Reproducing crowd turbulence with Verlet integration and agent modeling

High density crowds are risk situations that already had turned some events into disasters. There are particular emerging events in these crowds that had led to dangerous situations. One important phenomenon is named “crowd turbulence”. It is produced by a propagation of forces among the mass and has already been the cause of several tragedies. We present a new approach to its representation and understanding by a hybrid model composed by two parts: physical interaction among the agents, and psychological factors that produce voluntary interactions. The focus of the present work is contributing with a model able to reproduce such events in a computationally efficient way on SIMD architecture

ABM simulation focused on urban mobility

The objectives of this research is to solve, through high-performance simulation, different mobility problems in cities with mixed traffic (public and private transport, emergencies, bicycles, scooters). To achieve these objectives, the research is oriented to develop new ABM models (Agent Based Models), integrated with Geographic Information Systems (GIS) in order to provide answers to different situations and mobility scenarios in big cities. We want to analyze different episodes and strategies (real or possible) to solve questions based on 'What if?' with variables such as mixed traffic, bicycles exclusive lanes, reduction of private vehicles lanes, among others. This work shows the first phase of ongoing research focused on the city of Barcelona, but the proposed methodology and models can be quickly extended to other cities. For this, we work with data captured in real traffic analysis processed with vehicle recognition algorithms based on AI (artificial intelligence) and the results are used as the basis for the ABM model based on GIS. The simulation is carried out by integrating initial real data with those generated by the simulation in order to analyze the mobility and their interactions.Instituto de Investigación en Informátic

R/parallel – speeding up bioinformatics analysis with R

Background: R is the preferred tool for statistical analysis of many bioinformaticians due in part to the increasing number of freely available analytical methods. Such methods can be quickly reused and adapted to each particular experiment. However, in experiments where large amounts of data are generated, for example using high-throughput screening devices, the processing time required to analyze data is often quite long. A solution to reduce the processing time is the use of parallel computing technologies. Because R does not support parallel computations, several tools have been developed to enable such technologies. However, these tools require multiple modications to the way R programs are usually written or run. Although these tools can finally speed up the calculations, the time, skills and additional resources required to use them are an obstacle for most bioinformaticians. Results: We have designed and implemented an R add-on package, R/parallel, that extends R by adding user-friendly parallel computing capabilities. With R/parallel any bioinformatician can now easily automate the parallel execution of loops and benefit from the multicore processor power of today's desktop computers. Using a single and simple function, R/parallel can be integrated directly with other existing R packages. With no need to change the implemented algorithms, the processing time can be approximately reduced N-fold, N being the number of available processor cores. Conclusion: R/parallel saves bioinformaticians time in their daily tasks of analyzing experimental data. It achieves this objective on two fronts: first, by reducing development time of parallel programs by avoiding reimplementation of existing methods and second, by reducing processing time by speeding up computations on current desktop computers. Future work is focused on extending the envelope of R/parallel by interconnecting and aggregating the power of several computers, both existing office computers and computing clusters.

High Performance Computing for Tumor Propagation Agent-based Model

Agent based modeling (ABM) and High Performance Computing (HPC) techniques are very popular in investigation and understanding cellular and molecular systems. The complex nature of these systems and the demand for emulation and comprehension at different levels in these models creates the expectation for new effective simulation strategies and tools. The present paper peruses the foresaid demands and the approaches for developing simulation in tumor model and its interactions using ABM and HPC. ABM allows the analysis of the actions and interactions of autonomous agents (cells in this case) to evaluate their effects on the system as a whole in order to re-create and predict the appearance of a complex phenomenon. This is a parametric model and it is necessary to explore the data model space to determine which combinations of adjustments cause the behaviors which are of interest. In this case, HPC is a useful tool to perform experiments in acceptable time.XVIII Workshop de Procesamiento Distribuido y Paralelo (WPDP).Red de Universidades con Carreras en Informática (RedUNCI

Distributed Simulation of Large-Scale Individual Oriented Models

The distributed simulation for high performance models has been carried-out into a very useful and low-cost tool. In the present work their application to an individual oriented model (Fish Schools) is analyzed. To do this, it was analyzed different alternatives for this type of simulation and their application to obtain performance and model scalability using different implementation. Thus, two distributed simulator have been developed based on PVM and MPI communication libraries. This paper resumes the advantages and drawbacks of each implementation and some conclusions about the distributed simulation for this type of models are extracted. Moreover, visualization aspects and the developed infrastructure based on OpenGl are described.Facultad de Informátic

