High Performance Computing on Cluster and Multicore Architecture

High Performance Computing have several issues on architecture, resources, computational model and data. The challenge is establishing the mature architecture with scalable resources. The cluster architecture and multicore architecture implement to produce high performance on computation and process. This research works on architecture development and performance analysis. The cluster architecture build on Raspberry Pi, a single board computer, implement MPICH2. Raspberry Pi cluster build on Raspbian Wheezy operating system and test by metrics computation applications. The multicore architecture build on single computer with Core i5 and Core i7 architecture. The research use himeno98 and himeno16Large tools to analysis the processor and memory allocation. The test run on 1000x1000 matrices and benchmarked with OpenMP. The analysis focuses on CPU Time, FLOPS, and score. The result show on cluster architecture have 2576,07 sec in CPU Time, 86,96 MLPOS, and 2,69 score. The result on Core i5 architecture have 55,57 sec in CPU time, 76,30 MLOPS, and 0,92 score. The result in Core i7 architecture have 59,56 sec CPU Time, 1427,61 MLOPS, and 17,23 score. The cluster and multicore architecture results show that computing process are effected by architecture models. High performance computing architecture that has been built on this result can give learn on the development of HPC architecture models, and baseline performance. In the future it will use for determine the delivery architecture model on HPC and can be test by more variation of load

The Problem of Semantics in the Metadata Mess

This presentation addresses problems related to the volume of available scientific data, and its accessibility or inaccessibility to researchers who seek it. Topics addressed include metadata and reducing semantic diversity, especially as they refer to geospatial and other architecture

Tracking Institutional Data Assets Using OAI-PMH

This master's paper explores the impetus for data stewardship policies and guidelines and describes an empirical study conducted to assess the feasibility of employing OAI-PMH as a tool to enable institutions to track data stewardship activities. Quantitative analyses of Dublin Core metadata harvested from twelve data-specific repositories were used to make conclusions about the current state of OAI-PMH implementation, to consider ways in which the unique properties of scholarly domains and their data might be reflected in metadata values, and to suggest steps repositories can take to enable the development and implementation of a federated index of distributed data records as a tool to support the sustainability of the research enterprise

Estrategias de descomposición en dominios para entornos Grid

En este trabajo estamos interesados en realizar simulaciones numéricas basadas en elementos finitos con integración explícita en el tiempo utilizando la tecnología Grid.Actualmente, las simulaciones explícitas de elementos finitos usan la técnica de descomposición en dominios con particiones balanceadas para realizar la distribución de los datos. Sin embargo, esta distribución de los datos presenta una degradación importante del rendimiento de las simulaciones explícitas cuando son ejecutadas en entornos Grid. Esto se debe principalmente, a que en un ambiente Grid tenemos comunicaciones heterogéneas, muy rápidas dentro de una máquina y muy lentas fuera de ella. De esta forma, una distribución balanceada de los datos se ejecuta a la velocidad de las comunicaciones más lentas. Para superar este problema proponemos solapar el tiempo de la comunicación remota con el tiempo de cálculo. Para ello, dedicaremos algunos procesadores a gestionar las comunicaciones más lentas, y el resto, a realizar cálculo intensivo. Este esquema de distribución de los datos, requiere que la descomposición en dominios sea no balanceada, para que, los procesadores dedicados a realizar la gestión de las comunicaciones lentas tengan apenas carga computacional. En este trabajo se han propuesto y analizado diferentes estrategias para distribuir los datos y mejorar el rendimiento de las aplicaciones en entornos Grid. Las estrategias de distribución estáticas analizadas son: 1. U-1domains: Inicialmente, el dominio de los datos es dividido proporcionalmente entre las máquinas dependiendo de su velocidad relativa. Posteriormente, en cada máquina, los datos son divididos en nprocs-1 partes, donde nprocs es el número de procesadores total de la máquina. Cada subdominio es asignado a un procesador y cada máquina dispone de un único procesador para gestionar las comunicaciones remotas con otras máquinas. 2. U-Bdomains: El particionamiento de los datos se realiza en dos fases. La primera fase es equivalente a la realizada para la distribución U-1domains. La segunda fase, divide, proporcionalmente, cada subdominio de datos en nprocs-B partes, donde B es el número de comunicaciones remotas con otras máquinas (dominios especiales). Cada máquina tiene más de un procesador para gestionar las comunicaciones remotas. 3. U-CBdomains: En esta distribución, se crean tantos dominios especiales como comunicaciones remotas. Sin embargo, ahora los dominios especiales son asignados a un único procesador dentro de la máquina. De esta forma, cada subdomino de datos es dividido en nprocs-1 partes. La gestión de las comunicaciones remotas se realiza concurrentemente mediante threads. Para evaluar el rendimiento de las aplicaciones sobre entornos Grid utilizamos Dimemas. Para cada caso, evaluamos el rendimiento de las aplicaciones en diferentes entornos y tipos de mallas. Los resultados obtenidos muestran que:· La distribución U-1domains reduce los tiempos de ejecución hasta un 45% respecto a la distribución balanceada. Sin embargo, esta distribución no resulta efectiva para entornos Grid compuestos de una gran cantidad de máquinas remotas.· La distribución U-Bdomains muestra ser más eficiente, ya que reduce el tiempo de ejecución hasta un 53%. Sin embargo, la escalabilidad de ésta distribución es moderada, debido a que puede llegar a tener un gran número de procesadores que no realizan cálculo intensivo. Estos procesadores únicamente gestionan las comunicaciones remotas. Como limite sólo podemos aplicar esta distribución si más del 50% de los procesadores en una máquina realizan cálculo.· La distribución U-CBdomains reduce los tiempos de ejecución hasta 30%, pero no resulta tan efectiva como la distribución U-Bdomains. Sin embargo, esta distribución incrementa la utilización de los procesadores en 50%, es decir que disminuye los procesadores ociosos

