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arXiv 2019年

作者： Tashakor, Ghazal Suppi, Remo Department Computer Architecture & Operating Systems Universitat Autnoma de Barcelona Barcelona Spain

This paper deals with the cellular biological network analysis of the tumor-growth model, consisting of multiple spaces and time scales. In this paper, we present a model in graph simulation using ABM for tumor growth. In particular, we propose a graph agent-based modeling and simulation system in the format of tumor growth scenario for evolving analysis. To manage cellular biological network analysis, we developed a workflow that allows us to estimate the tumor model and the complexity of the evolving behavior in a principled manner. By developing the model using Python, which has enabled us to run the model multiple times (more than what is possible by conventional means) to generate a large amount of data, we have succeeded in getting deep in to the micro-environment of the tumor, employing network analysis. Combining agent-based modeling with graph-based modeling to simulate the structure, dynamics, and functions of complex networks is exclusively important for biological systems with a large number of open parameters, e.g., epidemic models of disease spreading or cancer. Extracting data from evolutionary directed graphs and a set of centrality algorithms helps us to tackle the problems of pathway analysis and to develop the ability to predict, control, and design the function of metabolisms. Reproducing and performing complex parametric simulations a known phenomenon at a sufficient level of detail for computational biology could be an impressive achievement for fast analysis purposes in clinics, both on the predictive diagnostic and therapeutic side. Copyright © 2019, The Authors. All rights reserved.

关键词： Autonomous agents

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Agent-model based on flame GPU for assessing pupal productivity of the transmitting vector of Aedes aegypti infectious diseases 18

Agent-model based on flame GPU for assessing pupal productiv...

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18th International Conference on Modeling and Applied Simulation, MAS 2019

作者： De Oca, Erica Montes Suppi, Remo De Giusti, Laura Naiouf, Marcelo La Plata Buenos Aires Argentina Universitat Autónoma de Barcelona Department of Computer Architecture and Operating Systems School of Engineering Campus Bellaterra Cerdanyola del Vallès Barcelona08193 Spain

ISBN: (纸本)9788885741300

Dengue, Zika and chikungunya are among the infectious diseases that have emerged in recent years. The common denominator to these three is their transmitting vector: the Aedes aegypti mosquito. Due to sanitary reasons, it is highly important that the vector for transmitting these diseases be controlled through the implementation of strategies specifically designed for each situation. In this article, the creation of an agent-based simulation model that allows assessing control strategies and policies through parallel computing on GPU is proposed. High Performance Computing is necessary due to the large volume of data that has to be processed (hundreds of thousands of agents) to obtain results within an acceptable time frame. Model validation was done at small scale with an analogous model on CPU and NetLogo and using data from an real system. In this article, the implementation, scalability and potential of this model as decision support system (DSS) are presented. © Modeling and Applied Simulation, MAS *** Rights Reserved.

关键词： Graphics processing unit

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GPU-Accelerated Real-Time Stixel Computation

GPU-Accelerated Real-Time Stixel Computation

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IEEE Workshop on Applications of computer Vision (WACV)

作者： Daniel Hernandez-Juarez Antonio Espinosa Juan C. Moure David Vázquez Antonio M. López Computer Architecture and Operating Systems Dpt. UAB Computer Vision Center and Computer Science Dpt. UAB

ISBN: (纸本)9781509048236

The Stixel World is a medium-level, compact representation of road scenes that abstracts millions of disparity pixels into hundreds or thousands of stixels. The goal of this work is to implement and evaluate a complete multistixel estimation pipeline on an embedded, energy-efficient, GPU-accelerated device. This work presents a full GPUaccelerated implementation of stixel estimation that produces reliable results at 26 frames per second (real-time) on the Tegra X1 for disparity images of 1024×440 pixels and stixel widths of 5 pixels, and achieves more than 400 frames per second on a high-end Titan X GPU card.

关键词： Dynamic programming Image segmentation Estimation Computational modeling Real-time systems Optimization Roads

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Wildland fire propagation danger maps based on factorial experimentation

Wildland fire propagation danger maps based on factorial exp...

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2nd International ICSC Symposium on Information Technologies in Environmental Engineering, ITEE 2005

作者： Bianchini, Germán Cortés, Ana Margalef, Tomàs Luque, Emilio Chuvieco, Emilio Camia, Andrea Computer Architecture and Operating Systems Department Universitat Autònoma de Barcelona Spain Department of Geography Universidad de Alcalá Spain European Commission - DG Joint Research Centre Institute for Environment and Sustainability Spain

ISBN: (纸本)3832243623

Wildland fire-risk assessment is a very significant issue. This risk assessment is usually based on ignition probability due to meteorological or human factors, but it does not usually consider propagation danger when a wildland fire has started. To evaluate propagation danger, it is necessary to apply some propagation model and simulate the behaviour of the fireline. However, this propagation danger must be evaluated considering many different possible scenarios. Therefore, the amount of simulations that must be carried out is enormous and it is necessary to apply high-performance computing techniques to make the methodology feasible. In this paper, a method for creating propagation danger maps based on factorial experimentation is described. The methodology was applied at a southern Europe scale during the 2004 summer season.

