4 research outputs found

    Management: A bibliography for NASA managers

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    This bibliography lists 731 reports, articles and other documents introduced into the NASA Scientific and Technical Information System in 1990. Items are selected and grouped according to their usefulness to the manager as manager. Citations are grouped into ten subject categories: human factors and personnel issues; management theory and techniques; industrial management and manufacturing; robotics and expert systems; computers and information management; research and development; economics, costs and markets; logistics and operations management; reliability and quality control; and legality, legislation, and policy

    Optimizing hardward granularity in parallel systems

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    Effects of Communication Protocol Stack Offload on Parallel Performance in Clusters

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    The primary research objective of this dissertation is to demonstrate that the effects of communication protocol stack offload (CPSO) on application execution time can be attributed to the following two complementary sources. First, the application-specific computation may be executed concurrently with the asynchronous communication performed by the communication protocol stack offload engine. Second, the protocol stack processing can be accelerated or decelerated by the offload engine. These two types of performance effects can be quantified with the use of the degree of overlapping Do and degree of acceleration Daccs. The composite communication speedup metrics S_comm(Do, Daccs) can be used in order to quantify the combined effects of the protocol stack offload. This dissertation thesis is validated empirically. The degree of overlapping Do, the degree of acceleration Daccs, and the communication speedup Scomm characteristic of the system configurations under test are derived in the course of experiments performed for the system configurations of interest. It is shown that the proposed metrics adequately describe the effects of the protocol stack offload on the application execution time. Additionally, a set of analytical models of the networking subsystem of a PC-based cluster node is developed. As a result of the modeling, the metrics Do, Daccs, and Scomm are obtained. The models are evaluated as to their complexity and precision by comparing the modeling results with the measured values of Do, Daccs, and Scomm. The primary contributions of this dissertation research are as follows. First, the metric Daccs and Scomm are introduced in order to complement the Do metric in its use for evaluation of the effects of optimizations in the networking subsystem on parallel performance in clusters. The metrics are shown to adequately describe CPSO performance effects. Second, a method for assessing performance effects of CPSO scenarios on application performance is developed and presented. Third, a set of analytical models of cluster node networking subsystems with CPSO capability is developed and characterised as to their complexity and precision of the prediction of the Do and Daccs metrics

    Procesamiento paralelo : Balance de carga din谩mico en algoritmo de sorting

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    Algunas t茅cnicas de sorting intentan balancear la carga mediante un muestreo inicial de los datos a ordenar y una distribuci贸n de los mismos de acuerdo a pivots. Otras redistribuyen listas parcialmente ordenadas de modo que cada procesador almacene un n煤mero aproximadamente igual de claves, y todos tomen parte del proceso de merge durante la ejecuci贸n. Esta Tesis presenta un nuevo m茅todo que balancea din谩micamente la carga basado en un enfoque diferente, buscando realizar una distribuci贸n del trabajo utilizando un estimador que permita predecir la carga de trabajo pendiente. El m茅todo propuesto es una variante de Sorting by Merging Paralelo, esto es, una t茅cnica basada en comparaci贸n. Las ordenaciones en los bloques se realizan mediante el m茅todo de Burbuja o Bubble Sort con centinela. En este caso, el trabajo a realizar -en t茅rminos de comparaciones e intercambios- se encuentra afectada por el grado de desorden de los datos. Se estudi贸 la evoluci贸n de la cantidad de trabajo en cada iteraci贸n del algoritmo para diferentes tipos de secuencias de entrada, n datos con valores de a n sin repetici贸n, datos al azar con distribuci贸n normal, observ谩ndose que el trabajo disminuye en cada iteraci贸n. Esto se utiliz贸 para obtener una estimaci贸n del trabajo restante esperado a partir de una iteraci贸n determinada, y basarse en el mismo para corregir la distribuci贸n de la carga. Con esta idea, el m茅toEs revisado por: http://sedici.unlp.edu.ar/handle/10915/9500Facultad de Ciencias Exacta
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