Evolving a secure grid-enabled, distributed data warehouse : a standards-based perspective

As digital data-collection has increased in scale and number, it becomes an important type of resource serving a wide community of researchers. Cross-institutional data-sharing and collaboration introduce a suitable approach to facilitate those research institutions that are suffering the lack of data and related IT infrastructures. Grid computing has become a widely adopted approach to enable cross-institutional resource-sharing and collaboration. It integrates a distributed and heterogeneous collection of locally managed users and resources. This project proposes a distributed data warehouse system, which uses Grid technology to enable data-access and integration, and collaborative operations across multi-distributed institutions in the context of HV/AIDS research. This study is based on wider research into OGSA-based Grid services architecture, comprising a data-analysis system which utilizes a data warehouse, data marts, and near-line operational database that are hosted by distributed institutions. Within this framework, specific patterns for collaboration, interoperability, resource virtualization and security are included. The heterogeneous and dynamic nature of the Grid environment introduces a number of security challenges. This study also concerns a set of particular security aspects, including PKI-based authentication, single sign-on, dynamic delegation, and attribute-based authorization. These mechanisms, as supported by the Globus Toolkit’s Grid Security Infrastructure, are used to enable interoperability and establish trust relationship between various security mechanisms and policies within different institutions; manage credentials; and ensure secure interactions

Ranked Similarity Search of Scientific Datasets: An Information Retrieval Approach

In the past decade, the amount of scientific data collected and generated by scientists has grown dramatically. This growth has intensified an existing problem: in large archives consisting of datasets stored in many files, formats and locations, how can scientists find data relevant to their research interests? We approach this problem in a new way: by adapting Information Retrieval techniques, developed for searching text documents, into the world of (primarily numeric) scientific data. We propose an approach that uses a blend of automated and curated methods to extract metadata from large repositories of scientific data. We then perform searches over this metadata, returning results ranked by similarity to the search criteria. We present a model of this approach, and describe a specific implementation thereof performed at an ocean-observatory data archive and now running in production. Our prototype implements scanners that extract metadata from datasets that contain different kinds of environmental observations, and a search engine with a candidate similarity measure for comparing a set of search terms to the extracted metadata. We evaluate the utility of the prototype by performing two user studies; these studies show that the approach resonates with users, and that our proposed similarity measure performs well when analyzed using standard Information Retrieval evaluation methods. We performed performance tests to explore how continued archive growth will affect our goal of interactive response, developed and applied techniques that mitigate the effects of that growth, and show that the techniques are effective. Lastly, we describe some of the research needed to extend this initial work into a true Google for data

An adjusted material flow cost accounting framework for process waste-reduction decisions in the South African Brewery industry

While contemporary environmental problems arise partly from increased industrial activities resulting in waste creation, the continued extraction and depletion of earth’s natural resources by organisations to meet consumers’ demand have led to unsustainable business practices (Jennings & Zandbergen 1995). Moreover, reversing the negative environmental impact caused by unsustainable business practices is the responsibility of the organisations whose activities cause harm to the environment (Ahuja & Khamba 2008). More importantly, managers require adequate and accurate financial and non-financial information on their unsustainable business practices to successfully manage both internal and external environmental effects of their actions (Schaltegger & Burritt 2000). But the lack of contemporary management accounting tools to capture waste information in the brewery process reduces the chance to improve waste-reduction decisions while opportunities for cost savings are also lost. Admittedly, Gale (2006:1231) argues that conventional management accounting Systems (MASs) do not have the ability to adequately monitor the increasing material costs and overheads in production processes with sufficient transparency. Nevertheless, this inability to provide adequate process waste information may likely limit organisations’ effort to implement and achieve desired waste-reduction strategies. As a result, it is imperative to integrate both physical and monetary waste information for sound decision-making. The main objective of this study is to adopt and adjust the existing MFCA framework to support and improve on managers’ process waste-reduction decisions in the South African brewery industry. In order to achieve this main objective, the study: • examines the extent to which conventional MASs provides process waste information to support waste-reduction decisions in a micro-brewery (Hope Brewery) and a large brewery (SAB Ltd); • assesses the impact of insufficient process waste information as provided by the conventional MASs on brewery waste-reduction decisions in a micro-brewery (Hope Brewery) and a large brewery (SAB Ltd); and • adjusts the existing MFCA framework to include waste categories subsumed or neglected in the provision of waste information to improve brewery waste-reduction decisions. vi The study adopted an exploratory multiple case study approach by means of in-depth interviews and a pilot study in two breweries- a micro-brewery and a large brewery to achieve the study objectives. Findings revealed that, while the use of technology is essential to reduce brewery process waste, there is lack of appropriate waste-capturing management accounting tool in both organisations. Besides it is essential for organisations to adopt appropriate management accounting tool to capture waste-related information for improved waste-reduction decisions and selection of appropriate waste management strategy. The study therefore suggests the adoption of an adjusted MFCA framework for a more robust approach to improve waste-reduction decisions since ‘what cannot be measured cannot be managed’.Management AccountingD. Comm. (Management Accounting