Lewis' enhanced laboratory for research into the fatigue and constitutive behavior of high temperature materials

Lewis Research Center's high temperature fatigue laboratory has undergone significant changes resulting in the addition of several new experimental capabilities. New materials testing systems have been installed enabling research to be conducted in multiaxial fatigue and deformation at high temperature, as well as cumulative creep-fatigue damage wherein the relative failure-life levels are widely separated. A key component of the new high-temperature fatigue and structures laboratory is a local, distributed computer system whose hardware and software architecture emphasizes a high degree of configurability, which in turn, enables the researcher to tailor a solution to the problem at hand

Computer aided design

technical reportThe report is based on the proposal submitted to the National Science Foundation in September 1981, as part of the Coordinated Experimental Computer Science Research Program. The sections covering the budget and biographical data on the senior research personnel have not been included. Also, the section describing the department facilities at the time of the proposal submission is not included, because it would be only of historical interest

A high temperature fatigue and structures testing facility

As man strives for higher levels of sophistication in air and space transportation, awareness of the need for accurate life and material behavior predictions for advanced propulsion system components is heightened. Such sophistication will require complex operating conditions and advanced materials to meet goals in performance, thrust-to-weight ratio, and fuel efficiency. To accomplish these goals will require that components be designed using a high percentage of the material's ultimate capabilities. This serves only to complicate matters dealing with life and material behavior predictions. An essential component of material behavior model development is the underlying experimentation which must occur to identify phenomena. To support experimentation, the NASA Lewis Research Center's High Temperature Fatigue and Structures Laboratory has been expanded significantly. Several new materials testing systems have been added, as well as an extensive computer system. The intent of this paper is to present an overview of the laboratory, and to discuss specific aspects of the test systems. A limited discussion of computer capabilities will also be presented

A large scale software system for simulation and design optimization of mechanical systems

The concept of an advanced integrated, networked simulation and design system is outlined. Such an advanced system can be developed utilizing existing codes without compromising the integrity and functionality of the system. An example has been used to demonstrate the applicability of the concept of the integrated system outlined here. The development of an integrated system can be done incrementally. Initial capabilities can be developed and implemented without having a detailed design of the global system. Only a conceptual global system must exist. For a fully integrated, user friendly design system, further research is needed in the areas of engineering data bases, distributed data bases, and advanced user interface design

The dynamics of computerization in a social science research team : a case study of infrastructure, strategies, and skills

This paper examines the dynamics of Computerization in a PC-oriented research group through a case study. The time and skill in integrating computing into the labor processes of research are often significant "hidden costs" of computerization. Computing infrastructure plays a key role in reducing these costs may be enhanced by careful organization. We illustrate computerization strategies that we have found to be productive and unproductive. Appropriate computerization strategies depend as much on the structuring of resources and interests in the larger social setting, as on a technical characterization of tasks

An Architecture for distributed multimedia database systems

In the past few years considerable demand for user oriented multimedia information systems has developed. These systems must provide a rich set of functionality so that new, complex, and interesting applications can be addressed. This places considerable importance on the management of diverse data types including text, images, audio and video. These requirements generate the need for a new generation of distributed heterogeneous multimedia database systems. In this paper we identify a set of functional requirements for a multimedia server considering database management, object synchronization and integration, and multimedia query processing. A generalization of the requirements to a distributed system is presented, and some of our current research and developing activities are discussed

Three Highly Parallel Computer Architectures and Their Suitability for Three Representative Artificial Intelligence Problems

Virtually all current Artificial Intelligence (AI) applications are designed to run on sequential (von Neumann) computer architectures. As a result, current systems do not scale up. As knowledge is added to these systems, a point is reached where their performance quickly degrades. The performance of a von Neumann machine is limited by the bandwidth between memory and processor (the von Neumann bottleneck). The bottleneck is avoided by distributing the processing power across the memory of the computer. In this scheme the memory becomes the processor (a smart memory ). This paper highlights the relationship between three representative AI application domains, namely knowledge representation, rule-based expert systems, and vision, and their parallel hardware realizations. Three machines, covering a wide range of fundamental properties of parallel processors, namely module granularity, concurrency control, and communication geometry, are reviewed: the Connection Machine (a fine-grained SIMD hypercube), DADO (a medium-grained MIMD/SIMD/MSIMD tree-machine), and the Butterfly (a coarse-grained MIMD Butterflyswitch machine)

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

Architecture independent environment for developing engineering software on MIMD computers

Engineers are constantly faced with solving problems of increasing complexity and detail. Multiple Instruction stream Multiple Data stream (MIMD) computers have been developed to overcome the performance limitations of serial computers. The hardware architectures of MIMD computers vary considerably and are much more sophisticated than serial computers. Developing large scale software for a variety of MIMD computers is difficult and expensive. There is a need to provide tools that facilitate programming these machines. First, the issues that must be considered to develop those tools are examined. The two main areas of concern were architecture independence and data management. Architecture independent software facilitates software portability and improves the longevity and utility of the software product. It provides some form of insurance for the investment of time and effort that goes into developing the software. The management of data is a crucial aspect of solving large engineering problems. It must be considered in light of the new hardware organizations that are available. Second, the functional design and implementation of a software environment that facilitates developing architecture independent software for large engineering applications are described. The topics of discussion include: a description of the model that supports the development of architecture independent software; identifying and exploiting concurrency within the application program; data coherence; engineering data base and memory management