Parallel database operations in heterogeneous environments

Im Gegensatz zu dem traditionellen Begriff eines Supercomputers, der aus vielen mittels superschneller, lokaler Netzwerkverbindungen miteinander verbundenen Superrechnern besteht, basieren heterogene Computerumgebungen auf "kompletten" Computersystemen, die mit Hilfe eines herkömmlichen Netzwerkanschlusses an private oder öffentliche Netzwerke angeschlossen sind. Der Bereich des Computernetzwerkens hat sich über die letzten drei Jahrzehnte entwickelt und ist, wie viele andere Technologien, in bezug auf Performance, Funktionalität und Verlässlichkeit extrem gewachsen. Zu Beginn des 21.Jahrhunderts zählt das betriebssichere Hochgeschwindigkeitsnetz genauso zur Alltäglichkeit wie Elektrizität, und auch Rechnerressourcen sind, was Verfügbarkeit und universellen Gebrauch anbelangt, ebenso Standard wie elektrischer Strom. Wissenschafter haben für die Verwendung von heterogenen Grids bei verschiedenen rechenintensiven Applikationen eine Architektur von computational Grids konzipiert und darin Modelle aufgesetzt, die zum einen Rechenleistungen defnieren und zum anderen die komplexen Eigenschaften der Grid-Organisation vor den Benutzern verborgen halten. Somit wird die Verwendung für den Benutzer genauso einfach wie es möglich ist elektrischen Strom zu beziehen. Grundsätzlich existiert keine generell akzeptierte Definition für Grids. Einige Wissenschafter bezeichnen sie als hochleistungsfähige verteilte Umgebung. Manche berücksichtigen bei der Definierung auch die geographische Verteilung und ihre Multi-Domain-Eigenschaft. Andere Wissenschafter wiederum definieren Grids über die Anzahl der Ressourcen, die sie verbinden. Parallele Datenbanksysteme haben in den letzten zwei Jahrzehnten große Bedeutung erlangt, da das rechenintensive wissenschaftliche Arbeiten, wie z.B. auf dem Gebiet der Bioinformatik, Strömungslehre und Hochenergie physik die Verarbeitung riesiger verteilter Datensätze erfordert. Diese Tendenz resultierte daraus, dass man von der fehlgeschlagenen Entwicklung hochspezialisierter Datenbankmaschinen zur Verwendung herkömmlicher paralleler Hardware-Architekturen übergegangen ist. Grundsätzlich wird die gleichzeitige Abarbeitung entweder durch verteilte Datenbankoperationen oder durch Datenparallelität gelöst. Im ersten Fall wird ein unterteilter Abfragenabarbeitungsplan durch verschiedene Datenbankoperatoren parallel durchgeführt. Im Fall der Datenparallelität erfolgt eine Unterteilung der Daten, wobei mehrere Prozessoren die gleichen Operationen parallel an Teilen der Daten durchführen. Es liegen genaue Analysen von parallelen Datenbank-Arbeitsvorgängen für sequenzielle Prozessoren vor. Eine Reihe von Publikationen haben dieses Thema abgehandelt und dabei Vorschläge und Analysen für parallele Datenbankmaschinen erstellt. Bis dato existiert allerdings noch keine spezifische Analyse paralleler Algorithmen mit dem Fokus der speziellen Eigenschaften einer "Grid"-Infrastruktur. Der spezifische Unterschied liegt in der Heterogenität von Grid-Ressourcen. In "shared nothing"-Architekturen, wie man sie bei klassischen Supercomputern und Cluster- Systemen vorfindet, sind alle Ressourcen wie z.B. Verarbeitungsknoten, Festplatten und Netzwerkverbindungen angesichts ihrer Leistung, Zugriffszeit und Bandbreite üblicherweise gleich (homogen). Im Gegensatz dazu zeigen Grid-Architekturen heterogene Ressourcen mit verschiedenen Leistungseigenschaften. Der herausfordernde Aspekt dieser Arbeit bestand darin aufzuzeigen, wie man das Problem heterogener Ressourcen löst, d.h. diese Ressourcen einerseits zur Leistungsmaximierung und andererseits zur Definition von Algorithmen einsetzt, um die Arbeitsablauf-Orchestrierung von Datenbankprozessoren zu optimieren. Um dieser Herausforderung gerecht werden zu können, wurde ein mathematisches Modell zur Untersuchung des Leistungsverhaltens paralleler Datenbankoperationen in heterogenen Umgebungen, wie z.B. in Grids, basierend auf generalisierten Multiprozessor- Architekturen entwickelt. Es wurden dabei sowohl die Parameter und deren Einfluss auf die Leistung als auch das Verhalten der Algorithmen in heterogenen Umgebungen beobachtet. Dabei konnte man feststellen, dass kleine Anpassungen an den Algorithmen zur signifikanten Leistungsverbesserung heterogener Umgebungen führen. Weiters wurde eine graphische Darstellung der Knotenkonfiguration entwickelt und ein optimierter Algorithmus, mit dem ein optimaler Knoten zur Ausführung von Datenbankoperationen gefunden werden kann. Diese Ergebnisse zum neuen Algorithmus wurden durch die Implementierung in einer serviceorientierten Architektur (SODA) bestätigt. Durch diese Implementierung konnte die Gültigkeit des Modells und des neu