Sorting big data on heterogeneous near-data processing systems

Big data workloads assumed recently a relevant importance in many business and scientific applications. Sorting ele-ments efficiently in big data workloads is a key operation. In this work, we analyze the implementation of the mergesort algorithm on heterogeneous systems composed of CPUs and near-data processors located on the system memory channels. For configurations with equal number of active CPU cores and near-data processors, our experiments show a per-formance speedup of up to 2.5, as well as up to 2.5× energy-per-solution reduction.