when a large multi-user cluster needs to access very large amounts of data, task scheduling becomes a challenge. in a heterogeneous cpu-gpu cluster with a complex application environment, the performance of each job depends on the characteristics of the underlying cluster. therefore, mapping tasks onto cpu cores and gpu devices provides significant challenges. this is an area of ongoing research; algorithms that combine and extend mapreduce and hadoop have been proposed and studied.