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Grid Computing allows scientists and engineers to run compute intensive experiments that were unfeasible not so long ago. On the downside, for users not proficient in distributed technologies, programming for Grids is difficult, tedious, time-consuming and error-prone. Then, disciplinary users typically waste precious time that could be instead invested into analyzing results. In a previous paper, we introduced BYG (Mateos et al., 2011) [28], a Java-based software that automatically parallelizes sequential applications by directly modifying their compiled codes. In addition, BYG is designed to harness Grid resources by reusing existing Grid platforms and schedulers. In its current shape, however, BYG lacks support for some state-of-the-art Grid schedulers and mechanisms for introducing application-dependent optimizations to parallelized codes. In this paper, we present several extensions to BYG aimed at overcoming these problems and thus improving its applicability and delivered efficiency. We also report experiments by using traditional computational kernels and real-life applications to show the positive practical implications of the proposed extensions. Fil: Mateos Diaz, Cristian Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina Fil: Zunino Suarez, Alejandro Octavio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina Fil: Hirsch Jofré, Matías Eberardo. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Fernández, Mariano. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas; Argentina

Computational Grids deliver the necessary computational infrastructure to perform resource-intensive computations such as the ones that solve the problems scientists are facing today. Exploiting Computational Grids comes at the expense of explicitly adapting the ordinary software implementing scientific problems to take advantage of Grid resources, which unavoidably requires knowledge on Grid programming. The recent notion of "gridifying" ordinary applications, which is based on semi-automatically deriving a Grid-aware version from the compiled code of a sequential application, promises users to be relieved from the requirement of manual usage of Grid APIs within their source codes. In this paper, we describe a novel gridification tool that allows users to easily parallelize Java applications on Grids. Extensive experiments with two real-world applications - ray tracing and sequence alignment - suggest that our approach provides a convenient balance between ease of gridification and Grid resource exploitation compared to manually using Grid APIs for gridifying ordinary applications. Fil: Mateos Diaz, Cristian Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina Fil: Zunino Suarez, Alejandro Octavio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina Fil: Hirsch Jofré, Matías Eberardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires; Argentina Fil: Fernández, Mariano. Universidad Nacional del Centro de la Provincia de Buenos Aires; Argentina Fil: Campo, Marcelo Ricardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina

The increasing interest in larger spatial and temporal scale models and high resolution input data processing comes at a price of higher computational demand. This price is evidently even higher when common modeling routines such as calibration and uncertainty analysis are involved. Likewise, methods and techniques for reducing computation time in large scale socio-environmental modeling software is growing. Recent advancements in distributed computing such as Grid infrastructure have provided further opportunity to this effort. In the interest of gaining computational efficiency, we developed generic tools and techniques for enabling the Soil and Water Assessment Tool (SWAT) model application to run on the EGEE (Enabling Grids for E-science projects in Europe) Grid. Various program components/scripts were written to split a large scale hydrological model of the Soil and Water Assessment Tool (SWAT), to submit the split models to the Grid, and to collect and merge results into single output format. A three-step procedure was applied to take advantage of the Grid. Firstly, a python script was run in order to split the SWAT model into several sub-models. Then, individual sub-models were submitted in parallel for execution on the Grid. Finally, the outputs of the sub-basins were collected and the reach routing process was performed with another script executing a modified SWAT program. We conducted experimental simulations with multiple temporal and spatial scale hydrological models on the Grid infrastructure. Results showed that, in spite of computing overheads, parallel computation of socio-environmental models on the Grid is beneficial for model applications especially with large spatial and temporal scales. In the end, we conclude by recommending methods for further reducing computational overheads while running large scale model applications on the Grid.

In the last 10 years, a new way of doing science is spreading in the world thank to the development of virtual research communities across many geographic and administrative boundaries. A virtual research community is a widely dispersed group of researchers and associated scientific instruments working together in a common virtual environment. This new kind of scientific environment, usually addressed as a "collaboratory", is based on the availability of high-speed networks and broadband access, advanced virtual tools and Grid-middleware technologies which, altogether, are the elements of the e-Infrastructures. The European Commission has heavily invested in promoting this new way of collaboration among scientists funding several international projects with the aim of creating e-Infrastructures to enable the European Research Area and connect the European researchers with their colleagues based in Africa, Asia and Latin America. In this paper we describe the actual status of these e-Infrastructures and present a complete picture of the virtual research communities currently using them. Information on the scientific domains and on the applications supported are provided together with their geographic distribution. © 2011 Springer Science+Business Media B.V.

Resource-intensive agricultural simulation applications have increased the need for gridification tools –i.e., software to transform and scale up the applications using Grid infrastructures–. Previous research has proposed JASAG, a generic gridification tool for agricultural applications, through which the performance of a whole-farm simulation application called Simugan improved considerably. However, JASAG still lacks proper support for efficiently exploiting Grid storage resources, causing significant delays for assembling and summarizing the generated data. In this application note, two different data processing techniques in the context of JASAG are presented to tackle this problem. Simugan was again employed to validate the benefits of these techniques. Experiments using data processing techniques show that the execution time of Simugan was accelerated by a factor of up to 34.34. Fil: Longo, Mathias. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina Fil: Arroqui, Mauricio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Ministerio de Ciencia. Tecnología e Innovación Productiva. Agencia Nacional de Promoción Cientifíca y Tecnológica; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Veterinarias; Argentina Fil: Rodríguez Alvarez, Juan Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Veterinarias; Argentina Fil: Machado, Claudio. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Veterinarias. Departamento de Fisiopatología. Área de Nutrición; Argentina Fil: Mateos Diaz, Cristian Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina Fil: Zunino Suarez, Alejandro Octavio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina