Programming Grid Applications with GRID Superscalar

Abstract. The aim of GRID superscalar is to reduce the development complexity of Grid applications to the minimum, in such a way that writing an application for a computational Grid may be as easy as writing a sequential application. Our assumption is that Grid applications would be in a lot of cases composed of tasks, most of them repetitive. The granularity of these tasks will be of the level of simulations or programs, and the data objects will be files. GRID superscalar allows application developers to write their application in a sequential fashion. The requirements to run that sequential application in a computational Grid are the specification of the interface of the tasks that should be run in the Grid, and, at some points, calls to the GRID superscalar interface functions and link with the run-time library. GRID superscalar provides an underlying run-time that is able to detect the inherent parallelism of the sequential application and performs concurrent task submission. In addition to a data-dependence analysis based on those input/output task parameters which are files, techniques such as file renaming and file locality are applied to increase the application performance. This paper presents the current GRID superscalar prototype based on Globus Toolkit 2.x, together with examples and performance evaluation of some benchmarks