关键词： Risk assessment

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Saving Time in a Program Robustness Evaluation

Saving Time in a Program Robustness Evaluation

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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Joao Gramacho Dolores Rexachs Emilio Luque Computer Architecture and Operating Systems Department Universitat Autònoma de Barcelona Barcelona Spain

ISBN: (纸本)9781479914449

The risk of having a program execution corrupted by transient faults is growing as computer processors are using more transistors, are becoming denser and are operating at lower voltages. This risk is multiplied when we take into account High Performance Computing with its hundreds or thousands of processors working together to solve a single problem. To evaluate how program executions behave in presence of transient faults we have proposed the concept of robustness against transient faults. This concept can be used to determine the more significant parts of a program with respect to the risk of misbehavior by transient faults for further study of improvement. The robustness concept can also be used as a metric to compare different approaches applied to a program to make it less likely of producing corrupted results. In this work we present why and how is possible to simplify a fraction of a program's robustness by taking into account the repetition of sequences of instructions. The simplified analysis obtains the exact same result as a full program robustness evaluation (exhaustively and without estimations). By simplifying the analysis we were able to reduce in up to 192 times our previously published robustness analysis time and also were able to evaluate larger programs in feasible time (unimaginable by using executions in a fault injection capable environment).

关键词： Robustness Transient analysis Registers Program processors computer architecture Compression algorithms Absorption

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Improving single-thread fetch performance on a multithreaded processor

Improving single-thread fetch performance on a multithreaded...

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Euromicro Symposium on Digital System Design

作者： J.C. Moure R.B. Garcia D.I. Rexachs E. Luque Computer Architecture and Operating Systems Group Universidad Autónoma de Barcelona Barcelona Spain

Multithreaded processors, by simultaneously using both the thread-level parallelism and the instruction-level parallelism of applications, achieve larger instruction per cycle rate than single-thread processors. On a multi-thread workload, a clustered organization maximizes performances. On a single-thread workload, however, all but one of the clusters are idle, degrading single-thread performance significantly. Using a clustered multi-thread performance as a baseline, we propose and analyze several mechanisms and policies to improve single-thread execution exploiting the existing hardware without a significant multi-thread performance loss. We focus on the fetch unit, which is maybe the most performance-critical stage. Essentially, we analyze three ways of exploiting the idle fetch clusters: allowing a single thread accessing its neighbor clusters, use the idle fetch clusters to provide multiple-path execution, or use them to widen the effective single-three fetch block.

关键词： Yarn Parallel processing Performance analysis Performance loss Bandwidth Degradation Surface-mount technology computer architecture operating systems Application software

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Relieving the Effects of Uncertainty in Forest Fire Spread Prediction by Hybrid MPI-OpenMP Parallel Strategies

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Procedia computer Science 2013年 18卷 2278-2287页

作者： Tomàs Artés Andrés Cencerrado Ana Cortés Tomàs Margalef Computer Architecture and Operating Systems Department Escola d’Enginyeria Universitat Auto‘noma de Barcelona Campus UAB Bellaterra 08193 Spain

The accurate prediction of forest fire propagation is a crucial issue to minimize its effects. Several models have been developed to determine the forest fire propagation. Simulators implementing such models require diverse input parameters to deliver predictions about fire propagation. However, the data describing the actual scenario where the fire is taking place are usually subject to high levels of uncertainty. The input-data uncertainty represents a serious drawback for the correctness of the prediction. So, a two-stage methodol- ogy was developed to calibrate the input parameters in an adjustment stage so that the calibrated parameters are used in the prediction stage to improve the quality of the predictions. This way, we relieve the effects of such uncertainty. In this work, we take advantage of this two stage methodology applying Genetic Algorithms as the calibration technique. However, the use of Genetic Algorithms require the execution of many simulations. This fact, added to the eventual long executions of the underlying simulator (due to its inherent complexity), implies to deal with another serious problem: the time needed to deliver the predictions. To be useful, the prediction must be provided much faster than real time. So, it is necessary to exploit all available computing resources. In this work, we present a two-stage forest fire spread prediction hybrid MPI-OpenMP application based on the Master- Worker paradigm and the parallelization of the FARSITE simulator in order to minimize the response time. The results as regards the enhancement in the quality of the predictions are reported, as well as the results regarding the time saving obtained by this hybrid application.