entwickelten optimierten Algorithmus nachgewiesen werden. In dieser Arbeit werden auch die Möglichkeiten für eine brauchbare Erweiterung des vorgestellten Modells gezeigt, wie z.B. für den Einsatz von Leistungskennziffern für Algorithmen zur Findung optimaler Knoten, die Verlässlichkeit der Knoten oder Vorgehensweisen/Lösungsaufgaben zur dynamischen Optimierung von Arbeitsabläufen.In contrast to the traditional notion of a supercomputer, which has many processors connected by a local high-speed computer bus, heterogeneous computing environments rely on "complete" computer nodes (CPU, storage, network interface, etc.) connected to a private or public network by a conventional network interface. Computer networking has evolved over the past three decades, and, like many technologies, has grown exponentially in terms of performance, functionality and reliability. At the beginning of the twenty-first century, high-speed, highly reliable Internet connectivity has become as commonplace as electricity, and computing resources have become as standard in terms of availability and universal use as electrical power. To use heterogeneous Grids for various applications requiring high-processing power, researchers propose the notion of computational Grids where rules are defined relating to both services and hiding the complexity of the Grid organization from the users. Thus, users would find it as easy to use as electrical power. Generally, there is no widely accepted definition of Grids. Some researchers define it as a high-performance distributed environment. Some take into consideration its geographically distributed, multi-domain feature. Others define Grids based on the number of resources they unify. Parallel database systems gained an important role in database research over the past two decades due to the necessity of handling large distributed datasets for scientific computing such as bioinformatics, fluid dynamics and high energy physics (HEP). This was connected with the shift from the (actually failed) development of highly specialized database machines to the usage of conventional parallel hardware architectures. Generally, concurrent execution is employed either by database operator or data parallelism. The first is achieved through parallel execution of a partitioned query execution plan by different operators, while the latter is achieved through parallel execution of the same operation on the partitioned data among multiple processors. Parallel database operation algorithms have been well analyzed for sequential processors. A number of publications have covered this topic which proposed and analyzed these algorithms for parallel database machines. Until now, to the best knowledge of the author, no specific analysis has been done so far on parallel algorithms with a focus on the specific characteristics of a Grid infrastructure. The specific difference lies in the heterogeneous nature of Grid resources. In a "shared nothing architecture", which can be found in classical supercomputers and cluster systems, all resources such as processing nodes, disks and network interconnection have typically homogeneous characteristics as regards to performance, access time and bandwidth. In contrast, in a Grid architecture heterogeneous resources are found that show different performance characteristics. The challenge of this research is to discover the way how to cope with or to exploit this situation to maximize performance and to define algorithms that lead to a solution for an optimized workflow orchestration. To address this challenge, we developed a mathematical model to investigate the performance behavior of parallel database operations in heterogeneous environments, such as a Grid, based on generalized multiprocessor architecture. We also studied the parameters and their influence on the performance as well as the behavior of the algorithms in heterogeneous environments. We discovered that only a small adjustment on the algorithm is necessary to significantly improve the performance for heterogeneous environments. A graphical representation of the node configuration and an optimized algorithm for finding the optimal node configuration for the execution of the parallel binary merge sort have been developed. Finally, we have proved our findings of the new algorithm by implementing it on a service-orientated infrastructure (SODA). The model and our new developed modified algorithms have been verified with the implementation. We also give an outlook of useful extensions to our model e.g. using performance indices, reliability of the nodes and approaches for dynamic optimization of workflow

Lyric Petrologies: Languages of Stone in Rilke, Trakl, Mandelstam, Celan, and Sachs.

