Supporting parallelism in server-based multiprocessor systems

Developing an efficient server-based real-time scheduling solution that supports dynamic task-level parallelism is now relevant to even the desktop and embedded domains and no longer only to the high performance computing market niche. This paper proposes a novel approach that combines the constantbandwidth server abstraction with a work-stealing load balancing scheme which, while ensuring isolation among tasks, enables a task to be executed on more than one processor at a given time instant.

Capacity sharing and stealing in dynamic server-based real-time systems

This paper proposes a dynamic scheduler that supports the coexistence of guaranteed and non-guaranteed bandwidth servers to efficiently handle soft-tasks’ overloads by making additional capacity available from two sources: (i) residual capacity allocated but unused when jobs complete in less than their budgeted execution time; (ii) stealing capacity from inactive non-isolated servers used to schedule best-effort jobs. The effectiveness of the proposed approach in reducing the mean tardiness of periodic jobs is demonstrated through extensive simulations. The achieved results become even more significant when tasks’ computation times have a large variance.

Implementation of a Campus wide DGPS Data Server

Although the Navigation Satellite Timing and Ranging (NAVSTAR) Global Positioning System (GPS) is, de facto, the standard positioning system used in outdoor navigation, it does not provide, per se, all the features required to perform many outdoor navigational tasks. The accuracy of the GPS measurements is the most critical issue. The quest for higher position readings accuracy led to the development, in the late nineties, of the Differential Global Positioning System (DGPS). The differential GPS method detects the range errors of the GPS satellites received and broadcasts them. The DGPS/GPS receivers correlate the DGPS data with the GPS satellite data they are receiving, granting users increased accuracy. DGPS data is broadcasted using terrestrial radio beacons, satellites and, more recently, the Internet. Our goal is to have access, within the ISEP campus, to DGPS correction data. To achieve this objective we designed and implemented a distributed system composed of two main modules which are interconnected: a distributed application responsible for the establishment of the data link over the Internet between the remote DGPS stations and the campus, and the campus-wide DGPS data server application. The DGPS data Internet link is provided by a two-tier client/server distributed application where the server-side is connected to the DGPS station and the client-side is located at the campus. The second unit, the campus DGPS data server application, diffuses DGPS data received at the campus via the Intranet and via a wireless data link. The wireless broadcast is intended for DGPS/GPS portable receivers equipped with an air interface and the Intranet link is provided for DGPS/GPS receivers with just a RS232 DGPS data interface. While the DGPS data Internet link servers receive the DGPS data from the DGPS base stations and forward it to the DGPS data Internet link client, the DGPS data Internet link client outputs the received DGPS data to the campus DGPS data server application. The distributed system is expected to provide adequate support for accurate (sub-metric) outdoor campus navigation tasks. This paper describes in detail the overall distributed application.

Visualisierung der Report Server Utalisation

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SwissTargetPrediction: a web server for target prediction of bioactive small molecules.

Bioactive small molecules, such as drugs or metabolites, bind to proteins or other macro-molecular targets to modulate their activity, which in turn results in the observed phenotypic effects. For this reason, mapping the targets of bioactive small molecules is a key step toward unraveling the molecular mechanisms underlying their bioactivity and predicting potential side effects or cross-reactivity. Recently, large datasets of protein-small molecule interactions have become available, providing a unique source of information for the development of knowledge-based approaches to computationally identify new targets for uncharacterized molecules or secondary targets for known molecules. Here, we introduce SwissTargetPrediction, a web server to accurately predict the targets of bioactive molecules based on a combination of 2D and 3D similarity measures with known ligands. Predictions can be carried out in five different organisms, and mapping predictions by homology within and between different species is enabled for close paralogs and orthologs. SwissTargetPrediction is accessible free of charge and without login requirement at http://www.swisstargetprediction.ch.

Use of Reversions, Iowa Department of Transportation, 2014

The Iowa Department of Transportation spent $406,240 of the Fiscal year 2013 RUTF/PRF budget reversion in FY 2014 for desktop and server software, information technology professional services, training and computer equipment.

