This paper evaluates the impact of task migration on gang-scheduling of parallel jobs for distributed systems. With migration, it is possible to move tasks of a job from their originally assigned set of nodes to another set of nodes, during execution of the job. This additional flexibility creates more opportunities for filling holes in the scheduling matrix. We conduct a simulation-based study of the effect of migration on average job slowdown and wait times for a large distributed system under a variety of loads. We find that migration can significantly improve these performance metrics over an important range of operating points. We also analyze the effect of the cost of migrating tasks on overall system performance.