关键词： Input Data Uncertainty High Performance Computing Prediction Framework OpenMP MPI Hybrid Applications Evolutionary Computation Forest Fires

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Coupling Wind Dynamics into a DDDAS Forest Fire Propagation Prediction System

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Procedia computer Science 2012年 9卷 1110-1118页

作者： Carlos Brun Tom‘as Artées Tom‘as Margalef Ana Cortées Computer Architecture and Operating Systems Department Escola d’Enginyeria Universitat Aut‘onoma de Barcelona Campus UAB Bellaterra 08193 Spain

Natural hazards are significant problems that every year cause important loses around the world. A good prediction of the behavior of the hazards is a crucial issue to fight against them and to minimize the damages. The models that represent these phenomena need several input parameters and in many cases, such parameters are diffcult to know or even to estimate in a real scenario. So, a methodology based on the DDDAS paradigm was developed to calibrate the input parameters according to real observations of the behavior and evolution of the hazard. Such calibrated parameters are then used to provide an improved prediction for the next time interval. This methodology was tested on Forest Fire Propagation Prediction with significant results. The developed methodology takes the fire behavior and propagation during a time interval and then searches for the values of the input parameters that best reproduce the propagation of the fire during that interval. Several Artificial Intelligence (AI) methods were applied to carry out this search as fast as possible. The values of the parameters that best reproduce the behavior of the fire were then used as input parameters to predict the propagation during the next time interval. These parameters were considered constant during both time intervals and a single value for each parameter was used for the calibrating process and for the prediction stage. This methodology fits on the DDDAS paradigm since the prediction is dynamically driven by the system evolution. However, there are several parameters that are not constant through time, but they may vary dynamically. In the case of forest fires, a typical example is the wind. In some cases, when the time interval is short an average value for the wind can be a feasible value, but when the time interval is longer, in most cases, a single value cannot represent the variability of the wind. We can estimate wind behavior applying some complementary model. In this work, we are going a ste

关键词： fire prediction DDDAS calibration wind simulation fire spread genetic algorithm

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How to Scale Dynamic Tuning to Large Parallel Applications

How to Scale Dynamic Tuning to Large Parallel Applications

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IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Andrea Martínez Anna Sikora Eduardo César Joan Sorribes Computer Architecture and Operating Systems Department Universitat Autònoma de Barcelona Bellaterra Barcelona Spain

ISBN: (纸本)9781479913725

Current performance analysis and tuning tools must be able to improve the performance of large-scale parallel applications. To be effective, such analysis and tuning tools must be scalable and be able to manage the dynamic behaviour of parallel applications. This work presents a scalable solution for dynamic tuning. This approach is based on a hierarchical performance analysis architecture that uses a novel information abstraction mechanism to solve local and global performance problems. We have developed a prototype implementation of the proposed analysis architecture making use of the MRNet framework. Scalability experiments have been performed using this prototype with up to 6400 application tasks. The results obtained show that the proposed analysis architecture will provide the scalability required to carry out dynamic tuning of large-scale parallel applications.

关键词： Tuning Instruments Analytical models Monitoring Pipelines Scalability Performance analysis

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Coupling Diagnostic and Prognostic Models to a Dynamic Data Driven Forest Fire Spread Prediction System

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Procedia computer Science 2013年 18卷 1851-1860页

作者： Carlos Brun Tomàs Margalef Ana Cortés Computer Architecture and Operating Systems Department Escola d’Enginyeria Universitat Autònoma de Barcelona Campus UAB Bellaterra 08193 Spain

Forest fires cause important losses around the world every year. A good prediction of fire propagation is a crucial point to minimize the devastating effects of these hazards. Several models that represent this phenomenon and provide a prediction of its spread have been developed. These models need input parameters which are usually difficult to know or even estimate. A two- stage prediction methodology was proposed to improve the quality of these parameters. In this methodology, such parameters are calibrated according to real observations and then, used in the prediction step. However, there are several parameters, which are not uniform along the map, but vary according to the topography of the terrain. Besides, these parameters are not constant along time but they are strongly dynamic. In such cases, it is necessary to introduce complementary models that overcome both restrictions. In the former case, the need of a spatial distribution model of a given variable is needed to be able to provide a spatial distribution for a given variable along the whole terrain by starting from the measured values of that parameter in certain points of the terrain. In the case of time variability, a complementary model such as weather forecasting model, could enable the capability of dealing with dynamic behavior of these parameters along time. In this paper, we describe an enhanced two-stage prediction scheme, where both type of complementary models a wind field model and a weather prediction model are coupled to the prediction scheme by enabling the system to dynamically adapts to complex terrains and dynamic conditions.

关键词： Forest fire prediction calibration models DDDAS wind field meteorology parameters tuning genetic algorithm

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