Lyric Petrologies: Languages of Stone in Rilke, Trakl, Mandelstam, Celan, and Sachs examines the poetics of stone in twentieth-century German and Russian lyric. I illuminate a diverse line of development whereby stone—traditionally a signal of silence, immutability, insignificance, even a crushing heaviness—emerges as the conceptual and figurative ground of reconfigured lyric languages and subjectivities. My close, comparative readings demonstrate that for authors like Celan, Mandelstam, and Sachs, who could hardly have lived through darker times, stone offers alternative but affirmative models for lyric subjectivity. My project defines a set of rhetorical devices that characterize the varying lyrics of stone. Lyrics by Rilke, Trakl, and Mandelstam from the first decades of the century demonstrate what I call invocations of stone, by addressing crafted works (i.e., architecture and sculpture) as signs of human history and affect. Later texts from Celan’s collections of the 1950s and 1960s gravitate toward “found” stone, and import geological discourse into lyric—a project foreshadowed in the later texts of Mandelstam, a poet whom Celan translated and declared a formative influence. Their texts think in terms of stone, aligning lyric with notions of stone’s alternative, natural history. Celan's texts, along with those of his contemporary Sachs, also seek to write as stone, by emulating stone’s varying legibilities—as a scientific or mystical record of the readable earth, or as a tabula rasa for more idiosyncratic, phenomenological readings. In the light of debates about the legitimacy and efficacy of post-Holocaust lyric, Celan's and Sachs' texts demonstrate stone's potentiality to model reconceptualized lyric languages and subjectivities. My readings are buttressed by considerations of the “language of things” in texts by Benjamin and others, as well as ideas about lyric subjectivity drawn from Nietzsche, Susman, Adorno, and Anglo-American literary theory. Challenging the suppositions that lyric represents an individual subjectivity, expression, and voice, Lyric Petrologies introduces the poetics of nonhuman, recalcitrant, and mute stone within the context of contemporary revisions of the idea of lyric. My readings in Lyric Petrologies also add to contemporary critical conversations on object theories and new materialisms, by acknowledging and investigating varying ways in which poetic language mediates matter.PHDComparative LiteratureUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113578/1/pierrer_1.pd

Comparing teacher resilience in primary schools in challenged contexts

The purpose of this comparative secondary analysis study was to contribute knowledge on teacher resilience in spaces of high social disadvantage by employing Sense of Coherence as theoretical framework. The study purposively sampled extant data from the Isithebe study, which included conveniently sampled teachers (n = 36) from six purposively sampled peri-urban primary schools characterised by adversity. The extant data (completed Teacher Resilience Questionnaires) were analysed and compared with the objective to investigate how well the underlying variable structure of the Teacher Resilience Questionnaire holds in the setting of the present study. A further objective was to analyse Teacher Resilience Questionnaires to compare teacher resilience traits that can act as either protective resources or risk factors. Data were analysed using SPSS by computing descriptive, reliability and inferential statistics. The results indicated that the underlying variable structure of the Teacher Resilience Questionnaire holds up well in the setting of South African, peri-urban primary schools in challenged contexts, except for the Teacher Emotion scale. There were no significant differences in teacher resilience between the six schools or between the two age groups. Results further indicated that perceived teacher resilience of teachers in peri-urban primary schools in challenged contexts was high. Specific traits which seem to act as internal protective resources for the teachers in spaces where structural disparity abounds as well as contextual resources were identified. These teacher protective resources are comparative to other resources found in other parts of the world. However, unlike other countries, protective resources contributed equally to high teacher resilience.Mini Dissertation (MEd (Educational Psychology))--University of Pretoria, 2020.Educational PsychologyMEd (Educational Psychology)Unrestricte