Invenio customization for CERN Document Server

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Evaluación de intervención de alertas para riesgo cardiovascular por diclofenaco en afiliados al régimen contributivo 2014 -2015

El objetivo fue evaluar la intervención de las alertas en la prescripción de diclofenaco. Estudio observacional, comparativo, post intervención, de un antes después, en pacientes con prescripción de diclofenaco. Se evaluó la intervención de las alertas restrictivas antes y después de su implementación en los pacientes prescritos con diclofenaco y que tenían asociado un diagnóstico de riesgo cardiovascular según CIE 10 o eran mayores de 65 años. Un total de 315.135 transacciones con prescripción de diclofenaco, en 49.355 pacientes promedio mes. El 94,8% (298.674) de las transacciones fueron prescritas por médicos generales.

Assessing the quality of modelled 3D protein structures using the ModFOLD server

Model quality assessment programs (MQAPs) aim to assess the quality of modelled 3D protein structures. The provision of quality scores, describing both global and local (per-residue) accuracy are extremely important, as without quality scores we are unable to determine the usefulness of a 3D model for further computational and experimental wet lab studies.Here, we briefly discuss protein tertiary structure prediction, along with the biennial Critical Assessment of Techniques for Protein Structure Prediction (CASP) competition and their key role in driving the field of protein model quality assessment methods (MQAPs). We also briefly discuss the top MQAPs from the previous CASP competitions. Additionally, we describe our downloadable and webserver-based model quality assessment methods: ModFOLD3, ModFOLDclust, ModFOLDclustQ, ModFOLDclust2, and IntFOLD-QA. We provide a practical step-by-step guide on using our downloadable and webserver-based tools and include examples of their application for improving tertiary structure prediction, ligand binding site residue prediction, and oligomer predictions.

Parmodel: a web server for automated comparative modeling of proteins

Parmodel is a web server for automated comparative modeling and evaluation of protein structures. The aim of this tool is to help inexperienced users to perform modeling, assessment, visualization, and optimization of protein models as well as crystallographers to evaluate structures solved experimentally. It is subdivided in four modules: Parmodel Modeling, Parmodel Assessment, Parmodel Visualization, and Parmodel Optimization. The main module is the Parmodel Modeling that allows the building of several models ford a same protein in a reduced time, through the distribution of modeling processes on a Beowulf cluster. Parmodel automates and integrates the main softwares used in comparative modeling as MODELLER, Whatcheck, Procheck, Raster3D, Molscript, and Gromacs. This web server is freely accessible at http://www.biocristalografia.df.ibilce.unesp.br/tools/parmodel. (C) 2004 Elsevier B.V. All rights reserved.

Workout Manager Android App

L’obiettivo di questa tesi è quello di progettare e sviluppare un'applicazione Android inerente alle palestre. In particolare l'utente finale dovrà essere in grado di poter scaricare i propri allenamenti da un server SQL remoto e visualizzarli con un layout grafico che ne ricordi la struttura di un allenamento cartaceo (con l’utilizzo quindi di schede, esercizi, serie, ripetizioni,...). Attraverso una procedura guidata, l’applicazione dovrà seguire l’utente durante il suo allenamento e registrarne i progressi. Questi ultimi dovranno essere memorizzati permanentemente e visualizzati attraverso dei grafici.

