Scheduling Schemes for Data Farming

The use of order statistics to arrive at a scheduling regime is shown to be applicable to data farms running on second generation parallel processors Uniform and decreasing task size scheduling regimes are examined Experimental timings and a further simula tion for large scale e ects were used to exercise the scheduling regimes The paper also considers a number of other scheduling schemes for data farms It is shown that a method previously used for loop scheduling is preferable particularly as a form of automatic and generalised scheduling for data farming where there is a data dependent workload