Exploiting Traffic Balancing and Multicast Efficiency in Distributed Video-on-Demand Architectures

Distributed Video-on-Demand (DVoD) systems are proposed as a solution to the limited streaming capacity and null scalability of centralized systems. In a previous work, we proposed a fully distributed large-scale VoD architecture, called Double P-Tree, which has shown itself to be a good approach to the design of flexible and scalable DVoD systems. In this paper, we present relevant design aspects related to video mapping and traffic balancing in order to improve Double P-Tree architecture performance. Our simulation results demonstrate that these techniques yield a more efficient system and considerably increase its streaming capacity. The results also show the crucial importance of topology connectivity in improving multicasting performance in DVoD systems. Finally, a comparison among several DVoD architectures was performed using simulation, and the results show that the Double P-Tree architecture incorporating mapping and load balancing policies outperforms similar DVoD architectures.This work was supported by the MCyT-Spain under contract TIC 2001-2592 and partially supported by the Generalitat de Catalunya- Grup de Recerca Consolidat 2001SGR-00218

Un planificador de canales lógicos para un servidor de VoD en Internet

La mayoría de los sistemas de Vídeo bajo Demanda (VoD, Video on Demand) fueron diseñados para trabajar en redes dedicadas. Sin embargo, hay algunos sistemas que proveen servicio de VoD en redes de mejor esfuerzo y no dedicadas, pero ellos adaptan la calidad de la media de acuerdo al ancho de banda disponible de la red. Nuestras actividades de investigación se enfocan en sistemas de VoD con alta calidad de servicio en redes no dedicadas. Actualmente, hemos diseñado y desarrollado un servidor de VoD, que incluye un Planificador del Tráfico de Red (NTS) encargado de la gestión y transmisión de los datos por la red, y un Planificador de Canales Lógicos (LCS) que planifica la entrega de los vídeos a los diversos clientes. El componente NTS es el encargado de informar al LCS sobre el estado de la comunicación con cada uno de los clientes para que éste pueda planificar la entrega de los vídeos con conocimiento del estado de la red. El presente trabajo describe el componente LCS y los resultados de su integración con el NTS, demostrando el correcto funcionamiento y viabilidad para trabajar en una red de condiciones variables como la red Internet.Most of the Video on Demand (VoD) systems were designed to work in dedicated networks. However, there are some approaches that provide VoD service in nondedicated and best effort networks. In such case, they adapt the media’s quality according to the available network bandwidth. Our research focus on VoD systems with high quality service over nondedicated networks. Currently, we have designed and developed a VoD server that includes a Network Traffic Scheduler (NTS) that is in charge to manage and transmit the data by the network, and a Logical Channels Scheduler (LCS) that schedule the videos’ delivery to the different clients. The NTS component is in charge to inform the LCS of the communication state with each client in order to let LCS make the videos’ delivery schedule with knowledge of the network state. The present work describes the LCS component and the results of the integration with the NTS, demonstrating the well function and viability to work over networks of variable conditions such as the Internet.I Workshop de Arquitecturas, Redes y Sistemas Operativos (WARSO)Red de Universidades con Carreras en Informática (RedUNCI

Simulación distribuida de modelos orientados al individuo utilizando MPI

El presente trabajo muestra los resultados obtenidos en el área de Simulación Distribuida de Eventos Discretos (PDES) para la solución de problemas basados en modelos orientados al individuo (IoM). Estos modelos son ampliamente utilizados en sistemas ecológicos y generan mejores resultados que los modelos convencionales pero, por otro lado, tienen el inconveniente que necesitan grandes capacidades de cómputo para la simulación de sistemas medianos o grandes (centenas o miles de individuos). La simulación distribuida puede ser utilizada como una herramienta útil para su simulación ya que permite emplear agrupaciones (clusters) de estaciones de trabajo de bajo costo como plataforma virtual de cómputo. Esto permite reducir el tiempo de simulación o, dado el incremento de potencia de cálculo, poder simular modelos más grandes y/o complejos. En el presente trabajo se analizan los conceptos teóricos involucrados, se describe el simulador diseñado y desarrollado bajo MPI (Message Passing Interface) y muestran los experimentos realizados para su validación y verificación.Eje: IV - Workshop de procesamiento distribuido y paralel