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Simulation Winter Conference

作者： Eva Bruballa Manel Taboada Alvaro Wong Dolores Rexachs Emilio Luque Tomàs Cerdà Computer Science School University Autonoma of Barcelona BCN SPAIN Computer Architecture and Operating Systems Department University Autonoma of Barcelona BCN SPAIN

ISBN: (纸本)9781467397414

The saturation of Emergency departments, due to the increasing demand of the service, is a current problem in the healthcare system. We propose an analytical model to obtain information from data obtained through the simulation of a Hospital Emergency department. The model defines how to calculate the theoretical throughput of a particular sanitary staff configuration, that is, the number of patients it can attend per unit time given its composition. This index is a reference to measure indicators concerning to performance and emergency response capacity of the system. The data for the analysis will be generated by the simulation of any possible scenario of the real system, taking into account all valid sanitary staff configurations and different number of patients entering into the emergency service.

关键词： Ad hoc networks Mobile computing

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A Methodology for Selective Protection of Matrix Multiplications: A Diagnostic Coverage and Performance Trade-off for CNNs Executed on GPUs

A Methodology for Selective Protection of Matrix Multiplicat...

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International Conference on System Reliability and Science (ICSRS)

作者： Javier Fernández Irune Agirre Jon Perez-Cerrolaza Jaume Abella Francisco J. Cazorla Ikerlan Technological Research Center Basque Research and Technology Alliance (BRTA) Spain Computer Architecture-Operating Systems Department Barcelona Supercomputing Center Spain

The ability of CNNs to efficiently and accurately perform complex functions, such as object detection, has fostered their adoption in safety-related autonomous systems. These algorithms require high computational performance platforms that exploit high levels of parallelism. The detection, control and mitigation of random errors in these underlying high computational platforms become a must according to functional safety standards. In this paper, we propose protecting, with a catalog of diagnostic techniques, the most computationally expensive operation of the CNNs, the matrix multiplication. However, this protection entails a performance penalty, and the complete CNN protection may be unaffordable for those systems operating with strict real-time constraints. This paper proposes a three-stage methodology to selectively protect CNN layers to achieve the required diagnostic coverage and performance trade-off: i) sensitivity analysis to misclassification per CNN layers using a statistical fault injection campaign, ii) layer-by- layer performance impact and diagnostic coverage analysis, and iii) selective layer protection. Furthermore, we propose a strategy to effectively compute the achievable diagnostic coverage of large matrices implemented on GPUs. Finally, we apply the proposed methodology and strategy in Tiny YOLO-v3, an object detector based on CNNs.

关键词： Sensitivity analysis Autonomous systems Object detection Detectors Parallel processing Real-time systems Safety

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Quantitative Evaluation of Decision Effects in the Management of Emergency department Problems

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Procedia computer Science 2015年 51卷 433-442页

作者： Zhengchun Liu Eduardo Cabrera Manel Taboada Francisco Epelde Dolores Rexachs Emilio Luque Computer Architecture & Operating Systems University Autonoma of Barcelona(UAB) Spain Institute of Advanced Research Computing Durham University UK Tomas Cerda Computer Science School (UAB) Spain Medicine Department Hospital Universitari Parc Tauli (UAB) Spain

Due to the complexity and crucial role of an Emergency department(ED) in the healthcare system. The ability to more accurately represent, simulate and predict performance of ED will be invaluable for decision makers to solve management problems. One way to realize this requirement is by modeling and simulating the emergency department, the objective of this research is to design a simulator, in order to better understand the bottleneck of ED performance and provide ability to predict such performance on defined condition. Agent-based modeling approach was used to model the healthcare staff, patient and physical resources in ED. This agent-based simulator provides the advantage of knowing the behavior of an ED system from the micro-level interactions among its components. The model was built in collaboration with healthcare staff in a typical ED and has been implemented and verified in a Netlogo modeling environment. Case studies are provided to present some capabilities of the simulator in quantitive analysis ED behavior and supporting decision making. Because of the complexity of the system, high performance computing technology was used to increase the number of studied scenarios and reduce execution time.

关键词： Emergency department Agent-based Modeling Complex System Decision Support

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Data resolution effects on a coupled data driven system for forest fire propagation prediction

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Procedia computer Science 2017年 108卷 1562-1571页

作者： À. Farguell A. Cortés T. Margalef J.R. Miro J. Mercader HPCA4SE research group Computer Architecture and Operating Systems department Universitat Autònoma de Barcelona 08193 Bellaterra Spain Servei Meteorològic de Catalunya 08029 Barcelona Spain

Every year, thousands of forest hectares are burned worldwide, causing important consequences on the atmosphere, biodiversity and economy. Proper prediction of the fire evolution allows to manage the fire fighting equipment properly. Therefore, it is crucial to use reliable and fast simulations in order to predict the evolution of the fire. WRF-SFIRE is a wildland fire simulator, which couples a meteorological model called Weather Research and Forecasting Model (WRF) and a forest fire simulator, SFIRE reproducing the interaction between the propagation of the fire and the atmosphere evolution. The mesh resolution used to solve the atmosphere evolution has a deep impact in the prediction of small scale meteorological effects. At the same time, the ability of introducing these small scale meteorological events into the forest fire simulation implies enhancements in the quality of the data that drives the simulation. Therefore, better fire propagation predictions are obtained. However, this improvement can be affected by the instability of the problem to be solved. This paper states an accuracy study changing the mesh resolution when running WRF-SFIRE using as example a real case that took place in Catalonia (northeast of Spain) in 2005.

关键词： WRF-SFIRE Accuracy Data resolution Data driven

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Reducing Data Uncertainty in Surface Meteorology Using Data Assimilation: A Comparison Study

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Procedia computer Science 2016年 80卷 1846-1855页

作者： A. Farguell J. Moré A. Cortés J.R. Miró T. Margalef V. Altava HPCA4SE research group Computer Architecture and Operating Systems department Universitat Autònoma de Barcelona 08193 Bellaterra Spain Servei Meteorològic de Catalunya 08029 Barcelona Spain

Data assimilation in weather forecasting is a well-known technique used to obtain an improved estimation of the current state of the atmosphere (analysis). The Meteorological Service of Catalunya (SMC) is seeking for a real time high resolution analysis of surface parameters over Catalonia (north-east of Spain), in order to know the current weather conditions at any point of that region. For this purpose, a comparative study among several data assimilation experiments based on LAPS (Local Analysis and Prediction System) and STMAS (Space-Time Multiscale Analysis System) and multi-regression technique designed at SMC, has been performed to determine which one delivers best results. The comparison has been done using as true state independent observational data provided by the Spanish Meteorological State Agency (Agencia Estatal de METeorologia, AEMET). The results show that the multi-regression technique provides more accurate analyses of temperature and relative humidity than the LAPS/STMAS experiments, mainly due to the fact that multi-regression methodology only uses observations and consequently the model biases are avoided.

关键词： Data Uncertainty Meteorology Data Assimilation Numerical Methods

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AGENT-BASED MODEL FOR TUMOR-ANALYSIS USING PYTHON+MESA

arXiv

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arXiv 2019年

作者： Tashakor, Ghazal Suppi, Remo Universitat Autònoma de Barcelona Department Computer Architecture & Operating Systems School of Engineering Campus Bellaterra Cerdanyola del Vallès Barcelona08193 Spain

The potential power provided and possibilities presented by computation graphs has steered most of the available modeling techniques to re-implementing, utilization and including the complex nature of System Biology (SB). To model the dynamics of cellular population, we need to study a plethora of scenarios ranging from cell differentiation to tumor growth and *** and verification of a model in research means running the model multiple times with different or in some cases identical parameters, to see how the model interacts and if some of the outputs would change regarding different *** this paper, we will describe the development and implementation of a new agent-based model using Python. The model can be executed using a development environment (based on Mesa, and extremely simplified for convenience) with different parameters. The result is collecting large sets of data, which will allow an in-depth analysis in the microenvironment of the tumor by the means of network analysis. Copyright © 2019, The Authors. All rights reserved.

关键词： Python

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Performance models for dynamic tuning of parallel applications on Computational Grids

Performance models for dynamic tuning of parallel applicatio...

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IEEE International Conference on Cluster Computing

作者： Genaro Costa Josep Jorba Anna Morajko Tomas Margalef Emilio Luque Computer Architecture and Operating Systems Department Universitat Autònoma Barcelona Bellaterra Spain Estudis d'Informatica Multimedia i Telecomunicacions Universitat Oberta de Catalunya Barcelona Spain

Performance is a main issue in parallel application development. Dynamic tuning is a technique that acts over application parameters to raise execution performance indexes. To perform that, it is necessary to collect measurements, analyze application behavior using a performance model and carry out tuning actions. Computational Grids present proclivity for dynamic changes on their features during application execution. Thus, dynamic tuning tools are indispensable to reach the expected performance indexes on those environments. A particular problem which provokes performance bottlenecks is the load distribution in master/worker applications. This paper addresses the performance modeling of such applications on Computational Grids for the perspective of dynamic tuning. It is inferred that grain size and number of workers are critical parameters to reduce execution time while raising the efficiency of resources usage. A heuristic to dynamically tune granularity and number of workers is proposed. The experimental simulated results of a matrix multiplication application in a heterogeneous Grid environment are shown.

