Fast networks have made it possible to aggregate distributed CPU, memory, and storage resources into Grids that can deliver considerable performance. However, achieving performance on such systems requires good performance prediction which is usually difficult due to their dynamic and heterogeneous nature. This is especially true for parallel applications whose performance is highly dependent upon the efficient coordination of their constituent components (e.g. computation and data). The goal of the AppLeS project is to develop application-level scheduling agents that provide mechanisms for automatically scheduling individual applications on production heterogeneous systems. AppLeS agents utilize the Network Weather Service (NWS) to monitor and forecast the varying performance of resources potentially usable by their applications. Each AppLeS uses static and dynamic application and system information to select viable resource configurations and evaluate their potential performance. The AppLeS then interacts with the appropriate resource management system to implement the application\'s network transfers and computational tasks. The next generation of AppLeS agents aims at providing templates that can be used for scheduling classes of structurally similar applications. In this document we introduce a template for scheduling Parameter Sweep applications (application consisting of \\em large number of independent tasks, with possible input data sharing). We have designed a general scheduling algorithm that can adapt to Grid environments and use a variety of strategies and heuristics to assign tasks and data to resources. In order to evaluate and compare those heuristics we have built a simulator as part of the template. The simulator makes it possible to rapidly conduct large numbers of experiments in a variety of environments. Our starting point was to use widely accepted heuristics that have been proposed in the litterature and venture improvements given our Grid and application model. This document presents the implementation of our simulator and explains how it will be used to obtain new research results in the field of Grid scheduling.