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Federated Big Data for Resource Aggregation and Load Balancing with DIRAC

Procedia computer Science 2015年 51卷 2769-2773页

作者： Víctor Fernández Víctor Méndez Tomás F. Pena Department of Particle Physics University of Santiago de Compostela Spain Computer Architecture and Operating Systems (CAOS) Universitat Autónoma de Barcelona Spain Research Center in Information Technologies (CiTIUS) University of Santiago de Compostela Spain

BigDataDIRAC is a Big Data solution with a Distributed Infrastructure with Remote Agent Control (DIRAC) access point. Users have the opportunity to access multiple Big Data resources scattered in different geographical areas, such as access to grid resources. This approach opens the possibility of offering not only grid and cloud to the users, but also Big Data resources from the same DIRAC environment. In this work, we describe a system to allow access to a federation of Big Data resources, including load balancing, using DIRAC. Our results demonstrate the ability of BigDataDIRAC to manage jobs driven by dataset location stored in the Hadoop File System (HDFS) of the Hadoop distributed clusters. DIRAC is used to monitor the execution, collect the necessary statistical data, and upload the results from the remote HDFS to the SandBox Storage machine. Performance results demonstrate that BigDataDIRAC load balancing is able to aggregate resources in an efficient manner.

关键词： Big Data federation DIRAC MapReduce Hadoop Cloud Computing

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Agent Based Model and Simulation of MRSA Transmission in Emergency departments

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Procedia computer Science 2015年 51卷 443-452页

作者： Cecilia Jaramillo Manel Taboada Francisco Epelde Dolores Rexachs Emilio Luque Department of Computer Architecture & Operating Systems Universitat Autonoma de Barcelona Bellaterra 08193 Barcelona Spain Tomas Cerda Computer Science School Universitat Autonoma de Barcelona Sant Cugat 08714 Barcelona Spain Medicine Department Hospital Universitari Parc Tauĺı Universitat Autonoma de Barcelona Sabadell 08208 Barcelona Spain

In healthcare environments we can find several microorganisms causing nosocomial infection, and of which one of the most common and most dangerous is Methicillin-resistant Staphylococcus Aureus. Its presence can lead to serious complications to the *** work uses Agent Based Modeling and Simulation techniques to build the model and the simulation of Methicillin-resistant Staphylococcus Aureus contact transmission in emergency departments. The simulator allows us to build virtual scenarios with the aim of understanding the phenomenon of MRSA transmission and the potential impact of the implementation of different measures in propagation rates.

关键词： Agent Based Modeling and Simulation MRSA Transmission Emergency department Complex System.

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An Optical Transceiver Reliability Study based on SFP Monitoring and OS-level Metric Data

An Optical Transceiver Reliability Study based on SFP Monito...

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IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGRID)

作者： Paolo Notaro Qiao Yu Soroush Haeri Jorge Cardoso Michael Gerndt Huawei Technologies Duesseldorf GmbH Munich Germany Chair of Computer Architecture and Parallel Systems Technical University of Munich Germany Chair of Distributed and Operating Systems Technical University of Berlin Germany Department of Informatics Engineering/CISUC University of Coimbra Portugal

The increasing demand for cloud computing drives the expansion in scale of datacenters and their internal optical network, in a strive for increasing bandwidth, high reliability, and lower latency. Optical transceivers are essential elements of optical networks, whose reliability has not been well-studied compared to other hardware components. In this paper, we leverage high quantities of monitoring data from optical transceivers and OS-level metrics to provide statistical insights about the occurrence of optical transceiver failures. We estimate transceiver failure rates and normal operating ranges for monitored attributes, correlate early-observable patterns to known failure symptoms, and finally develop failure prediction models based on our analyses. Our results enable network administrators to deploy early-warning systems and enact predictive maintenance strategies, such as replacement or traffic re-routing, reducing the number of incidents and their associated costs.

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HIGH THROUGHPUT IMAGE CODEC FOR HIGH-RESOLUTION SATELLITE IMAGES

HIGH THROUGHPUT IMAGE CODEC FOR HIGH-RESOLUTION SATELLITE IM...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Carlos de Cea-Dominguez P. Enfedaque Juan C. Moure Joan Bartrina-Rapesta Francesc Auli-Llinas Department of Information and Communications Engineering Universitat Autònoma de Barcelona Spain Department of Computer Architecture and Operating Systems Universitat Autònoma de Barcelona Spain Computational Research Division Lawrence Berkeley National Laboratory

The growth in the use of satellite images has generated the need for their fast compression, processing, and distribution. JPEG2000 is a widespread standard for the compression and transmission of such images once they are in the ground. Despite its advanced features and excellent coding performance, JPEG2000 demands significant computational resources. This paper introduces a wavelet-based codec that uses the JPEG2000 framework, but replaces its most computationally demanding coding stage by a highly parallel engine. When executed in Graphics Processing Units to code high-resolution satellite images, the proposed codec achieves speed-ups of up to 8× when compared to the fastest implementation of JPEG2000 executed in a multi-core platform.

关键词： High throughput image coding Bitplane image coding JPEG2000

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Simulating the micro-level behavior of emergency department for macro-level features prediction 15

Simulating the micro-level behavior of emergency department ...

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Simulation Winter Conference

作者： Zhengchun Liu Dolores Rexachs Emilio Luque Francisco Epelde Eduardo Cabrera Computer Architecture & Operating Systems University Autònoma of Barcelona Bellaterra Barcelona SPAIN Medicine Department Hospital Universitari Parc Taulí Sabadell Barcelona SPAIN Institute of Advanced Research Computing Durham University Durham UK

ISBN: (纸本)9781467397414

Emergency departments are currently facing major pressures due to rising demand caused by population growth, aging and high expectations of service quality. With changes continuing to challenge healthcare systems, developing solutions and formulating policies require a good understanding of the complex and dynamic nature of the relevant systems. However, as a typically complex system, it is hard to grasp the non-linear association between macro-level features and micro-level behavior for a systematic understanding. Instead of describing all the potential causes of this complex issue, in this paper we present a layer-based application framework to discover knowledge of an emergency department system through simulating micro-level behaviors of its components to facilitate a systematic understanding. Finally, case studies are used to demonstrate the potential use of the proposed approach. Results show that the proposed framework can significantly rtheeflect the non-linear association between micro-level behavior and macro-level features.

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Impact of I/O and Data Management in Ensemble Large Scale Climate Forecasting Using EC-Earth3

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Procedia computer Science 2014年 29卷 2370-2379页

作者： Muhammad Asif Andrés Cencerrado Oriol Mula-Valls Domingo Manubens Francisco Doblas-Reyes Ana Cortés Institut Català de Ciències del Clima (IC3) Barcelona Spain Computer Architecture and Operating Systems Department Universitat Autònoma de Barcelona 08193 Bellaterra Barcelona Spain Institució Catalana de Recerca i Estudis Avanc¸ats (ICREA) Barcelona Spain

The EC-Earth climate model is a seamless Earth System Model (ESM) used to carry out climate research in 24 academic institutions and meteorological services from 11 countries in Europe. This model couples several components and it is continuously under development. In this work we present a study regarding the impact of the I/O and data management when using EC-Earth in well-known supercomputing environments. Most large-scale and long-term climate simulators have been developed bearing in mind the paramount importance of its scalability. However, the computational capabilities of the High Performance Computing (HPC) environments increase at so great speed that it is almost impossible to re-implement the whole models so that they are able to exploit efficiently the new features. Therefore, it is necessary to design different strategies to take advantage of them. In this work we present an operational framework to run ensemble simulations in HPC platforms. A set of experiments are presented in order to validate the suitability of this technique. Moreover, the derived impact regarding the I/O and data management aspects is analyzed.

关键词： High Performance Computing Climate Simulation Supercomputing Environments EC-Earth3

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Analysis of the Resilience of an Emergency department: The Case of Accident with Multiple Victims

Analysis of the Resilience of an Emergency Department: The C...

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2023 Winter Simulation Conference, WSC 2023

作者： Rodriguez, Mariela Boixader, Francesc Bruballa, Eva Epelde, Francisco De Giusti, Armando Wong, Alvaro Rexach, Dolores Luque, Emilio National University of Jujuy Faculty of Engineering 10 Italo Palanca Jujuy4600 Argentina Computer Science School Universitat Autonoma de Barcelona Barcelona Sant Cugat del Vallès08174 Spain University Hospital Parc Tauli Universitat Autonoma de Barcelona Internal Medicine Sadabell Barcelona08208 Spain National University of la Plata Faculty of Informatics Calles 50 y 120 Buenos Aires La Plata1900 Argentina Universitat Autonoma de Barcelona Computer Architecture and Operating Systems Department Barcelona Edific Q Campus UAB Bellaterra08193 Spain

ISBN: (纸本)9798350369663

The care of multiple victims such as in natural disasters in an Emergency department is critical. This differs from ordinary care by the number of patients that arrive, their severity and insufficient staff for these events. Designing and simulating this real life scenario will be useful for disaster management decision makers. The objective of this simulation is to model a system with resilience to critical situations. To model the input of this research, we worked with the percentage of patients received by Cauquenes Hospital during the Chilean Earthquake on February 27th, 2010. A comparison of two situations has been carried out: the admission of patients before an earthquake with normal daily attention versus the admission of patients before an earthquake and the activation of the relief chain. The latter situation allows the system to be resilient and adapt quickly to its new reality. © 2023 IEEE.

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Resilience Analysis of an Emergency department in Stressful Situations 11th

Resilience Analysis of an Emergency Department in Stressful ...