关键词： Tuning Program processors Grain size Performance analysis Bandwidth Computational modeling Equations

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Virtual Clinical Trials: A tool for the Study of Transmission of Nosocomial Infections

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Procedia computer Science 2017年 108卷 109-118页

作者： Cecilia Jaramillo Dolores Rexachs Francisco Epelde Emilio Luque Department of Computer Architecture & Operating Systems Universitat Autonoma de Barcelona Bellaterra 08193 Barcelona Spain Short Stay Unit Emergency Service Hospital Universitari Parc Tauli Universitat Autonoma de Barcelona Sabadell 08208 Barcelona Spain

A clinical trial is a study designed to demonstrate the efficacy and safety of a drug, procedure, medical device, or diagnostic test. Since clinical trials involve research in humans, they must be carefully designed and must comply strictly with a set of ethical conditions. Logistical disadvantages, ethical constraints, costs and high execution times could have a negative impact on the execution of the clinical trial. This article proposes the use of a simulation tool, the MRSA-T-Simulator, to design and perform “virtual clinical trials” for the purpose of studying MRSA contact transmission among hospitalized patients. The main advantage of the simulator is its flexibility when it comes to configuring the patient population, healthcare staff and the simulation environment.

关键词： Simulation Agent Based Model Clinical Trials Nosocomial Infection

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Simulation and Big Data: A Way to Discover Unusual Knowledge in Emergency departments: Work-in-Progress Paper

Simulation and Big Data: A Way to Discover Unusual Knowledge...

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International Conference on Future Internet of Things and Cloud (FiCloud)

作者： Eva Bruballa Manel Taboada Eduardo Cabrera Dolores Rexachs Emilio Luque Tomàs Cerdà Computer Science School Universitat Autònoma de Barcelona (UAB) Barcelona Spain Computer Architecture and Operating Systems Department Universitat Autònoma de Barcelona (UAB) Barcelona Spain

Here a work in progress is reported on within research that aims to obtain knowledge about variables which may influence a hospital emergency department's performance and quality of service. Knowledge discovery will be achieved through the analysis of intensive data generated by the simulation of any possible scenario in the real system. The challenge is to provide knowledge of critical, non-usual or extreme situations. Simulation is the only way to obtain information about these kinds of situations, as it is not possible to test such scenarios in the real system. We show how simulation of the real system through advanced computing is a source of big data, as it allows rapid and massive data generation. The potential of high performance computing makes it possible to generate a very large amount of data within a reasonable time, store this data, then process and analyze it to obtain knowledge. We describe the methodology proposed for this goal, which is based on the use of the simulator as a sensor of the real system, and so as the main source of data. The application of data mining techniques will open the doors to knowledge. To verify that the proposed methodology works, we propose a case study in which the aim is to obtain knowledge from a set of data already available, obtained from the simulation of a reduced set of scenarios of the real system.

关键词： Data models Data mining Computational modeling Hospitals Analytical models Big data

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Towards a Dynamic Data Driven Wildfire Behavior Prediction System at European Level

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Procedia computer Science 2014年 29卷 1216-1226页

作者： Tomàs Artés Andrés Cencerrado Ana Cortés Tomàs Margalef Darío Rodríguez-Aseretto Thomas Petroliagkis Jesús San-Miguel-Ayanz Computer Architecture and Operating Systems department Universitat Autònoma de Barcelona 08193 Bellaterra Spain European Commission Joint Research CentreInstitute for Environment and Sustainability Via E. Fermi 2749 I-21027 Ispra (VA) Italy

Southern European countries are severally affected by forest fires every year, which lead to very large environmental damages and great economic investments to recover affected areas. All affected countries invest lots of resources to minimize fire damages. Emerging technologies are used to help wildfire analysts determine fire behavior and spread aiming at a more efficient use of resources in fire fighting. In this case of trans-boundary fires, the European Forest Fire Information System (EFFIS) works as a complementary system to a national and regional systems in the countries, providing information required for international collaboration on forest fires prevention and fighting. In this work, we describe a way of exploiting all the available information in the system to feed a Dynamic Data Driven wildfire behavior prediction model that can deliver results to support operational decision. The model is able to calibrate the unknown parameters based on the real observed data, such as wind condition and fuel moisture using a steering loop. Since this process is computational intensive, we exploit multi-core platforms using a hybrid MPI-OpenMP programming paradigm.

关键词： DDDAS Input Data Uncertainty High Performance Computing Calibration Hybrid MPI-OpenMP Applications Evolutionary Computation Forest Fires EFFIS

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