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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

Exploiting Grids intuitively requires developers to alter their applications, which calls for expertise on Grid programming. Gridification tools address this problem by semi-automatically making user applications to be Grid-aware. However, most of these tools produce monolithic Grid applications in which common tuning mechanisms (e.g. parallelism) are not applicable, and do not reuse existing Grid middleware services. We propose BYG (BYtecode Gridifier), a gridification tool that relies on novel bytecode rewriting techniques to parallelize and easily execute existing applications via Grid middlewares. Experiments performed by using several computing intensive applications on a cluster and a simulated wide-area Grid suggest that our techniques are effective while staying competitive compared to programmatically using such services for gridifying applications.