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11th Conference on Cloud Computing, Big Data and Emerging Topics, JCC-BD and ET 2023

作者： Rodriguez, Mariela Boixader, Francesc Epelde, Francisco Bruballa, Eva De Giusti, Armando Wong, Alvaro Rexachs, Dolores Luque, Emilio Faculty of Engineering National University of Jujuy San Salvador de Jujuy4600 Argentina Computer Science School Universitat Autonoma de Barcelona Sant Cugat del Vallès Barcelona08174 Spain Consultant Internal Medicine University Hospital Parc Tauli Universitat Autonoma of Barcelona Sadabell Barcelona08208 Spain Faculty of Informatics National University of La Plata Calles 50 y 120 – La Plata Buenos Aires1900 Argentina Computer Architecture and Operating Systems Department Universitat Autónoma of Barcelona Campus UAB Edificio Bellaterra Barcelona08193 Spain

ISBN: (纸本)9783031409417

The performance analysis an Emergency department (ED) is fundamental and necessary to plan the service when it is affected by increasing number of patients due to an external scenario multiple victims from accidents, disasters or catastrophes. In order to perform this analysis, it is important to set up a simulated scenario that allows this study. The proposal is to analyze the ED simulator developed by the HPC4EAS research group at UAB by taking it to a stress situation. The work analyzes key performance indicator (KPI) that measure the performance of an ED (length of stay, waiting queue length, service rate) and make it possible to evaluate the percentage of patients that can be attended without altering the available resources. Study allowed us to determine that the care box (area A - area for the care of seriously ill patients) becomes congested when 40% more patients than usual are received, and the next resource to become congested is the room for the care of milder patients (area B). Analysis that will later allow us to investigate what happens when there is an accident, natural disaster or pandemic. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Accidents

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Analyzing the I/O Patterns of Deep Learning Applications 9th

Analyzing the I/O Patterns of Deep Learning Applications

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9th Conference on Cloud Computing, Big Data and Emerging Topics, JCC-BDandET 2021

作者： Párraga, Edixon León, Betzabeth Bond, Román Encinas, Diego Bezerra, Aprigio Mendez, Sandra Rexachs, Dolores Luque, Emilio Computer Architecture and Operating Systems Department Universitat Autònoma de Barcelona Campus UAB Edifici Q Bellaterra Barcelona08193 Spain SimHPC-TICAPPS Universidad Nacional Arturo Jauretche Florencio Varela1888 Argentina Informatics Research Institute LIDI CIC’s Associated Research Center Universidad Nacional de La Plata La Plata1900 Argentina Departamento de Ciências Exatas e Tecnológicas Universidade Estadual de Santa Cruz Ilhéus Bahia Brazil Barcelona08034 Spain

ISBN: (纸本)9783030848248

A traditional HPC storage system is designed to manage an I/O workload dominated by write operation bursts, mainly for applications carrying out simulations and checkpointing partial results. Currently, this context is more diverse because of artificial intelligence applications’ workload, such as machine learning and deep learning. As ML/DL applications are becoming more compute-intensive, they require the power of HPC systems. However, the HPC I/O system could be a bottleneck to scaling these kind of applications, mainly in the training stage. In this paper, we present a methodology for analyzing the I/O patterns of deep learning applications that allows us to understand the DL applications’ I/O in HPC systems. We have applied our approach to serial and distributed DL codes by using the TensorFlow2 and PyTorch framework for the MNIST and CIFAR-10 datasets. © 2021, Springer Nature Switzerland AG.

关键词： Deep learning

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Assimilation of fire perimeters and satellite detections by minimization of the residual in a fire spread model

arXiv

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arXiv 2018年

作者： Caus, Angel Farguell Haley, James Kochanski, Adam K. Fité, Ana Cortés Mandel, Jan HPCA4SE research group Computer Architecture and Operating Systems Department Universitat Autònoma de Barcelona Bellaterra08193 Spain Department of Mathematical and Statistical Sciences University of Colorado Denver 1201 Larimer St. DenverCO80204 United States Salt Lake CityUt84112-0110 United States

Assimilation of data into a fire-spread model is formulated as an optimization problem. The level set equation, which relates the fire arrival time and the rate of spread, is allowed to be satisfied only approximately, and we minimize a norm of the residual. Previous methods based on modification of the fire arrival time either used an additive correction to the fire arrival time, or made a position correction. Unlike additive fire arrival time corrections, the new method respects the dependence of the fire rate of spread on diurnal changes of fuel moisture and on weather changes, and, unlike position corrections, it respects the dependence of the fire spread on fuels and terrain as well. The method is used to interpolate the fire arrival time between two perimeters by imposing the fire arrival time at the perimeters as constraints.65N55, 35F21 Copyright © 2018, The Authors. All rights reserved.

关键词： Fires

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