical environments has become an essential research consideration. Timely and energy efficient information discovery is very impor-tant to maintain the QoS of such mission critical applications. An inefficient information discovery mechanism will result in high transmission of data packets over the network creating bottlenecks leading to unbalanced energy consumption over the network. High latency and inefficient energy consumption will have a direct effect on the QoS of mission-critical applications of particular importance in this regard is the minimization of hotspots.

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