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Given an array $\mathcal{A}$ of $n$ elements and a value $2 \leq k \leq n$, afrequent item or $k$-majority element is an element occurring in $\mathcal{A}$more than $n/k$ times. The $k$-majority problem requires finding all of the$k$-majority elements. In this paper we deal with parallel shared-memoryalgorithms for frequent items; we present a shared-memory version of the SpaceSaving algorithm and we study its behavior with regard to accuracy andperformance on many and multi-core processors, including the Intel Phiaccelerator. We also investigate a hybrid MPI/OpenMP version against a pure MPIbased version. Through extensive experimental results we prove that theMPI/OpenMP parallel version of the algorithm significantly enhances theperformance of the earlier pure MPI version of the same algorithm. Results alsoprove that for this algorithm the Intel Phi accelerator does not introduce anyimprovement with respect to the Xeon octa-core processor.

Parallel Space Saving on Multi and Many-Core Processors