Guiding performance tuning for grid schedules

Grid jobs often consist of a large number of tasks. If the performance of a statically scheduled grid job is unsatisfactory, one must decide which code of which task should be improved. We propose a novel method to guide grid users as to which tasks of their grid job they should accelerate in order to reduce the makespan of the complete job. The input we need is the task schedule of the grid job, which can be derived from traces of a previous run of the job. We provide several algorithms depending on whether only one or several tasks can be improved, or whether task improvement is achieved by improvement of one processor.