Sistema de monitorización de sistemas distribuidos

La computación distribuida ha estado presente desde hace unos cuantos años, pero es quizás en la actualidad cuando está contando con una mayor repercusión. En los últimos años el modelo de computación en la nube (Cloud computing) ha ganado mucha popularidad, prueba de ello es la cantidad de productos existentes. Todo sistema informático requiere ser controlado a través de sistemas de monitorización que permiten conocer el estado del mismo, de tal manera que pueda ser gestionado fácilmente. Hoy en día la mayoría de los productos de monitorización existentes limitan a la hora de visualizar una representación real de la arquitectura de los sistemas a monitorizar, lo que puede dificultar la tarea de los administradores. Es decir, la visualización que proporcionan de la arquitectura del sistema, en muchos casos se ve influenciada por el diseño del sistema de visualización, lo que impide ver los niveles de la arquitectura y las relaciones entre estos. En este trabajo se presenta un sistema de monitorización para sistemas distribuidos o Cloud, que pretende dar solución a esta problemática, no limitando la representación de la arquitectura del sistema a monitorizar. El sistema está formado por: agentes, que se encargan de la tarea de recolección de las métricas del sistema monitorizado; un servidor, al que los agentes le envían las métricas para que las almacenen en una base de datos; y una aplicación web, a través de la que se visualiza toda la información. El sistema ha sido probado satisfactoriamente con la monitorización de CumuloNimbo, una plataforma como servicio (PaaS), que ofrece interfaz SQL y procesamiento transaccional altamente escalable sobre almacenes clave valor. Este trabajo describe la arquitectura del sistema de monitorización, y en concreto, el desarrollo de la principal contribución al sistema, la aplicación web. ---ABSTRACT---Distributed computing has been around for quite a long time, but now it is becoming more and more important. In the last few years, cloud computing, a branch of distributed computing has become very popular, as its different products in the market can prove. Every computing system requires to be controlled through monitoring systems to keep them functioning correctly. Currently, most of the monitoring systems in the market only provide a view of the architectures of the systems monitored, which in most cases do not permit having a real view of the system. This lack of vision can make administrators’ tasks really difficult. If they do not know the architecture perfectly, controlling the system based on the view that the monitoring system provides is extremely complicated. The project introduces a new monitoring system for distributed or Cloud systems, which shows the real architecture of the system. This new system is composed of several elements: agents, which collect the metrics of the monitored system; a server, which receives the metrics from the agents and saves them in a database; and a web application, which shows all the data collected in an easy way. The monitoring system has been tested successfully with Cumulonimbo. CumuloNimbo is a platform as a service (PaaS) which offers an SQL interface and a high-scalable transactional process. This platform works over key-value storage. This project describes the architecture of the monitoring system, especially, the development of the web application, which is the main contribution to the system.

Server power modeling for run-time energy optimization of cloud computing facilities

As advanced Cloud services are becoming mainstream, the contribution of data centers in the overall power consumption of modern cities is growing dramatically. The average consumption of a single data center is equivalent to the energy consumption of 25.000 households. Modeling the power consumption for these infrastructures is crucial to anticipate the effects of aggressive optimization policies, but accurate and fast power modeling is a complex challenge for high-end servers not yet satisfied by analytical approaches. This work proposes an automatic method, based on Multi-Objective Particle Swarm Optimization, for the identification of power models of enterprise servers in Cloud data centers. Our approach, as opposed to previous procedures, does not only consider the workload consolidation for deriving the power model, but also incorporates other non traditional factors like the static power consumption and its dependence with temperature. Our experimental results shows that we reach slightly better models than classical approaches, but simul- taneously simplifying the power model structure and thus the numbers of sensors needed, which is very promising for a short-term energy prediction. This work, validated with real Cloud applications, broadens the possibilities to derive efficient energy saving techniques for Cloud facilities.

Leakage-aware cooling management for improving server energy efficiency

The computational and cooling power demands of enterprise servers are increasing at an unsustainable rate. Understanding the relationship between computational power, temperature, leakage, and cooling power is crucial to enable energy-efficient operation at the server and data center levels. This paper develops empirical models to estimate the contributions of static and dynamic power consumption in enterprise servers for a wide range of workloads, and analyzes the interactions between temperature, leakage, and cooling power for various workload allocation policies. We propose a cooling management policy that minimizes the server energy consumption by setting the optimum fan speed during runtime. Our experimental results on a presently shipping enterprise server demonstrate that including leakage awareness in workload and cooling management provides additional energy savings without any impact on performance.